List of Publications | Research | Beckstein Lab

@article{sexton_bayesian_2025,
	title = {Bayesian {Nonparametric} {Analysis} of {Residence} {Times} for {Protein}–{Lipid} {Interactions} in {Molecular} {Dynamics} {Simulations}},
	issn = {1549-9618},
	url = {https://doi.org/10.1021/acs.jctc.4c01522},
	doi = {10.1021/acs.jctc.4c01522},
	abstract = {Molecular Dynamics (MD) simulations are a versatile tool to investigate the interactions of proteins within their environments, in particular, of membrane proteins with the surrounding lipids. However, quantitative analysis of lipid–protein binding kinetics has remained challenging due to considerable noise and low frequency of long binding events, even in hundreds of microseconds of simulation data. Here, we apply Bayesian nonparametrics to compute residue-resolved residence time distributions from MD trajectories. Such an analysis characterizes binding processes at different time scales (quantified by their kinetic off-rate) and assigns to each trajectory frame a probability of belonging to a specific process. In this way, we classify trajectory frames in an unsupervised manner and obtain, for example, different binding poses or molecular densities based on the time scale of the process. We demonstrate our approach by characterizing interactions of cholesterol with six different G-protein-coupled receptors (A2AAR, β2AR, CB1R, CB2R, CCK1R, and CCK2R) simulated with coarse-grained MD simulations with the MARTINI model. The nonparametric Bayesian analysis allows us to connect the coarse binding time series data to the underlying molecular picture and thus not only infers accurate binding kinetics with error distributions from MD simulations but also describes molecular events responsible for the broad range of kinetic rates.},
	urldate = {2025-04-02},
	journal = {Journal of Chemical Theory and Computation},
	author = {Sexton, Ricky and Fazel, Mohamadreza and Schweiger, Maxwell and Pressé, Steve and Beckstein, Oliver},
	month = apr,
	year = {2025},
	note = {Publisher: American Chemical Society},
}

Molecular Dynamics (MD) simulations are a versatile tool to investigate the interactions of proteins within their environments, in particular, of membrane proteins with the surrounding lipids. However, quantitative analysis of lipid–protein binding kinetics has remained challenging due to considerable noise and low frequency of long binding events, even in hundreds of microseconds of simulation data. Here, we apply Bayesian nonparametrics to compute residue-resolved residence time distributions from MD trajectories. Such an analysis characterizes binding processes at different time scales (quantified by their kinetic off-rate) and assigns to each trajectory frame a probability of belonging to a specific process. In this way, we classify trajectory frames in an unsupervised manner and obtain, for example, different binding poses or molecular densities based on the time scale of the process. We demonstrate our approach by characterizing interactions of cholesterol with six different G-protein-coupled receptors (A2AAR, β2AR, CB1R, CB2R, CCK1R, and CCK2R) simulated with coarse-grained MD simulations with the MARTINI model. The nonparametric Bayesian analysis allows us to connect the coarse binding time series data to the underlying molecular picture and thus not only infers accurate binding kinetics with error distributions from MD simulations but also describes molecular events responsible for the broad range of kinetic rates.

@misc{woods_zarrtraj_2024,
	title = {Zarrtraj: {A} {Python} package for streaming molecular dynamics trajectories from cloud services},
	shorttitle = {Zarrtraj},
	url = {https://zenodo.org/records/14172229},
	doi = {10.5281/zenodo.14172229},
	abstract = {Molecular dynamics (MD) simulations provide a microscope into the behavior of atomic-scale environments otherwise prohibitively difficult to observe. However, the resulting trajectory data are too often siloed in a single institutions' HPC environment, rendering it unusable by the broader scientific community. Additionally, it is increasingly common for trajectory data to be entirely stored in a cloud storage provider, rather than a traditional on-premise storage site. Zarrtraj enables these trajectories to be read directly from cloud storage providers like AWS, Google Cloud, and Microsoft Azure into MDAnalysis, a popular Python package for analyzing trajectory data, providing a method to open up access to trajectory data to anyone with an internet connection. Enabling cloud streaming for MD trajectories empowers easier replication of published analysis results, analyses of large, conglomerate datasets from different sources, and training machine learning models without downloading and storing trajectory data.},
	urldate = {2025-02-15},
	publisher = {Zenodo},
	author = {Woods, Lawson and MacDermott-Opeskin, Hugo and Jakupovic, Edis and Zhuang, Yuxuan and Gowers, Richard and Beckstein, Oliver},
	month = nov,
	year = {2024},
	keywords = {file-format, mdanalysis, molecular-dynamics, streaming, zarr},
}

Molecular dynamics (MD) simulations provide a microscope into the behavior of atomic-scale environments otherwise prohibitively difficult to observe. However, the resulting trajectory data are too often siloed in a single institutions' HPC environment, rendering it unusable by the broader scientific community. Additionally, it is increasingly common for trajectory data to be entirely stored in a cloud storage provider, rather than a traditional on-premise storage site. Zarrtraj enables these trajectories to be read directly from cloud storage providers like AWS, Google Cloud, and Microsoft Azure into MDAnalysis, a popular Python package for analyzing trajectory data, providing a method to open up access to trajectory data to anyone with an internet connection. Enabling cloud streaming for MD trajectories empowers easier replication of published analysis results, analyses of large, conglomerate datasets from different sources, and training machine learning models without downloading and storing trajectory data.

@misc{sexton_bayesian_2024,
	title = {Bayesian nonparametric analysis of residence times for protein-lipid interactions in {Molecular} {Dynamics} simulations},
	copyright = {© 2024, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution 4.0 International), CC BY 4.0, as described at http://creativecommons.org/licenses/by/4.0/},
	url = {https://www.biorxiv.org/content/10.1101/2024.11.07.622502v1},
	doi = {10.1101/2024.11.07.622502},
	abstract = {Molecular Dynamics (MD) simulations are a versatile tool to investigate the interactions of proteins within their environments, in particular of membrane proteins with the surrounding lipids. However, quantitative analysis of lipid-protein binding kinetics has remained challenging due to considerable noise and low frequency of long binding events, even in hundreds of microseconds of simulation data. Here we apply Bayesian nonparametrics to compute residue-resolved residence time distributions from MD trajectories. Such an analysis characterizes binding processes at different timescales (quantified by their kinetic off-rate) and assigns to each trajectory frame a probability of belonging to a specific process. In this way, we classify trajectory frames in an unsupervised manner and obtain, for example, different binding poses or molecular densities based on the timescale of the process. We demonstrate our approach by characterizing interactions of cholesterol with six different G-protein coupled receptors (A2AAR, β2AR, CB1R, CB2R, CCK1R, CCK2R) simulated with coarse-grained MD simulations with the MARTINI model. The nonparametric Bayesian analysis allows us to connect the coarse binding time series data to the underlying molecular picture and, thus, not only infers accurate binding kinetics with error distributions from MD simulations but also describes molecular events responsible for the broad range of kinetic rates.},
	language = {en},
	urldate = {2024-11-10},
	publisher = {bioRxiv},
	author = {Sexton, Ricky C. and Fazel, Mohamadreza and Schweiger, Maxwell C. and Presse, Steve and Beckstein, Oliver},
	month = nov,
	year = {2024},
}

Molecular Dynamics (MD) simulations are a versatile tool to investigate the interactions of proteins within their environments, in particular of membrane proteins with the surrounding lipids. However, quantitative analysis of lipid-protein binding kinetics has remained challenging due to considerable noise and low frequency of long binding events, even in hundreds of microseconds of simulation data. Here we apply Bayesian nonparametrics to compute residue-resolved residence time distributions from MD trajectories. Such an analysis characterizes binding processes at different timescales (quantified by their kinetic off-rate) and assigns to each trajectory frame a probability of belonging to a specific process. In this way, we classify trajectory frames in an unsupervised manner and obtain, for example, different binding poses or molecular densities based on the timescale of the process. We demonstrate our approach by characterizing interactions of cholesterol with six different G-protein coupled receptors (A2AAR, β2AR, CB1R, CB2R, CCK1R, CCK2R) simulated with coarse-grained MD simulations with the MARTINI model. The nonparametric Bayesian analysis allows us to connect the coarse binding time series data to the underlying molecular picture and, thus, not only infers accurate binding kinetics with error distributions from MD simulations but also describes molecular events responsible for the broad range of kinetic rates.

@article{wu_alchemlyb_2024,
	title = {alchemlyb: the simple alchemistry library},
	volume = {9},
	issn = {2475-9066},
	shorttitle = {alchemlyb},
	url = {https://joss.theoj.org/papers/10.21105/joss.06934},
	doi = {10.21105/joss.06934},
	abstract = {alchemlyb is an open-source Python software package for the analysis of alchemical free energy
calculations, an important method in computational chemistry and biology, most notably in
the field of drug discovery (Merz et al., 2010). Its functionality contains individual composable
building blocks for all aspects of a full typical free energy analysis workflow, starting with the
extraction of raw data from the output of diverse molecular simulation packages, moving on to
data preprocessing tasks such as decorrelation of time series, using various estimators to derive
free energy estimates from simulation samples, and finally providing quality analysis tools for
data convergence checking and visualization. alchemlyb also contains high-level end-to-end
workflows that combine multiple building blocks into a user-friendly analysis pipeline from the
initial data input stage to the final results. This workflow functionality enhances accessibility
by enabling researchers from diverse scientific backgrounds, and not solely computational
chemistry specialists, to use alchemlyb effectively},
	language = {en},
	number = {101},
	urldate = {2024-09-26},
	journal = {Journal of Open Source Software},
	author = {Wu, Zhiyi and Dotson, David L. and Alibay, Irfan and Allen, Bryce K. and Barhaghi, Mohammad Soroush and Hénin, Jérôme and Joseph, Thomas T. and Kenney, Ian M. and Lee, Hyungro and Li, Haoxi and Lim, Victoria and Liu, Shuai and Marson, Domenico and Merz, Pascal T. and Schlaich, Alexander and Mobley, David and Shirts, Michael R. and Beckstein, Oliver},
	month = sep,
	year = {2024},
	pages = {6934},
}

alchemlyb is an open-source Python software package for the analysis of alchemical free energy calculations, an important method in computational chemistry and biology, most notably in the field of drug discovery (Merz et al., 2010). Its functionality contains individual composable building blocks for all aspects of a full typical free energy analysis workflow, starting with the extraction of raw data from the output of diverse molecular simulation packages, moving on to data preprocessing tasks such as decorrelation of time series, using various estimators to derive free energy estimates from simulation samples, and finally providing quality analysis tools for data convergence checking and visualization. alchemlyb also contains high-level end-to-end workflows that combine multiple building blocks into a user-friendly analysis pipeline from the initial data input stage to the final results. This workflow functionality enhances accessibility by enabling researchers from diverse scientific backgrounds, and not solely computational chemistry specialists, to use alchemlyb effectively

@article{awtrey_kinetic_2024,
	title = {Kinetic {Diagram} {Analysis}: {A} {Python} {Library} for {Calculating} {Steady}-{State} {Observables} of {Biochemical} {Systems} {Analytically}},
	issn = {1549-9618},
	shorttitle = {Kinetic {Diagram} {Analysis}},
	url = {https://doi.org/10.1021/acs.jctc.4c00688},
	doi = {10.1021/acs.jctc.4c00688},
	abstract = {Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al. (J. Gen. Physiol., 2020, 152, e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.},
	urldate = {2024-08-20},
	journal = {Journal of Chemical Theory and Computation},
	author = {Awtrey, Nikolaus Carl and Beckstein, Oliver},
	month = aug,
	year = {2024},
	note = {Publisher: American Chemical Society},
}

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis (KDA), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al. (J. Gen. Physiol., 2020, 152, e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

@misc{bai_chloride_2024,
	title = {Chloride binding and cholesterol effects on high frequency complex nonlinear capacitance ({cNLC}) in the mouse outer hair cell: experiment and molecular dynamics},
	copyright = {© 2024, Posted by Cold Spring Harbor Laboratory. The copyright holder for this pre-print is the author. All rights reserved. The material may not be redistributed, re-used or adapted without the author's permission.},
	shorttitle = {Chloride binding and cholesterol effects on high frequency complex nonlinear capacitance ({cNLC}) in the mouse outer hair cell},
	url = {https://www.biorxiv.org/content/10.1101/2024.01.29.577264v1},
	doi = {10.1101/2024.01.29.577264},
	abstract = {The function of prestin (SLC26a5), an anion transport family member, has evolved to enhance auditory sensitivity and frequency selectivity by providing mechanical feedback via outer hair cells (OHC) into the organ of Corti. The frequency extent of this boost is governed by the voltage-dependent kinetics of the protein charge movements, otherwise known as nonlinear capacitance (NLC) that we measure in membrane patches under voltage clamp. Here we extend our previous studies on guinea pig OHCs by studying the frequency response of NLC in the mouse OHC, a species with higher frequency auditory needs. We find that the characteristic frequency cut-off (Fis) for the mouse surpasses that of the guinea pig, being 27 kHz vs. 19 kHz, respectively; nevertheless, each shows significant activity in the ultrasonic range. We also evaluate the influence of anion binding on prestin frequency response. Several single point mutations within the chloride binding pocket of prestin (e.g., S396E, S398E) lack anion influence. In agreement, we show absence of anion binding through molecular dynamics (MD) simulations. NLC Fis in the S396E knock-in mouse remains the same as controls, indicating that high frequency activity is likely governed by viscoelastic loads within the membrane characterized by stretched-exponential frequency roll-off. Accordingly, treatment with MBCD, which removes membrane cholesterol, possibly from prestin itself, and can alter membrane fluidity, augments NLC Fis out to 39 kHz. Although interactions between membrane lipid and prestin have been suggested from structural studies to arise at their interfacial boundaries within the membrane, our MD simulations suggest that phospholipids can insert within transmembrane domains of prestin during voltage perturbation. Such novel lipid-protein interactions could account for our observed changes in the phase of prestin voltage-sensor charge movements across frequency. We hypothesize that because prestin tertiary structures of all species studied to-date are indistinguishable, it is likely that any special auditory requirements of individual species for cochlear amplification have evolved to capitalize on prestin performance by modifying, not the protein itself, but the external loads on the protein, including those within the membrane and organ of Corti.},
	language = {en},
	urldate = {2024-01-31},
	publisher = {bioRxiv},
	author = {Bai, Jun-Ping and Zhang, Chenou and Renigunta, Vijay and Oliver, Dominik and Navaratnam, Dhasakumar S. and Beckstein, Oliver and Santos-Sacchi, Joseph},
	month = jan,
	year = {2024},
	note = {Pages: 2024.01.29.577264
Section: New Results},
}

The function of prestin (SLC26a5), an anion transport family member, has evolved to enhance auditory sensitivity and frequency selectivity by providing mechanical feedback via outer hair cells (OHC) into the organ of Corti. The frequency extent of this boost is governed by the voltage-dependent kinetics of the protein charge movements, otherwise known as nonlinear capacitance (NLC) that we measure in membrane patches under voltage clamp. Here we extend our previous studies on guinea pig OHCs by studying the frequency response of NLC in the mouse OHC, a species with higher frequency auditory needs. We find that the characteristic frequency cut-off (Fis) for the mouse surpasses that of the guinea pig, being 27 kHz vs. 19 kHz, respectively; nevertheless, each shows significant activity in the ultrasonic range. We also evaluate the influence of anion binding on prestin frequency response. Several single point mutations within the chloride binding pocket of prestin (e.g., S396E, S398E) lack anion influence. In agreement, we show absence of anion binding through molecular dynamics (MD) simulations. NLC Fis in the S396E knock-in mouse remains the same as controls, indicating that high frequency activity is likely governed by viscoelastic loads within the membrane characterized by stretched-exponential frequency roll-off. Accordingly, treatment with MBCD, which removes membrane cholesterol, possibly from prestin itself, and can alter membrane fluidity, augments NLC Fis out to 39 kHz. Although interactions between membrane lipid and prestin have been suggested from structural studies to arise at their interfacial boundaries within the membrane, our MD simulations suggest that phospholipids can insert within transmembrane domains of prestin during voltage perturbation. Such novel lipid-protein interactions could account for our observed changes in the phase of prestin voltage-sensor charge movements across frequency. We hypothesize that because prestin tertiary structures of all species studied to-date are indistinguishable, it is likely that any special auditory requirements of individual species for cochlear amplification have evolved to capitalize on prestin performance by modifying, not the protein itself, but the external loads on the protein, including those within the membrane and organ of Corti.

@article{becker_mechanism_2023,
	title = {Mechanism of substrate binding and transport in {BASS} transporters},
	volume = {12},
	issn = {2050-084X},
	url = {https://doi.org/10.7554/eLife.89167},
	doi = {10.7554/eLife.89167},
	abstract = {The bile acid sodium symporter (BASS) family transports a wide array of molecules across membranes, including bile acids in humans, and small metabolites in plants. These transporters, many of which are sodium-coupled, have been shown to use an elevator mechanism of transport, but exactly how substrate binding is coupled to sodium ion binding and transport is not clear. Here, we solve the crystal structure at 2.3 Å of a transporter from Neisseria meningitidis (ASBTNM) in complex with pantoate, a potential substrate of ASBTNM. The BASS family is characterised by two helices that cross-over in the centre of the protein in an arrangement that is intricately held together by two sodium ions. We observe that the pantoate binds, specifically, between the N-termini of two of the opposing helices in this cross-over region. During molecular dynamics simulations the pantoate remains in this position when sodium ions are present but is more mobile in their absence. Comparison of structures in the presence and absence of pantoate demonstrates that pantoate elicits a conformational change in one of the cross-over helices. This modifies the interface between the two domains that move relative to one another to elicit the elevator mechanism. These results have implications, not only for ASBTNM but for the BASS family as a whole and indeed other transporters that work through the elevator mechanism.},
	urldate = {2023-11-14},
	journal = {eLife},
	author = {Becker, Patrick and Naughton, Fiona and Brotherton, Deborah and Pacheco-Gomez, Raul and Beckstein, Oliver and Cameron, Alexander D},
	editor = {Stockbridge, Randy B and Maduke, Merritt},
	month = nov,
	year = {2023},
	note = {Publisher: eLife Sciences Publications, Ltd},
	keywords = {bile acid symporters, elevator mechanism, sodium-coupled transport},
	pages = {RP89167},
}

The bile acid sodium symporter (BASS) family transports a wide array of molecules across membranes, including bile acids in humans, and small metabolites in plants. These transporters, many of which are sodium-coupled, have been shown to use an elevator mechanism of transport, but exactly how substrate binding is coupled to sodium ion binding and transport is not clear. Here, we solve the crystal structure at 2.3 Å of a transporter from Neisseria meningitidis (ASBTNM) in complex with pantoate, a potential substrate of ASBTNM. The BASS family is characterised by two helices that cross-over in the centre of the protein in an arrangement that is intricately held together by two sodium ions. We observe that the pantoate binds, specifically, between the N-termini of two of the opposing helices in this cross-over region. During molecular dynamics simulations the pantoate remains in this position when sodium ions are present but is more mobile in their absence. Comparison of structures in the presence and absence of pantoate demonstrates that pantoate elicits a conformational change in one of the cross-over helices. This modifies the interface between the two domains that move relative to one another to elicit the elevator mechanism. These results have implications, not only for ASBTNM but for the BASS family as a whole and indeed other transporters that work through the elevator mechanism.

@article{hussein_energy_2023,
	title = {Energy coupling and stoichiometry of {Zn2}+/{H}+ antiport by the prokaryotic cation diffusion facilitator {YiiP}},
	volume = {12},
	issn = {2050-084X},
	url = {https://doi.org/10.7554/eLife.87167},
	doi = {10.7554/eLife.87167},
	abstract = {YiiP from Shewanella oneidensis is a prokaryotic Zn2+/H+ antiporter that serves as a model for the Cation Diffusion Facilitator (CDF) superfamily, members of which are generally responsible for homeostasis of transition metal ions. Previous studies of YiiP as well as related CDF transporters have established a homodimeric architecture and the presence of three distinct Zn2+ binding sites named A, B, and C. In this study, we use cryo-EM, microscale thermophoresis and molecular dynamics simulations to address the structural and functional roles of individual sites as well as the interplay between Zn2+ binding and protonation. Structural studies indicate that site C in the cytoplasmic domain is primarily responsible for stabilizing the dimer and that site B at the cytoplasmic membrane surface controls the structural transition from an inward facing conformation to an occluded conformation. Binding data show that intramembrane site A, which is directly responsible for transport, has a dramatic pH dependence consistent with coupling to the proton motive force. A comprehensive thermodynamic model encompassing Zn2+ binding and protonation states of individual residues indicates a transport stoichiometry of 1 Zn2+ to 2–3 H+ depending on the external pH. This stoichiometry would be favorable in a physiological context, allowing the cell to use the proton gradient as well as the membrane potential to drive the export of Zn2+.},
	urldate = {2023-11-02},
	journal = {eLife},
	author = {Hussein, Adel and Fan, Shujie and Lopez-Redondo, Maria and Kenney, Ian and Zhang, Xihui and Beckstein, Oliver and Stokes, David L},
	editor = {Maduke, Merritt},
	month = oct,
	year = {2023},
	note = {Publisher: eLife Sciences Publications, Ltd},
	keywords = {Shewanella oneidensis, YiiP, membrane transport, zinc proton antiport},
	pages = {RP87167},
}

YiiP from Shewanella oneidensis is a prokaryotic Zn2+/H+ antiporter that serves as a model for the Cation Diffusion Facilitator (CDF) superfamily, members of which are generally responsible for homeostasis of transition metal ions. Previous studies of YiiP as well as related CDF transporters have established a homodimeric architecture and the presence of three distinct Zn2+ binding sites named A, B, and C. In this study, we use cryo-EM, microscale thermophoresis and molecular dynamics simulations to address the structural and functional roles of individual sites as well as the interplay between Zn2+ binding and protonation. Structural studies indicate that site C in the cytoplasmic domain is primarily responsible for stabilizing the dimer and that site B at the cytoplasmic membrane surface controls the structural transition from an inward facing conformation to an occluded conformation. Binding data show that intramembrane site A, which is directly responsible for transport, has a dramatic pH dependence consistent with coupling to the proton motive force. A comprehensive thermodynamic model encompassing Zn2+ binding and protonation states of individual residues indicates a transport stoichiometry of 1 Zn2+ to 2–3 H+ depending on the external pH. This stoichiometry would be favorable in a physiological context, allowing the cell to use the proton gradient as well as the membrane potential to drive the export of Zn2+.

@article{kenney_thermodynamically_2023,
	title = {Thermodynamically consistent determination of free energies and rates in kinetic cycle models},
	volume = {3},
	issn = {2667-0747},
	url = {https://www.sciencedirect.com/science/article/pii/S2667074723000216},
	doi = {10.1016/j.bpr.2023.100120},
	abstract = {Kinetic and thermodynamic models of biological systems are commonly used to connect microscopic features to system function in a bottom-up multiscale approach. The parameters of such models—free energy differences for equilibrium properties and in general rates for equilibrium and out-of-equilibrium observables—have to be measured by different experiments or calculated from multiple computer simulations. All such parameters necessarily come with uncertainties so that when they are naively combined in a full model of the process of interest, they will generally violate fundamental statistical mechanical equalities, namely detailed balance and an equality of forward/backward rate products in cycles due to Hill. If left uncorrected, such models can produce arbitrary outputs that are physically inconsistent. Here, we develop a maximum likelihood approach (named multibind) based on the so-called potential graph to combine kinetic or thermodynamic measurements to yield state-resolved models that are thermodynamically consistent while being most consistent with the provided data and their uncertainties. We demonstrate the approach with two theoretical models, a generic two-proton binding site and a simplified model of a sodium/proton antiporter. We also describe an algorithm to use the multibind approach to solve the inverse problem of determining microscopic quantities from macroscopic measurements and, as an example, we predict the microscopic pKa values and protonation states of a small organic molecule from 1D NMR data. The multibind approach is applicable to any thermodynamic or kinetic model that describes a system as transitions between well-defined states with associated free energy differences or rates between these states. A Python package multibind, which implements the approach described here, is made publicly available under the MIT Open Source license.},
	number = {3},
	urldate = {2023-08-16},
	journal = {Biophysical Reports},
	author = {Kenney, Ian M. and Beckstein, Oliver},
	month = sep,
	year = {2023},
	pages = {100120},
}

Kinetic and thermodynamic models of biological systems are commonly used to connect microscopic features to system function in a bottom-up multiscale approach. The parameters of such models—free energy differences for equilibrium properties and in general rates for equilibrium and out-of-equilibrium observables—have to be measured by different experiments or calculated from multiple computer simulations. All such parameters necessarily come with uncertainties so that when they are naively combined in a full model of the process of interest, they will generally violate fundamental statistical mechanical equalities, namely detailed balance and an equality of forward/backward rate products in cycles due to Hill. If left uncorrected, such models can produce arbitrary outputs that are physically inconsistent. Here, we develop a maximum likelihood approach (named multibind) based on the so-called potential graph to combine kinetic or thermodynamic measurements to yield state-resolved models that are thermodynamically consistent while being most consistent with the provided data and their uncertainties. We demonstrate the approach with two theoretical models, a generic two-proton binding site and a simplified model of a sodium/proton antiporter. We also describe an algorithm to use the multibind approach to solve the inverse problem of determining microscopic quantities from macroscopic measurements and, as an example, we predict the microscopic pKa values and protonation states of a small organic molecule from 1D NMR data. The multibind approach is applicable to any thermodynamic or kinetic model that describes a system as transitions between well-defined states with associated free energy differences or rates between these states. A Python package multibind, which implements the approach described here, is made publicly available under the MIT Open Source license.

@article{alibay_mdakits_2023,
	title = {{MDAKits}: {A} {Framework} for {FAIR}-{Compliant} {Molecular} {Simulation} {Analysis}},
	shorttitle = {{MDAKits}},
	url = {https://conference.scipy.org/proceedings/scipy2023/ian_kenney.html},
	doi = {10.25080/gerudo-f2bc6f59-00a},
	urldate = {2023-08-09},
	journal = {Proceedings of the 22nd Python in Science Conference},
	author = {Alibay, Irfan and Wang, Lily and Naughton, Fiona and Kenney, Ian and Barnoud, Jonathan and Gowers, Richard J. and Beckstein, Oliver},
	year = {2023},
	note = {Conference Name: Proceedings of the 22nd Python in Science Conference},
	pages = {76--84},
}

@article{winkelmann_crystal_2022,
	title = {Crystal structure of the {Na}+/{H}+ antiporter {NhaA} at active {pH} reveals the mechanistic basis for {pH} sensing},
	volume = {13},
	copyright = {2022 The Author(s)},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-022-34120-z},
	doi = {10.1038/s41467-022-34120-z},
	abstract = {The strict exchange of protons for sodium ions across cell membranes by Na+/H+ exchangers is a fundamental mechanism for cell homeostasis. At active pH, Na+/H+ exchange can be modelled as competition between H+ and Na+ to an ion-binding site, harbouring either one or two aspartic-acid residues. Nevertheless, extensive analysis on the model Na+/H+ antiporter NhaA from Escherichia coli, has shown that residues on the cytoplasmic surface, termed the pH sensor, shifts the pH at which NhaA becomes active. It was unclear how to incorporate the pH senor model into an alternating-access mechanism based on the NhaA structure at inactive pH 4. Here, we report the crystal structure of NhaA at active pH 6.5, and to an improved resolution of 2.2 Å. We show that at pH 6.5, residues in the pH sensor rearrange to form new salt-bridge interactions involving key histidine residues that widen the inward-facing cavity. What we now refer to as a pH gate, triggers a conformational change that enables water and Na+ to access the ion-binding site, as supported by molecular dynamics (MD) simulations. Our work highlights a unique, channel-like switch prior to substrate translocation in a secondary-active transporter.},
	language = {en},
	number = {1},
	urldate = {2022-12-13},
	journal = {Nature Communications},
	author = {Winkelmann, Iven and Uzdavinys, Povilas and Kenney, Ian M. and Brock, Joseph and Meier, Pascal F. and Wagner, Lina-Marie and Gabriel, Florian and Jung, Sukkyeong and Matsuoka, Rei and von Ballmoos, Christoph and Beckstein, Oliver and Drew, David},
	month = oct,
	year = {2022},
	note = {Number: 1
Publisher: Nature Publishing Group},
	keywords = {Bioenergetics, Membrane proteins, Membrane structure and assembly, X-ray crystallography},
	pages = {6383},
}

The strict exchange of protons for sodium ions across cell membranes by Na+/H+ exchangers is a fundamental mechanism for cell homeostasis. At active pH, Na+/H+ exchange can be modelled as competition between H+ and Na+ to an ion-binding site, harbouring either one or two aspartic-acid residues. Nevertheless, extensive analysis on the model Na+/H+ antiporter NhaA from Escherichia coli, has shown that residues on the cytoplasmic surface, termed the pH sensor, shifts the pH at which NhaA becomes active. It was unclear how to incorporate the pH senor model into an alternating-access mechanism based on the NhaA structure at inactive pH 4. Here, we report the crystal structure of NhaA at active pH 6.5, and to an improved resolution of 2.2 Å. We show that at pH 6.5, residues in the pH sensor rearrange to form new salt-bridge interactions involving key histidine residues that widen the inward-facing cavity. What we now refer to as a pH gate, triggers a conformational change that enables water and Na+ to access the ion-binding site, as supported by molecular dynamics (MD) simulations. Our work highlights a unique, channel-like switch prior to substrate translocation in a secondary-active transporter.

@article{beckstein_general_2022,
	title = {General principles of secondary active transporter function},
	volume = {3},
	url = {https://aip.scitation.org/doi/10.1063/5.0047967},
	doi = {10.1063/5.0047967},
	abstract = {Transport of ions and small molecules across the cell membrane against electrochemical gradients is catalyzed by integral membrane proteins that use a source of free energy to drive the energetically uphill flux of the transported substrate. Secondary active transporters couple the spontaneous influx of a “driving” ion such as Na+ or H+ to the flux of the substrate. The thermodynamics of such cyclical non-equilibrium systems are well understood, and recent work has focused on the molecular mechanism of secondary active transport. The fact that these transporters change their conformation between an inward-facing and outward-facing conformation in a cyclical fashion, called the alternating access model, is broadly recognized as the molecular framework in which to describe transporter function. However, only with the advent of high resolution crystal structures and detailed computer simulations, it has become possible to recognize common molecular-level principles between disparate transporter families. Inverted repeat symmetry in secondary active transporters has shed light onto how protein structures can encode a bi-stable two-state system. Based on structural data, three broad classes of alternating access transitions have been described as rocker-switch, rocking-bundle, and elevator mechanisms. More detailed analysis indicates that transporters can be understood as gated pores with at least two coupled gates. These gates are not just a convenient cartoon element to illustrate a putative mechanism but map to distinct parts of the transporter protein. Enumerating all distinct gate states naturally includes occluded states in the alternating access picture and also suggests what kind of protein conformations might be observable. By connecting the possible conformational states and ion/substrate bound states in a kinetic model, a unified picture emerges in which the symporter, antiporter, and uniporter functions are extremes in a continuum of functionality. As usual with biological systems, few principles and rules are absolute and exceptions are discussed as well as how biological complexity may be integrated in quantitative kinetic models that may provide a bridge from the structure to function.},
	number = {1},
	urldate = {2022-04-04},
	journal = {Biophysics Reviews},
	author = {Beckstein, Oliver and Naughton, Fiona},
	month = mar,
	year = {2022},
	note = {Publisher: American Institute of Physics},
	pages = {011307},
}

Transport of ions and small molecules across the cell membrane against electrochemical gradients is catalyzed by integral membrane proteins that use a source of free energy to drive the energetically uphill flux of the transported substrate. Secondary active transporters couple the spontaneous influx of a “driving” ion such as Na+ or H+ to the flux of the substrate. The thermodynamics of such cyclical non-equilibrium systems are well understood, and recent work has focused on the molecular mechanism of secondary active transport. The fact that these transporters change their conformation between an inward-facing and outward-facing conformation in a cyclical fashion, called the alternating access model, is broadly recognized as the molecular framework in which to describe transporter function. However, only with the advent of high resolution crystal structures and detailed computer simulations, it has become possible to recognize common molecular-level principles between disparate transporter families. Inverted repeat symmetry in secondary active transporters has shed light onto how protein structures can encode a bi-stable two-state system. Based on structural data, three broad classes of alternating access transitions have been described as rocker-switch, rocking-bundle, and elevator mechanisms. More detailed analysis indicates that transporters can be understood as gated pores with at least two coupled gates. These gates are not just a convenient cartoon element to illustrate a putative mechanism but map to distinct parts of the transporter protein. Enumerating all distinct gate states naturally includes occluded states in the alternating access picture and also suggests what kind of protein conformations might be observable. By connecting the possible conformational states and ion/substrate bound states in a kinetic model, a unified picture emerges in which the symporter, antiporter, and uniporter functions are extremes in a continuum of functionality. As usual with biological systems, few principles and rules are absolute and exceptions are discussed as well as how biological complexity may be integrated in quantitative kinetic models that may provide a bridge from the structure to function.

@article{matsuoka_structure_2022,
	title = {Structure, mechanism and lipid-mediated remodeling of the mammalian {Na}+/{H}+ exchanger {NHA2}},
	volume = {29},
	language = {en},
	journal = {Molecular Biology},
	author = {Matsuoka, Rei and Fudim, Roman and Jung, Sukkyeong and Zhang, Chenou and Bazzone, Andre and Chatzikyriakidou, Yurie and Robinson, Carol V and Nomura, Norimichi and Iwata, So and Landreh, Michael and Orellana, Laura and Beckstein, Oliver and Drew, David},
	year = {2022},
	pages = {38},
}

@incollection{tielker_perspective_2021,
	series = {{ACS} {Symposium} {Series}},
	title = {Perspective on the {SAMPL} and {D3R} {Blind} {Prediction} {Challenges} for {Physics}-{Based} {Free} {Energy} {Methods}},
	volume = {1397},
	isbn = {978-0-8412-9806-4},
	url = {https://doi.org/10.1021/bk-2021-1397.ch003},
	abstract = {Solvation and binding thermodynamics of a drug-like molecule is quantified by the respective free energy (FE) change that governs physical properties like log P/log D and binding affinities as well as more complex features such as solubility or permeability. The drug discovery process benefits significantly from reliable predictions of FEs, which are hence a key area for the theoretical and modeling community. Despite the clear physical background rooted in statistical mechanics, the desired accuracy goal is hard to achieve. Current modeling methods still need to be improved in various areas related to the FE problem, such as the quality of force fields and quantum-mechanical approximations, the efficiency of sampling algorithms as well as the robustness of computational workflows. In this context, blind prediction challenges, where participants are tasked with testing their computational methods and workflows on compound property predictions without knowing the experimental data, are excellent testbeds to evaluate and improve the modeling methodology. SAMPL (Statistical Assessment of the Modeling of Proteins and Ligands) and Drug Design Data Resource-Grand Challenges (D3R-GCs) represent widely known initiatives demonstrating how the “blind prediction” concept boosts the development of FE predictions. In this chapter, we summarize the status of recent SAMPL and D3R-GCs from the point of view of long-time participants, with the aim of providing the community with a collection of datasets and references.},
	number = {1397},
	urldate = {2021-11-20},
	booktitle = {Free {Energy} {Methods} in {Drug} {Discovery}: {Current} {State} and {Future} {Directions}},
	publisher = {American Chemical Society},
	author = {Tielker, Nicolas and Eberlein, Lukas and Beckstein, Oliver and Güssregen, Stefan and Iorga, Bogdan I. and Kast, Stefan M. and Liu, Shuai},
	editor = {Armacost, Kira A. and Thompson, David C.},
	month = nov,
	year = {2021},
	doi = {10.1021/bk-2021-1397.ch003},
	note = {Section: 3},
	pages = {67--107},
}

Solvation and binding thermodynamics of a drug-like molecule is quantified by the respective free energy (FE) change that governs physical properties like log P/log D and binding affinities as well as more complex features such as solubility or permeability. The drug discovery process benefits significantly from reliable predictions of FEs, which are hence a key area for the theoretical and modeling community. Despite the clear physical background rooted in statistical mechanics, the desired accuracy goal is hard to achieve. Current modeling methods still need to be improved in various areas related to the FE problem, such as the quality of force fields and quantum-mechanical approximations, the efficiency of sampling algorithms as well as the robustness of computational workflows. In this context, blind prediction challenges, where participants are tasked with testing their computational methods and workflows on compound property predictions without knowing the experimental data, are excellent testbeds to evaluate and improve the modeling methodology. SAMPL (Statistical Assessment of the Modeling of Proteins and Ligands) and Drug Design Data Resource-Grand Challenges (D3R-GCs) represent widely known initiatives demonstrating how the “blind prediction” concept boosts the development of FE predictions. In this chapter, we summarize the status of recent SAMPL and D3R-GCs from the point of view of long-time participants, with the aim of providing the community with a collection of datasets and references.

@techreport{matsuoka_structure_2021,
	title = {Structure and lipid-mediated remodelling mechanism of the {Na}+/{H}+ exchanger {NHA2}},
	copyright = {© 2021, Posted by Cold Spring Harbor Laboratory. The copyright holder for this pre-print is the author. All rights reserved. The material may not be redistributed, re-used or adapted without the author's permission.},
	url = {https://www.biorxiv.org/content/10.1101/2021.07.22.453398v1},
	abstract = {Na+/H+ exchangers catalyse an ion-exchange activity that is carried out in most, if not all cells. SLC9B2, also known as NHA2, correlates with the long-sought after sodium/lithium (Na+/Li+) exchanger linked to the pathogenesis of diabetes mellitus and essential hypertension in humans. Despite its functional importance, structural information and the molecular basis of its ion-exchange mechanism have been lacking. Here, we report the cryo EM structures of bison NHA2 in detergent and in nanodiscs at 3.0 and 3.5 Å resolution, respectively. NHA2 shares closest structural similarity to the bacterial electrogenic Na+/H+ antiporter NapA, rather than other mammalian SLC9A members. Nevertheless, SSM-based electrophysiology results with NHA2 show the catalysis of electroneutral rather than electrogenic ion exchange, and the ion-binding site is quite distinctive, with a tryptophan-arginine- glutamate triad separated from the well-established ion-binding aspartates. These triad residues fine-tune ion binding specificity, as demonstrated by a salt-bridge swap mutant that converts NHA2 into a Li+-specific transporter. Strikingly, an additional N-terminal helix in NHA2 establishes a unique homodimer with a large ∼ 25 Å intracellular gap between protomers. In the presence of phosphatidylinositol lipids, the N-terminal helix rearranges and closes this gap. We confirm that dimerization of NHA2 is required for activity in vivo, and propose that the N- terminal helix has evolved as a lipid-mediated remodelling switch for regulation of transport activity.},
	language = {en},
	urldate = {2021-08-31},
	author = {Matsuoka, Rei and Fudim, Roman and Jung, Sukkyeong and Zhang, Chenou and Bazzone, Andre and Chatzikyriakidou, Yurie and Nomura, Norimichi and Iwata, So and Orellana, Laura and Beckstein, Oliver and Drew, David},
	month = jul,
	year = {2021},
	doi = {10.1101/2021.07.22.453398},
	note = {Company: Cold Spring Harbor Laboratory
Distributor: Cold Spring Harbor Laboratory
Label: Cold Spring Harbor Laboratory
Section: New Results
Type: article},
	pages = {2021.07.22.453398},
}

Na+/H+ exchangers catalyse an ion-exchange activity that is carried out in most, if not all cells. SLC9B2, also known as NHA2, correlates with the long-sought after sodium/lithium (Na+/Li+) exchanger linked to the pathogenesis of diabetes mellitus and essential hypertension in humans. Despite its functional importance, structural information and the molecular basis of its ion-exchange mechanism have been lacking. Here, we report the cryo EM structures of bison NHA2 in detergent and in nanodiscs at 3.0 and 3.5 Å resolution, respectively. NHA2 shares closest structural similarity to the bacterial electrogenic Na+/H+ antiporter NapA, rather than other mammalian SLC9A members. Nevertheless, SSM-based electrophysiology results with NHA2 show the catalysis of electroneutral rather than electrogenic ion exchange, and the ion-binding site is quite distinctive, with a tryptophan-arginine- glutamate triad separated from the well-established ion-binding aspartates. These triad residues fine-tune ion binding specificity, as demonstrated by a salt-bridge swap mutant that converts NHA2 into a Li+-specific transporter. Strikingly, an additional N-terminal helix in NHA2 establishes a unique homodimer with a large ∼ 25 Å intracellular gap between protomers. In the presence of phosphatidylinositol lipids, the N-terminal helix rearranges and closes this gap. We confirm that dimerization of NHA2 is required for activity in vivo, and propose that the N- terminal helix has evolved as a lipid-mediated remodelling switch for regulation of transport activity.

@inproceedings{jakupovic_mpi-parallel_2021,
	address = {Austin, TX},
	title = {{MPI}-parallel {Molecular} {Dynamics} {Trajectory} {Analysis} with the {H5MD} {Format} in the {MDAnalysis} {Python} {Package}},
	url = {https://conference.scipy.org/proceedings/scipy2021/edis_jakupovic.html},
	doi = {10.25080/majora-1b6fd038-005},
	abstract = {Molecular dynamics (MD) computer simulations help elucidate details of the molecular processes in complex biological systems, from protein dynamics to drug discovery. One major issue is that these MD simulation files are now commonly terabytes in size, which means analyzing the data from these files becomes a painstakingly expensive task. In the age of national supercomputers, methods of parallel analysis are becoming a necessity for the efficient use of time and high performance computing (HPC) resources but for any approach to parallel analysis, simply reading the file from disk becomes the performance bottleneck that limits overall analysis speed. One promising way around this file I/O hurdle is to use a parallel message passing interface (MPI) implementation with the HDF5 (Hierarchical Data Format 5) file format to access a single file simultaneously with numerous processes on a parallel file system. Our previous feasibility study suggested that this combination can lead to favorable parallel scaling with hundreds of CPU cores, so we implemented a fast and user-friendly HDF5 reader (the H5MDReader class) that adheres to H5MD (HDF5 for Molecular Dynamics) specifications. We made H5MDReader (together with a H5MD output class H5MDWriter) available in the MDAnalysis library, a Python package that simplifies the process of reading and writing various popular MD file formats by providing a streamlined user-interface that is independent of any specific file format. We benchmarked H5MDReader's parallel file reading capabilities on three HPC clusters: ASU Agave, SDSC Comet, and PSC Bridges. The benchmark consisted of a simple split-apply-combine scheme of an I/O bound task that split a 90k frame (113 GiB) coordinate trajectory into chunks for processes, where each process performed the commonly used RMSD (root mean square distance after optimal structural superposition) calculation on their chunk of data, and then gathered the results back to the root process. For baseline performance, we found maximum I/O speedups at 2 full nodes, with Agave showing 20x, and a maximum computation speedup on Comet of 373x on 384 cores (all three HPCs scaled well in their computation task). We went on to test a series of optimizations attempting to speed up I/O performance, including adjusting file system stripe count, implementing a masked array feature that only loads relevant data for the computation task, front loading all I/O by loading the entire trajectory into memory, and manually adjusting the HDF5 dataset chunk shapes. We found the largest improvement in I/O performance by optimizing the chunk shape of the HDF5 datasets to match the iterative access pattern of our analysis benchmark. With respect to baseline serial performance, our best result was a 98x speedup at 112 cores on ASU Agave. In terms of absolute time saved, the analysis went from 4623 seconds in the baseline serial run to 47 seconds in the parallel, properly chunked run. Our results emphasize the fact that file I/O is not just dependent on the access pattern of the file, but more so the synergy between access pattern and the layout of the file on disk.},
	urldate = {2021-07-05},
	booktitle = {Proceedings of the 20th {Python} in {Science} {Conference}},
	author = {Jakupovic, Edis and Beckstein, Oliver},
	editor = {Agarwal, Meghann and Calloway, Chris and Niederhut, Dillon and Shupe, David},
	year = {2021},
	pages = {40--48},
}

Molecular dynamics (MD) computer simulations help elucidate details of the molecular processes in complex biological systems, from protein dynamics to drug discovery. One major issue is that these MD simulation files are now commonly terabytes in size, which means analyzing the data from these files becomes a painstakingly expensive task. In the age of national supercomputers, methods of parallel analysis are becoming a necessity for the efficient use of time and high performance computing (HPC) resources but for any approach to parallel analysis, simply reading the file from disk becomes the performance bottleneck that limits overall analysis speed. One promising way around this file I/O hurdle is to use a parallel message passing interface (MPI) implementation with the HDF5 (Hierarchical Data Format 5) file format to access a single file simultaneously with numerous processes on a parallel file system. Our previous feasibility study suggested that this combination can lead to favorable parallel scaling with hundreds of CPU cores, so we implemented a fast and user-friendly HDF5 reader (the H5MDReader class) that adheres to H5MD (HDF5 for Molecular Dynamics) specifications. We made H5MDReader (together with a H5MD output class H5MDWriter) available in the MDAnalysis library, a Python package that simplifies the process of reading and writing various popular MD file formats by providing a streamlined user-interface that is independent of any specific file format. We benchmarked H5MDReader's parallel file reading capabilities on three HPC clusters: ASU Agave, SDSC Comet, and PSC Bridges. The benchmark consisted of a simple split-apply-combine scheme of an I/O bound task that split a 90k frame (113 GiB) coordinate trajectory into chunks for processes, where each process performed the commonly used RMSD (root mean square distance after optimal structural superposition) calculation on their chunk of data, and then gathered the results back to the root process. For baseline performance, we found maximum I/O speedups at 2 full nodes, with Agave showing 20x, and a maximum computation speedup on Comet of 373x on 384 cores (all three HPCs scaled well in their computation task). We went on to test a series of optimizations attempting to speed up I/O performance, including adjusting file system stripe count, implementing a masked array feature that only loads relevant data for the computation task, front loading all I/O by loading the entire trajectory into memory, and manually adjusting the HDF5 dataset chunk shapes. We found the largest improvement in I/O performance by optimizing the chunk shape of the HDF5 datasets to match the iterative access pattern of our analysis benchmark. With respect to baseline serial performance, our best result was a 98x speedup at 112 cores on ASU Agave. In terms of absolute time saved, the analysis went from 4623 seconds in the baseline serial run to 47 seconds in the parallel, properly chunked run. Our results emphasize the fact that file I/O is not just dependent on the access pattern of the file, but more so the synergy between access pattern and the layout of the file on disk.

@article{fan_precise_2021,
	title = {Precise force-field-based calculations of octanol-water partition coefficients for the {SAMPL7} molecules},
	issn = {1573-4951},
	url = {https://doi.org/10.1007/s10822-021-00407-4},
	doi = {10.1007/s10822-021-00407-4},
	abstract = {We predicted water-octanol partition coefficients for the molecules in the SAMPL7 challenge with explicit solvent classical molecular dynamics (MD) simulations. Water hydration free energies and octanol solvation free energies were calculated with a windowed alchemical free energy approach. Three commonly used force fields (AMBER GAFF, CHARMM CGenFF, OPLS-AA) were tested. Special emphasis was placed on converging all simulations, using a criterion developed for the SAMPL6 challenge. In aggregate, over 1000 \$\${\textbackslash}mu\$\$s of simulations were performed, with some free energy windows remaining not fully converged even after 1 \$\${\textbackslash}mu\$\$s of simulation time. Nevertheless, the amount of sampling produced \$\${\textbackslash}log P\_\{ow\}\$\$estimates with a precision of 0.1 log units or better for converged simulations. Despite being probably as fully sampled as can expected and is feasible, the agreement with experiment remained modest for all force fields, with no force field performing better than 1.6 in root mean squared error. Overall, our results indicate that a large amount of sampling is necessary to produce precise \$\${\textbackslash}log P\_\{ow\}\$\$predictions for the SAMPL7 compounds and that high precision does not necessarily lead to high accuracy. Thus, fundamental problems remain to be solved for physics-based \$\${\textbackslash}log P\_\{ow\}\$\$predictions.},
	language = {en},
	urldate = {2021-07-13},
	journal = {Journal of Computer-Aided Molecular Design},
	author = {Fan, Shujie and Nedev, Hristo and Vijayan, Ranjit and Iorga, Bogdan I. and Beckstein, Oliver},
	month = jul,
	year = {2021},
}

We predicted water-octanol partition coefficients for the molecules in the SAMPL7 challenge with explicit solvent classical molecular dynamics (MD) simulations. Water hydration free energies and octanol solvation free energies were calculated with a windowed alchemical free energy approach. Three commonly used force fields (AMBER GAFF, CHARMM CGenFF, OPLS-AA) were tested. Special emphasis was placed on converging all simulations, using a criterion developed for the SAMPL6 challenge. In aggregate, over 1000  $$\mu$$ s of simulations were performed, with some free energy windows remaining not fully converged even after 1  $$\mu$$ s of simulation time. Nevertheless, the amount of sampling produced $$\log P_\ow\$$estimates with a precision of 0.1 log units or better for converged simulations. Despite being probably as fully sampled as can expected and is feasible, the agreement with experiment remained modest for all force fields, with no force field performing better than 1.6 in root mean squared error. Overall, our results indicate that a large amount of sampling is necessary to produce precise$$ \log P_\ow\ $$predictions for the SAMPL7 compounds and that high precision does not necessarily lead to high accuracy. Thus, fundamental problems remain to be solved for physics-based$$ \log P_\ow\$$predictions.

@article{lopez-redondo_zinc_2021,
	title = {Zinc binding alters the conformational dynamics and drives the transport cycle of the cation diffusion facilitator {YiiP}},
	volume = {153},
	issn = {0022-1295},
	url = {https://doi.org/10.1085/jgp.202112873},
	doi = {10.1085/jgp.202112873},
	abstract = {YiiP is a secondary transporter that couples Zn2+ transport to the proton motive force. Structural studies of YiiP from prokaryotes and Znt8 from humans have revealed three different Zn2+ sites and a conserved homodimeric architecture. These structures define the inward-facing and outward-facing states that characterize the archetypal alternating access mechanism of transport. To study the effects of Zn2+ binding on the conformational transition, we use cryo-EM together with molecular dynamics simulation to compare structures of YiiP from Shewanella oneidensis in the presence and absence of Zn2+. To enable single-particle cryo-EM, we used a phage-display library to develop a Fab antibody fragment with high affinity for YiiP, thus producing a YiiP/Fab complex. To perform MD simulations, we developed a nonbonded dummy model for Zn2+ and validated its performance with known Zn2+-binding proteins. Using these tools, we find that, in the presence of Zn2+, YiiP adopts an inward-facing conformation consistent with that previously seen in tubular crystals. After removal of Zn2+ with high-affinity chelators, YiiP exhibits enhanced flexibility and adopts a novel conformation that appears to be intermediate between inward-facing and outward-facing states. This conformation involves closure of a hydrophobic gate that has been postulated to control access to the primary transport site. Comparison of several independent cryo-EM maps suggests that the transition from the inward-facing state is controlled by occupancy of a secondary Zn2+ site at the cytoplasmic membrane interface. This work enhances our understanding of individual Zn2+ binding sites and their role in the conformational dynamics that govern the transport cycle.},
	number = {8},
	urldate = {2021-07-13},
	journal = {Journal of General Physiology},
	author = {Lopez-Redondo, Maria and Fan, Shujie and Koide, Akiko and Koide, Shohei and Beckstein, Oliver and Stokes, David L.},
	month = jul,
	year = {2021},
}

YiiP is a secondary transporter that couples Zn2+ transport to the proton motive force. Structural studies of YiiP from prokaryotes and Znt8 from humans have revealed three different Zn2+ sites and a conserved homodimeric architecture. These structures define the inward-facing and outward-facing states that characterize the archetypal alternating access mechanism of transport. To study the effects of Zn2+ binding on the conformational transition, we use cryo-EM together with molecular dynamics simulation to compare structures of YiiP from Shewanella oneidensis in the presence and absence of Zn2+. To enable single-particle cryo-EM, we used a phage-display library to develop a Fab antibody fragment with high affinity for YiiP, thus producing a YiiP/Fab complex. To perform MD simulations, we developed a nonbonded dummy model for Zn2+ and validated its performance with known Zn2+-binding proteins. Using these tools, we find that, in the presence of Zn2+, YiiP adopts an inward-facing conformation consistent with that previously seen in tubular crystals. After removal of Zn2+ with high-affinity chelators, YiiP exhibits enhanced flexibility and adopts a novel conformation that appears to be intermediate between inward-facing and outward-facing states. This conformation involves closure of a hydrophobic gate that has been postulated to control access to the primary transport site. Comparison of several independent cryo-EM maps suggests that the transition from the inward-facing state is controlled by occupancy of a secondary Zn2+ site at the cytoplasmic membrane interface. This work enhances our understanding of individual Zn2+ binding sites and their role in the conformational dynamics that govern the transport cycle.

@article{geiger_evidence_2021,
	title = {Evidence that specific interactions play a role in the cholesterol sensitivity of {G} protein-coupled receptors},
	volume = {1863},
	issn = {0005-2736},
	url = {http://www.sciencedirect.com/science/article/pii/S0005273621000080},
	doi = {10.1016/j.bbamem.2021.183557},
	abstract = {G protein-coupled receptors (GPCRs) are known to be modulated by membrane cholesterol levels, but whether or not the effects are caused by specific receptor-cholesterol interactions or cholesterol's general effects on the membrane is not well-understood. We performed coarse-grained molecular dynamics (CGMD) simulations coupled with structural bioinformatics approaches on the β2-adrenergic receptor (β2AR) and the cholecystokinin (CCK) receptor subfamily. The β2AR has been shown to be sensitive to membrane cholesterol and cholesterol molecules have been clearly resolved in numerous β2AR crystal structures. The two CCK receptors are highly homologous and preserve similar cholesterol recognition motifs but despite their homology, CCK1R shows functional sensitivity to membrane cholesterol while CCK2R does not. Our results offer new insights into how cholesterol modulates GPCR function by showing cholesterol interactions with β2AR that agree with previously published data; additionally, we observe differential and specific cholesterol binding in the CCK receptor subfamily while revealing a previously unreported Cholesterol Recognition Amino-acid Consensus (CRAC) sequence that is also conserved across 38\% of class A GPCRs. A thermal denaturation assay (LCP-Tm) shows that mutation of a conserved CRAC sequence on TM7 of the β2AR affects cholesterol stabilization of the receptor in a lipid bilayer. The results of this study provide a better understanding of receptor-cholesterol interactions that can contribute to novel and improved therapeutics for a variety of diseases.},
	language = {en},
	number = {9},
	urldate = {2021-01-12},
	journal = {Biochimica et Biophysica Acta (BBA) - Biomembranes},
	author = {Geiger, James and Sexton, Rick and Al-Sahouri, Zina and Lee, Ming-Yue and Chun, Eugene and Harikumar, Kaleeckal G. and Miller, Laurence J. and Beckstein, Oliver and Liu, Wei},
	month = sep,
	year = {2021},
	keywords = {Cholecystokinin (CCK) receptors, Cholesterol, Cholesterol recognition amino-acid consensus (CRAC), Course-grained molecular dynamics, G protein-coupled receptors},
	pages = {183557},
}

G protein-coupled receptors (GPCRs) are known to be modulated by membrane cholesterol levels, but whether or not the effects are caused by specific receptor-cholesterol interactions or cholesterol's general effects on the membrane is not well-understood. We performed coarse-grained molecular dynamics (CGMD) simulations coupled with structural bioinformatics approaches on the β2-adrenergic receptor (β2AR) and the cholecystokinin (CCK) receptor subfamily. The β2AR has been shown to be sensitive to membrane cholesterol and cholesterol molecules have been clearly resolved in numerous β2AR crystal structures. The two CCK receptors are highly homologous and preserve similar cholesterol recognition motifs but despite their homology, CCK1R shows functional sensitivity to membrane cholesterol while CCK2R does not. Our results offer new insights into how cholesterol modulates GPCR function by showing cholesterol interactions with β2AR that agree with previously published data; additionally, we observe differential and specific cholesterol binding in the CCK receptor subfamily while revealing a previously unreported Cholesterol Recognition Amino-acid Consensus (CRAC) sequence that is also conserved across 38% of class A GPCRs. A thermal denaturation assay (LCP-Tm) shows that mutation of a conserved CRAC sequence on TM7 of the β2AR affects cholesterol stabilization of the receptor in a lipid bilayer. The results of this study provide a better understanding of receptor-cholesterol interactions that can contribute to novel and improved therapeutics for a variety of diseases.

@article{winkelmann_structure_2020,
	title = {Structure and elevator mechanism of the mammalian sodium/proton exchanger {NHE9}},
	volume = {39},
	issn = {0261-4189},
	url = {https://www.embopress.org/doi/full/10.15252/embj.2020105908},
	doi = {10.15252/embj.2020105908},
	abstract = {Abstract Na+/H+ exchangers (NHEs) are ancient membrane-bound nanomachines that work to regulate intracellular pH, sodium levels and cell volume. NHE activities contribute to the control of the cell cycle, cell proliferation, cell migration and vesicle trafficking. NHE dysfunction has been linked to many diseases, and they are targets of pharmaceutical drugs. Despite their fundamental importance to cell homeostasis and human physiology, structural information for the mammalian NHEs was lacking. Here, we report the cryogenic electron microscopy structure of NHE isoform 9 (SLC9A9) from Equus caballus at 3.2 Å resolution, an endosomal isoform highly expressed in the brain and associated with autism spectrum (ASD) and attention deficit hyperactivity (ADHD) disorders. Despite low sequence identity, the NHE9 architecture and ion-binding site are remarkably most similar to distantly related bacterial Na+/H+ antiporters with 13 transmembrane segments. Collectively, we reveal the conserved architecture of the NHE ion-binding site, their elevator-like structural transitions, the functional implications of autism disease mutations and the role of phosphoinositide lipids to promote homodimerization that, together, have important physiological ramifications.},
	number = {24},
	urldate = {2020-10-29},
	journal = {The EMBO Journal},
	author = {Winkelmann, Iven and Matsuoka, Rei and Meier, Pascal F and Shutin, Denis and Zhang, Chenou and Orellana, Laura and Sexton, Ricky and Landreh, Michael and Robinson, Carol V and Beckstein, Oliver and Drew, David},
	month = dec,
	year = {2020},
	note = {Publisher: John Wiley \& Sons, Ltd},
	keywords = {SLCA9, membrane protein, pH regulation, sodium/proton exchanger, structure},
	pages = {e105908},
}

Abstract Na+/H+ exchangers (NHEs) are ancient membrane-bound nanomachines that work to regulate intracellular pH, sodium levels and cell volume. NHE activities contribute to the control of the cell cycle, cell proliferation, cell migration and vesicle trafficking. NHE dysfunction has been linked to many diseases, and they are targets of pharmaceutical drugs. Despite their fundamental importance to cell homeostasis and human physiology, structural information for the mammalian NHEs was lacking. Here, we report the cryogenic electron microscopy structure of NHE isoform 9 (SLC9A9) from Equus caballus at 3.2 Å resolution, an endosomal isoform highly expressed in the brain and associated with autism spectrum (ASD) and attention deficit hyperactivity (ADHD) disorders. Despite low sequence identity, the NHE9 architecture and ion-binding site are remarkably most similar to distantly related bacterial Na+/H+ antiporters with 13 transmembrane segments. Collectively, we reveal the conserved architecture of the NHE ion-binding site, their elevator-like structural transitions, the functional implications of autism disease mutations and the role of phosphoinositide lipids to promote homodimerization that, together, have important physiological ramifications.

@article{khoshlessan_parallel_2020,
	title = {Parallel performance of molecular dynamics trajectory analysis},
	volume = {32},
	issn = {1532-0626, 1532-0634},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.5789},
	doi = {10.1002/cpe.5789},
	abstract = {The performance of biomolecular molecular dynamics simulations has steadily increased on modern high-performance computing resources but acceleration of the analysis of the output trajectories has lagged behind so that analyzing simulations is becoming a bottleneck. To close this gap, we studied the performance of trajectory analysis with message passing interface (MPI) parallelization and the Python MDAnalysis library on three different Extreme Science and Engineering Discovery Environment (XSEDE) supercomputers where trajectories were read from a Lustre parallel file system. Strong scaling performance was impeded by stragglers, MPI processes that were slower than the typical process. Stragglers were less prevalent for compute-bound workloads, thus pointing to file reading as a bottleneck for scaling. However, a more complicated picture emerged in which both the computation and the data ingestion exhibited close to ideal strong scaling behavior whereas stragglers were primarily caused by either large MPI communication costs or long times to open the single shared trajectory file. We improved overall strong scaling performance by either subfiling (splitting the trajectory into separate files) or MPI-IO with parallel HDF5 trajectory files. The parallel HDF5 approach resulted in near ideal strong scaling on up to 384 cores (16 nodes), thus reducing trajectory analysis times by two orders of magnitude compared with the serial approach.},
	language = {en},
	urldate = {2020-04-28},
	journal = {Concurrency and Computation: Practice and Experience},
	author = {Khoshlessan, Mahzad and Paraskevakos, Ioannis and Fox, Geoffrey C. and Jha, Shantenu and Beckstein, Oliver},
	month = apr,
	year = {2020},
	pages = {e5789},
}

The performance of biomolecular molecular dynamics simulations has steadily increased on modern high-performance computing resources but acceleration of the analysis of the output trajectories has lagged behind so that analyzing simulations is becoming a bottleneck. To close this gap, we studied the performance of trajectory analysis with message passing interface (MPI) parallelization and the Python MDAnalysis library on three different Extreme Science and Engineering Discovery Environment (XSEDE) supercomputers where trajectories were read from a Lustre parallel file system. Strong scaling performance was impeded by stragglers, MPI processes that were slower than the typical process. Stragglers were less prevalent for compute-bound workloads, thus pointing to file reading as a bottleneck for scaling. However, a more complicated picture emerged in which both the computation and the data ingestion exhibited close to ideal strong scaling behavior whereas stragglers were primarily caused by either large MPI communication costs or long times to open the single shared trajectory file. We improved overall strong scaling performance by either subfiling (splitting the trajectory into separate files) or MPI-IO with parallel HDF5 trajectory files. The parallel HDF5 approach resulted in near ideal strong scaling on up to 384 cores (16 nodes), thus reducing trajectory analysis times by two orders of magnitude compared with the serial approach.

@article{henderson_alternative_2020,
	title = {Alternative proton-binding site and long-distance coupling in {Escherichia} coli sodium–proton antiporter {NhaA}},
	copyright = {© 2020 . https://www-pnas-org.ezproxy1.lib.asu.edu/site/aboutpnas/licenses.xhtmlPublished under the PNAS license.},
	issn = {0027-8424, 1091-6490},
	url = {https://www.pnas.org/content/early/2020/09/23/2005467117},
	doi = {10.1073/pnas.2005467117},
	abstract = {Escherichia coli NhaA is a prototypical sodium–proton antiporter responsible for maintaining cellular ion and volume homeostasis by exchanging two protons for one sodium ion; despite two decades of research, the transport mechanism of NhaA remains poorly understood. Recent crystal structure and computational studies suggested Lys300 as a second proton-binding site; however, functional measurements of several K300 mutants demonstrated electrogenic transport, thereby casting doubt on the role of Lys300. To address the controversy, we carried out state-of-the-art continuous constant pH molecular dynamics simulations of NhaA mutants K300A, K300R, K300Q/D163N, and K300Q/D163N/D133A. Simulations suggested that K300 mutants maintain the electrogenic transport by utilizing an alternative proton-binding residue Asp133. Surprisingly, while Asp133 is solely responsible for binding the second proton in K300R, Asp133 and Asp163 jointly bind the second proton in K300A, and Asp133 and Asp164 jointly bind two protons in K300Q/D163N. Intriguingly, the coupling between Asp133 and Asp163 or Asp164 is enabled through the proton-coupled hydrogen-bonding network at the flexible intersection of two disrupted helices. These data resolve the controversy and highlight the intricacy of the compensatory transport mechanism of NhaA mutants. Alternative proton-binding site and proton sharing between distant aspartates may represent important general mechanisms of proton-coupled transport in secondary active transporters.},
	language = {en},
	urldate = {2020-09-24},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Henderson, Jack A. and Huang, Yandong and Beckstein, Oliver and Shen, Jana},
	month = sep,
	year = {2020},
	note = {Publisher: National Academy of Sciences
Section: Biological Sciences},
	keywords = {cation–proton antiporters, molecular dynamics, protein electrostatics, proton transport, secondary active transporters},
}

Escherichia coli NhaA is a prototypical sodium–proton antiporter responsible for maintaining cellular ion and volume homeostasis by exchanging two protons for one sodium ion; despite two decades of research, the transport mechanism of NhaA remains poorly understood. Recent crystal structure and computational studies suggested Lys300 as a second proton-binding site; however, functional measurements of several K300 mutants demonstrated electrogenic transport, thereby casting doubt on the role of Lys300. To address the controversy, we carried out state-of-the-art continuous constant pH molecular dynamics simulations of NhaA mutants K300A, K300R, K300Q/D163N, and K300Q/D163N/D133A. Simulations suggested that K300 mutants maintain the electrogenic transport by utilizing an alternative proton-binding residue Asp133. Surprisingly, while Asp133 is solely responsible for binding the second proton in K300R, Asp133 and Asp163 jointly bind the second proton in K300A, and Asp133 and Asp164 jointly bind two protons in K300Q/D163N. Intriguingly, the coupling between Asp133 and Asp163 or Asp164 is enabled through the proton-coupled hydrogen-bonding network at the flexible intersection of two disrupted helices. These data resolve the controversy and highlight the intricacy of the compensatory transport mechanism of NhaA mutants. Alternative proton-binding site and proton sharing between distant aspartates may represent important general mechanisms of proton-coupled transport in secondary active transporters.

@article{candanedo_dynamics_2020,
	title = {Dynamics of rare gas solids irradiated by electron beams},
	volume = {152},
	issn = {0021-9606},
	url = {https://aip.scitation.org/doi/10.1063/1.5134801},
	doi = {10.1063/1.5134801},
	abstract = {The remarkable success of x-ray free-electron lasers and their ability to image biological macromolecules while outrunning secondary radiation damage due to photoelectrons, by using femtosecond pulses, raise the question of whether this can be done using pulsed high-energy electron beams. In this paper, we use excited state molecular dynamics simulations, with tabulated potentials, for rare gas solids to investigate the effect of radiation damage due to inelastic scattering (by plasmons, excitons, and heat) on the pair distribution function. We use electron energy loss spectra to characterize the electronic excitations responsible for radiation damage.},
	number = {14},
	urldate = {2020-04-10},
	journal = {The Journal of Chemical Physics},
	author = {Candanedo, J. and Caleman, C. and Tîmneanu, N. and Beckstein, O. and Spence, J. C. H.},
	month = apr,
	year = {2020},
	note = {Publisher: American Institute of Physics},
	pages = {144303},
}

The remarkable success of x-ray free-electron lasers and their ability to image biological macromolecules while outrunning secondary radiation damage due to photoelectrons, by using femtosecond pulses, raise the question of whether this can be done using pulsed high-energy electron beams. In this paper, we use excited state molecular dynamics simulations, with tabulated potentials, for rare gas solids to investigate the effect of radiation damage due to inelastic scattering (by plasmons, excitons, and heat) on the pair distribution function. We use electron energy loss spectra to characterize the electronic excitations responsible for radiation damage.

@article{fan_prediction_2020,
	title = {Prediction of octanol-water partition coefficients for the {SAMPL6}-log {P} molecules using molecular dynamics simulations with {OPLS}-{AA}, {AMBER} and {CHARMM} force fields},
	issn = {1573-4951},
	url = {https://doi.org/10.1007/s10822-019-00267-z},
	doi = {10.1007/s10822-019-00267-z},
	abstract = {All-atom molecular dynamics simulations with stratified alchemical free energy calculations were used to predict the octanol-water partition coefficient \$\${\textbackslash}log P\_\{ow\}\$\$logPow of eleven small molecules as part of the SAMPL6-\$\${\textbackslash}log P\$\$logP blind prediction challenge using four different force field parametrizations: standard OPLS-AA with transferable charges, OPLS-AA with non-transferable CM1A charges, AMBER/GAFF, and CHARMM/CGenFF. Octanol parameters for OPLS-AA, GAFF and CHARMM were validated by comparing the density as a function of temperature, the chemical potential, and the hydration free energy to experimental values. The partition coefficients were calculated from the solvation free energy for the compounds in water and pure (“dry”) octanol or “wet” octanol with 27 mol\% water dissolved. Absolute solvation free energies were computed by thermodynamic integration (TI) and the multistate Bennett acceptance ratio with uncorrelated samples from data generated by an established protocol using 5-ns windowed alchemical free energy perturbation (FEP) calculations with the Gromacs molecular dynamics package. Equilibration of sets of FEP simulations was quantified by a new measure of convergence based on the analysis of forward and time-reversed trajectories. The accuracy of the \$\${\textbackslash}log P\_\{ow\}\$\$logPow predictions was assessed by descriptive statistical measures such as the root mean square error (RMSE) of the data set compared to the experimental values. Discarding the first 1 ns of each 5-ns window as an equilibration phase had a large effect on the GAFF data, where it improved the RMSE by up to 0.8 log units, while the effect for other data sets was smaller or marginally worsened the agreement. Overall, CGenFF gave the best prediction with RMSE 1.2 log units, although for only eight molecules because the current CGenFF workflow for Gromacs does not generate files for certain halogen-containing compounds. Over all eleven compounds, GAFF gave an RMSE of 1.5. The effect of using a mixed water/octanol solvent slightly decreased the accuracy for CGenFF and GAFF and slightly increased it for OPLS-AA. The GAFF and OPLS-AA results displayed a systematic error where molecules were too hydrophobic whereas CGenFF appeared to be more balanced, at least on this small data set.},
	language = {en},
	urldate = {2020-01-21},
	journal = {Journal of Computer-Aided Molecular Design},
	author = {Fan, Shujie and Iorga, Bogdan I. and Beckstein, Oliver},
	month = jan,
	year = {2020},
}

All-atom molecular dynamics simulations with stratified alchemical free energy calculations were used to predict the octanol-water partition coefficient $$\log P_\ow\$$logPow of eleven small molecules as part of the SAMPL6-$$ \log P $$logP blind prediction challenge using four different force field parametrizations: standard OPLS-AA with transferable charges, OPLS-AA with non-transferable CM1A charges, AMBER/GAFF, and CHARMM/CGenFF. Octanol parameters for OPLS-AA, GAFF and CHARMM were validated by comparing the density as a function of temperature, the chemical potential, and the hydration free energy to experimental values. The partition coefficients were calculated from the solvation free energy for the compounds in water and pure (“dry”) octanol or “wet” octanol with 27 mol% water dissolved. Absolute solvation free energies were computed by thermodynamic integration (TI) and the multistate Bennett acceptance ratio with uncorrelated samples from data generated by an established protocol using 5-ns windowed alchemical free energy perturbation (FEP) calculations with the Gromacs molecular dynamics package. Equilibration of sets of FEP simulations was quantified by a new measure of convergence based on the analysis of forward and time-reversed trajectories. The accuracy of the$$ \log P_\ow\$$logPow predictions was assessed by descriptive statistical measures such as the root mean square error (RMSE) of the data set compared to the experimental values. Discarding the first 1 ns of each 5-ns window as an equilibration phase had a large effect on the GAFF data, where it improved the RMSE by up to 0.8 log units, while the effect for other data sets was smaller or marginally worsened the agreement. Overall, CGenFF gave the best prediction with RMSE 1.2 log units, although for only eight molecules because the current CGenFF workflow for Gromacs does not generate files for certain halogen-containing compounds. Over all eleven compounds, GAFF gave an RMSE of 1.5. The effect of using a mixed water/octanol solvent slightly decreased the accuracy for CGenFF and GAFF and slightly increased it for OPLS-AA. The GAFF and OPLS-AA results displayed a systematic error where molecules were too hydrophobic whereas CGenFF appeared to be more balanced, at least on this small data set.

@article{dabos_substrate_2020,
	title = {Substrate specificity of {OXA}-48 after β5-β6 loop replacement.},
	copyright = {Copyright © 2020 American Chemical Society},
	url = {https://pubs.acs.org/doi/pdf/10.1021/acsinfecdis.9b00452},
	doi = {10.1021/acsinfecdis.9b00452},
	abstract = {OXA-48 carbapenemase has rapidly spread in many countries worldwide with several OXA-48-variants being described, differing by a few amino acid (AA) substitutions or deletions, mostly in the β5-β6 loop. While single AA substitutions have only minor impact on OXA-48 hydrolytic profiles, others with 4 AA deletions result in loss of carbapenem hydrolysis and gain of expanded-spectrum cephalosporin (ESC) hydrolysis. We have replaced the β5-β6 loop of OXA-48 with that of OXA-18, a clavulanic-acid inhibited oxacillinase capable of hydrolyzing ESCs but not carbapenems. The hybrid enzyme OXA-48Loop18 was able to hydrolyze ESCs and carbapenems (although with a lower kcat), even though the β5-β6 loop was longer and its sequence quite different from that of OXA-48. The kinetic parameters of OXA-48Loop18 were in agreement with the MIC values. X-ray crystallography and molecular modeling suggest that the confor-mation of the grafted loop allows the binding of bulkier substrates, unlike that of the native loop, expanding the hydrolytic profile. This seems to be due not only to differences in AA sequence, but also to the backbone conformation the loop can adopt. Finally, our results provide further experimental evidence for the role of the β5-β6 loop in substrate selectivity of OXA-48-like enzymes and additional de-tails on the structure-function relationship of β-lactamases, demonstrating how localized changes in these proteins can alter or expand their function, highlighting their plasticity.},
	language = {en},
	urldate = {2020-03-18},
	journal = {ACS Infectious Diseases},
	author = {Dabos, Laura and Zavala, Agustin and Bonnin, Rémy A. and Beckstein, Oliver and Retailleau, Pascal and Iorga, Bogdan I. and NAAS, Thierry},
	month = mar,
	year = {2020},
	note = {Publisher: American Chemical Society},
}

OXA-48 carbapenemase has rapidly spread in many countries worldwide with several OXA-48-variants being described, differing by a few amino acid (AA) substitutions or deletions, mostly in the β5-β6 loop. While single AA substitutions have only minor impact on OXA-48 hydrolytic profiles, others with 4 AA deletions result in loss of carbapenem hydrolysis and gain of expanded-spectrum cephalosporin (ESC) hydrolysis. We have replaced the β5-β6 loop of OXA-48 with that of OXA-18, a clavulanic-acid inhibited oxacillinase capable of hydrolyzing ESCs but not carbapenems. The hybrid enzyme OXA-48Loop18 was able to hydrolyze ESCs and carbapenems (although with a lower kcat), even though the β5-β6 loop was longer and its sequence quite different from that of OXA-48. The kinetic parameters of OXA-48Loop18 were in agreement with the MIC values. X-ray crystallography and molecular modeling suggest that the confor-mation of the grafted loop allows the binding of bulkier substrates, unlike that of the native loop, expanding the hydrolytic profile. This seems to be due not only to differences in AA sequence, but also to the backbone conformation the loop can adopt. Finally, our results provide further experimental evidence for the role of the β5-β6 loop in substrate selectivity of OXA-48-like enzymes and additional de-tails on the structure-function relationship of β-lactamases, demonstrating how localized changes in these proteins can alter or expand their function, highlighting their plasticity.

@incollection{fox_contributions_2019,
	series = {Advances in {Parallel} {Computing}},
	title = {Contributions to high-performance big data computing},
	volume = {34},
	url = {https://doi.org/10.3233/APC190005},
	abstract = {Our project is at the interface of Big Data and HPC – High-Performance Big Data computing and this paper describes a collaboration between 7 collaborating Universities at Arizona State, Indiana (lead), Kansas, Rutgers, Stony Brook, Virginia Tech, and Utah. It addresses the intersection of High-performance and Big Data computing with several different application areas or communities driving the requirements for software systems and algorithms. We describe the base architecture, including the HPC-ABDS, High-Performance Computing enhanced Apache Big Data Stack, and an application use case study identifying key features that determine software and algorithm requirements. We summarize middleware including Harp-DAAL collective communication layer, Twister2 Big Data toolkit, and pilot jobs. Then we present the SPIDAL Scalable Parallel Interoperable Data Analytics Library and our work for it in core machine-learning, image processing and the application communities, Network science, Polar Science, Biomolecular Simulations, Pathology, and Spatial systems. We describe basic algorithms and their integration in end-to-end use cases.},
	booktitle = {Future {Trends} of {HPC} in a {Disruptive} {Scenario}},
	publisher = {IOS Press},
	author = {Fox, Geoffrey and Qiu, Judy and Crandall, David and von Laszewski, Gregor and Beckstein, Oliver and Paden, John and Paraskevakos, Ioannis and Jha, Shantenu and Wang, Fusheng and Marathe, Madhav and Vullikanti, Anil and Cheatham III, Thomas E.},
	editor = {Grandinetti, Lucio and Joubert, Gerhard R. and Michielsen, Kristel and Mirtaheri, Seyedeh Leili and Taufer, Michela and Yokota, Rio},
	year = {2019},
	pages = {34--81},
}

Our project is at the interface of Big Data and HPC – High-Performance Big Data computing and this paper describes a collaboration between 7 collaborating Universities at Arizona State, Indiana (lead), Kansas, Rutgers, Stony Brook, Virginia Tech, and Utah. It addresses the intersection of High-performance and Big Data computing with several different application areas or communities driving the requirements for software systems and algorithms. We describe the base architecture, including the HPC-ABDS, High-Performance Computing enhanced Apache Big Data Stack, and an application use case study identifying key features that determine software and algorithm requirements. We summarize middleware including Harp-DAAL collective communication layer, Twister2 Big Data toolkit, and pilot jobs. Then we present the SPIDAL Scalable Parallel Interoperable Data Analytics Library and our work for it in core machine-learning, image processing and the application communities, Network science, Polar Science, Biomolecular Simulations, Pathology, and Spatial systems. We describe basic algorithms and their integration in end-to-end use cases.

@inproceedings{fox_learning_2019,
	title = {Learning {Everywhere}: {Pervasive} {Machine} {Learning} for {Effective} {High}-{Performance} {Computation}},
	shorttitle = {Learning {Everywhere}},
	doi = {10.1109/IPDPSW.2019.00081},
	abstract = {The convergence of HPC and data intensive methodologies provide a promising approach to major performance improvements. This paper provides a general description of the interaction between traditional HPC and ML approaches and motivates the "Learning Everywhere" paradigm for HPC. We introduce the concept of "effective performance" that one can achieve by combining learning methodologies with simulation based approaches, and distinguish between traditional performance as measured by benchmark scores. To support the promise of integrating HPC and learning methods, this paper examines specific examples and opportunities across a series of domains. It concludes with a series of open software systems, methods and infrastructure challenges that the Learning Everywhere paradigm presents.},
	booktitle = {2019 {IEEE} {International} {Parallel} and {Distributed} {Processing} {Symposium} {Workshops} ({IPDPSW})},
	author = {Fox, Geoffrey and Glazier, James A. and Kadupitiya, J.C.S. and Jadhao, Vikram and Kim, Minje and Qiu, Judy and Sluka, James P. and Somogyi, Endre and Marathe, Madhav and Adiga, Abhijin and Chen, Jiangzhuo and Beckstein, Oliver and Jha, Shantenu},
	month = may,
	year = {2019},
	note = {ISSN: null},
	keywords = {Biological system modeling, Computational modeling, Data models, Effective Performance, Forecasting, ML approaches, Machine learning, Machine learning driven HPC, Mathematical model, Predictive models, data intensive methodologies, general description, high-performance computation, learning (artificial intelligence), learning everywhere paradigm, learning methodologies, learning methods, open software systems, parallel processing, performance improvements, pervasive machine learning, simulation based approaches, traditional HPC, traditional performance, ubiquitous computing},
	pages = {422--429},
}

The convergence of HPC and data intensive methodologies provide a promising approach to major performance improvements. This paper provides a general description of the interaction between traditional HPC and ML approaches and motivates the "Learning Everywhere" paradigm for HPC. We introduce the concept of "effective performance" that one can achieve by combining learning methodologies with simulation based approaches, and distinguish between traditional performance as measured by benchmark scores. To support the promise of integrating HPC and learning methods, this paper examines specific examples and opportunities across a series of domains. It concludes with a series of open software systems, methods and infrastructure challenges that the Learning Everywhere paradigm presents.

@article{beckstein_general_2019,
	title = {General {Principles} of {Secondary} {Active} {Transporter} {Function}},
	url = {http://arxiv.org/abs/1912.06275},
	abstract = {Transport of ions and small molecules across the cell membrane against electrochemical gradients is catalyzed by integral membrane proteins that use a source of free energy to drive the energetically uphill flux of the transported substrate. Secondary active transporters couple the spontaneous influx of a "driving" ion such as Na+ or H+ to the flux of the substrate. The thermodynamics of such cyclical non-equilibrium systems are well understood and recent work has focused on the molecular mechanism of secondary active transport. The fact that these transporters change their conformation between an inward-facing and outward-facing conformation in a cyclical fashion, called the alternating access model, is broadly recognized as the molecular framework in which to describe transporter function. However, only with the advent of high resolution crystal structures and detailed computer simulations has it become possible to recognize common molecular-level principles between disparate transporter families. Inverted repeat symmetry in secondary active transporters has shed light on how protein structures can encode a bi-stable two-state system. More detailed analysis (based on experimental structural data and detailed molecular dynamics simulations) indicates that transporters can be understood as gated pores with at least two coupled gates. These gates are not just a convenient cartoon element to illustrate a putative mechanism but map to distinct parts of the transporter protein. Enumerating all distinct gate states naturally includes occluded states in the alternating access picture and also suggests what kind of protein conformations might be observable. By connecting the possible conformational states and ion/substrate bound states in a kinetic model, a unified picture emerges in which symporter, antiporter, and uniporter function are extremes in a continuum of functionality.},
	urldate = {2019-12-16},
	journal = {arXiv:1912.06275 [q-bio]},
	author = {Beckstein, Oliver and Naughton, Fiona},
	month = dec,
	year = {2019},
	note = {arXiv: 1912.06275},
	keywords = {Quantitative Biology - Biomolecules},
}

Transport of ions and small molecules across the cell membrane against electrochemical gradients is catalyzed by integral membrane proteins that use a source of free energy to drive the energetically uphill flux of the transported substrate. Secondary active transporters couple the spontaneous influx of a "driving" ion such as Na+ or H+ to the flux of the substrate. The thermodynamics of such cyclical non-equilibrium systems are well understood and recent work has focused on the molecular mechanism of secondary active transport. The fact that these transporters change their conformation between an inward-facing and outward-facing conformation in a cyclical fashion, called the alternating access model, is broadly recognized as the molecular framework in which to describe transporter function. However, only with the advent of high resolution crystal structures and detailed computer simulations has it become possible to recognize common molecular-level principles between disparate transporter families. Inverted repeat symmetry in secondary active transporters has shed light on how protein structures can encode a bi-stable two-state system. More detailed analysis (based on experimental structural data and detailed molecular dynamics simulations) indicates that transporters can be understood as gated pores with at least two coupled gates. These gates are not just a convenient cartoon element to illustrate a putative mechanism but map to distinct parts of the transporter protein. Enumerating all distinct gate states naturally includes occluded states in the alternating access picture and also suggests what kind of protein conformations might be observable. By connecting the possible conformational states and ion/substrate bound states in a kinetic model, a unified picture emerges in which symporter, antiporter, and uniporter function are extremes in a continuum of functionality.

@inproceedings{fan_pmda_2019,
	address = {Austin, TX},
	title = {{PMDA} - {Parallel} {Molecular} {Dynamics} {Analysis}},
	url = {https://conference.scipy.org/proceedings/scipy2019/shujie_fan.html},
	doi = {10.25080/Majora-7ddc1dd1-013},
	abstract = {MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats. With the development of highly optimized MD software packages on high performance computing (HPC) resources, the size of simulation trajectories is growing up to many terabytes in size. However efficient usage of multicore architecture is a challenge for MDAnalysis, which does not yet provide a standard interface for parallel analysis. To address the challenge, we developed PMDA, a Python library that builds upon MDAnalysis to provide parallel analysis algorithms. PMDA parallelizes common analysis algorithms in MDAnalysis through a task-based approach with the Dask library. We implement a simple split-apply-combine scheme for parallel trajectory analysis. The trajectory is split into blocks, analysis is performed separately and in parallel on each block ({\textbackslash}textquotedbl\{\}apply{\textbackslash}textquotedbl\{\}), then results from each block are gathered and combined. PMDA allows one to perform parallel trajectory analysis with pre-defined analysis tasks. In addition, it provides a common interface that makes it easy to create user-defined parallel analysis modules. PMDA supports all schedulers in Dask, and one can run analysis in a distributed fashion on HPC machines, ad-hoc clusters, a single multi-core workstation or a laptop. We tested the performance of PMDA on single node and multiple nodes on a national supercomputer. The results show that parallelization improves the performance of trajectory analysis and, depending on the analysis task, can cut down time to solution from hours to minutes. Although still in alpha stage, it is already used on resources ranging from multi-core laptops to XSEDE supercomputers to speed up analysis of molecular dynamics trajectories. PMDA is available as open source under the GNU General Public License, version 2 and can be easily installed via the pip and conda package managers.},
	booktitle = {Proceedings of the 18th {Python} in {Science} {Conference}},
	author = {Fan, Shujie and Linke, Max and Paraskevakos, Ioannis and Gowers, Richard J. and Gecht, Michael and Beckstein, Oliver},
	editor = {Calloway, Chris and Lippa, David and Niederhut, Dillon and Shupe, David},
	year = {2019},
	pages = {134 -- 142},
}

MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats. With the development of highly optimized MD software packages on high performance computing (HPC) resources, the size of simulation trajectories is growing up to many terabytes in size. However efficient usage of multicore architecture is a challenge for MDAnalysis, which does not yet provide a standard interface for parallel analysis. To address the challenge, we developed PMDA, a Python library that builds upon MDAnalysis to provide parallel analysis algorithms. PMDA parallelizes common analysis algorithms in MDAnalysis through a task-based approach with the Dask library. We implement a simple split-apply-combine scheme for parallel trajectory analysis. The trajectory is split into blocks, analysis is performed separately and in parallel on each block (\textquotedbl\\apply\textquotedbl\\), then results from each block are gathered and combined. PMDA allows one to perform parallel trajectory analysis with pre-defined analysis tasks. In addition, it provides a common interface that makes it easy to create user-defined parallel analysis modules. PMDA supports all schedulers in Dask, and one can run analysis in a distributed fashion on HPC machines, ad-hoc clusters, a single multi-core workstation or a laptop. We tested the performance of PMDA on single node and multiple nodes on a national supercomputer. The results show that parallelization improves the performance of trajectory analysis and, depending on the analysis task, can cut down time to solution from hours to minutes. Although still in alpha stage, it is already used on resources ranging from multi-core laptops to XSEDE supercomputers to speed up analysis of molecular dynamics trajectories. PMDA is available as open source under the GNU General Public License, version 2 and can be easily installed via the pip and conda package managers.

@inproceedings{beckstein_convergence_2018,
	title = {Convergence of data generation and analysis in the biomolecular simulation community},
	url = {https://www.exascale.org/bdec/sites/www.exascale.org.bdec/files/whitepapers/Beckstein-Fox-Jha_BDEC2_WP_0.pdf},
	language = {en},
	booktitle = {Online {Resource} for {Big} {Data} and {Extreme}-{Scale} {Computing} {Workshop}},
	author = {Beckstein, Oliver and Fox, Geoffrey and Jha, Shantenu},
	month = nov,
	year = {2018},
	pages = {4},
}

@inproceedings{paraskevakos_task-parallel_2018,
	address = {New York, NY, USA},
	series = {{ICPP} 2018},
	title = {Task-parallel {Analysis} of {Molecular} {Dynamics} {Trajectories}},
	isbn = {978-1-4503-6510-9},
	url = {http://doi.acm.org/10.1145/3225058.3225128},
	doi = {10.1145/3225058.3225128},
	abstract = {Different parallel frameworks for implementing data analysis applications have been proposed by the HPC and Big Data communities. In this paper, we investigate three task-parallel frameworks: Spark, Dask and RADICAL-Pilot with respect to their ability to support data analytics on HPC resources and compare them to MPI. We investigate the data analysis requirements of Molecular Dynamics (MD) simulations which are significant consumers of supercomputing cycles, producing immense amounts of data. A typical large-scale MD simulation of a physical system of O(100k) atoms over μsecs can produce from O(10) GB to O(1000) GBs of data. We propose and evaluate different approaches for parallelization of a representative set of MD trajectory analysis algorithms, in particular the computation of path similarity and leaflet identification. We evaluate Spark, Dask and RADICAL-Pilot with respect to their abstractions and runtime engine capabilities to support these algorithms. We provide a conceptual basis for comparing and understanding different frameworks that enable users to select the optimal system for each application. We also provide a quantitative performance analysis of the different algorithms across the three frameworks.},
	urldate = {2019-01-28},
	booktitle = {Proceedings of the 47th {International} {Conference} on {Parallel} {Processing}},
	publisher = {ACM},
	author = {Paraskevakos, Ioannis and Luckow, Andre and Khoshlessan, Mahzad and Chantzialexiou, George and Cheatham, Thomas E. and Beckstein, Oliver and Fox, Geoffrey C. and Jha, Shantenu},
	year = {2018},
	keywords = {Data analytics, MD Simulations Analysis, MD analysis, task-parallel},
	pages = {49:1--49:10},
}

Different parallel frameworks for implementing data analysis applications have been proposed by the HPC and Big Data communities. In this paper, we investigate three task-parallel frameworks: Spark, Dask and RADICAL-Pilot with respect to their ability to support data analytics on HPC resources and compare them to MPI. We investigate the data analysis requirements of Molecular Dynamics (MD) simulations which are significant consumers of supercomputing cycles, producing immense amounts of data. A typical large-scale MD simulation of a physical system of O(100k) atoms over μsecs can produce from O(10) GB to O(1000) GBs of data. We propose and evaluate different approaches for parallelization of a representative set of MD trajectory analysis algorithms, in particular the computation of path similarity and leaflet identification. We evaluate Spark, Dask and RADICAL-Pilot with respect to their abstractions and runtime engine capabilities to support these algorithms. We provide a conceptual basis for comparing and understanding different frameworks that enable users to select the optimal system for each application. We also provide a quantitative performance analysis of the different algorithms across the three frameworks.

@article{selwa_sampl6:_2018,
	title = {{SAMPL6}: calculation of macroscopic {pKa} values from ab initio quantum mechanical free energies},
	volume = {32},
	issn = {0920-654X, 1573-4951},
	shorttitle = {{SAMPL6}},
	url = {http://link.springer.com/article/10.1007/s10822-018-0138-6},
	doi = {10.1007/s10822-018-0138-6},
	abstract = {Macroscopic pKa values were calculated for all compounds in the SAMPL6 blind prediction challenge, based on quantum chemical calculations with a continuum solvation model and a linear correction derived from a small training set. Microscopic pKa values were derived from the gas-phase free energy difference between protonated and deprotonated forms together with the Conductor-like Polarizable Continuum Solvation Model and the experimental solvation free energy of the proton. pH-dependent microstate free energies were obtained from the microscopic pKas with a maximum likelihood estimator and appropriately summed to yield macroscopic pKa values or microstate populations as function of pH. We assessed the accuracy of three approaches to calculate the microscopic pKas: direct use of the quantum mechanical free energy differences and correction of the direct values for short-comings in the QM solvation model with two different linear models that we independently derived from a small training set of 38 compounds with known pKa. The predictions that were corrected with the linear models had much better accuracy [root-mean-square error (RMSE) 2.04 and 1.95 pKa units] than the direct calculation (RMSE 3.74). Statistical measures indicate that some systematic errors remain, likely due to differences in the SAMPL6 data set and the small training set with respect to their interactions with water. Overall, the current approach provides a viable physics-based route to estimate macroscopic pKa values for novel compounds with reasonable accuracy.},
	language = {en},
	number = {10},
	urldate = {2018-08-16},
	journal = {Journal of Computer-Aided Molecular Design},
	author = {Selwa, Edithe and Kenney, Ian M. and Beckstein, Oliver and Iorga, Bogdan I.},
	month = aug,
	year = {2018},
	pages = {1203--1216},
}

Macroscopic pKa values were calculated for all compounds in the SAMPL6 blind prediction challenge, based on quantum chemical calculations with a continuum solvation model and a linear correction derived from a small training set. Microscopic pKa values were derived from the gas-phase free energy difference between protonated and deprotonated forms together with the Conductor-like Polarizable Continuum Solvation Model and the experimental solvation free energy of the proton. pH-dependent microstate free energies were obtained from the microscopic pKas with a maximum likelihood estimator and appropriately summed to yield macroscopic pKa values or microstate populations as function of pH. We assessed the accuracy of three approaches to calculate the microscopic pKas: direct use of the quantum mechanical free energy differences and correction of the direct values for short-comings in the QM solvation model with two different linear models that we independently derived from a small training set of 38 compounds with known pKa. The predictions that were corrected with the linear models had much better accuracy [root-mean-square error (RMSE) 2.04 and 1.95 pKa units] than the direct calculation (RMSE 3.74). Statistical measures indicate that some systematic errors remain, likely due to differences in the SAMPL6 data set and the small training set with respect to their interactions with water. Overall, the current approach provides a viable physics-based route to estimate macroscopic pKa values for novel compounds with reasonable accuracy.

@article{calabrese_topological_2017,
	title = {Topological {Dissection} of the {Membrane} {Transport} {Protein} {Mhp1} {Derived} from {Cysteine} {Accessibility} and {Mass} {Spectrometry}},
	volume = {89},
	issn = {0003-2700},
	url = {http://dx.doi.org/10.1021/acs.analchem.7b01310},
	doi = {10.1021/acs.analchem.7b01310},
	abstract = {Cys accessibility and quantitative intact mass spectrometry (MS) analyses have been devised to study the topological transitions of Mhp1, the membrane protein for sodium-linked transport of hydantoins from Microbacterium liquefaciens. Mhp1 has been crystallized in three forms (outward-facing open, outward-facing occluded with substrate bound, and inward-facing open). We show that one natural cysteine residue, Cys327, out of three, has an enhanced solvent accessibility in the inward-facing (relative to the outward-facing) form. Reaction of the purified protein, in detergent, with the thiol-reactive N-ethylmalemide (NEM), results in modification of Cys327, suggesting that Mhp1 adopts predominantly inward-facing conformations. Addition of either sodium ions or the substrate 5-benzyl-l-hydantoin (L-BH) does not shift this conformational equilibrium, but systematic co-addition of the two results in an attenuation of labeling, indicating a shift toward outward-facing conformations that can be interpreted using conventional enzyme kinetic analyses. Such measurements can afford the Km for each ligand as well as the stoichiometry of ion–substrate-coupled conformational changes. Mutations that perturb the substrate binding site either result in the protein being unable to adopt outward-facing conformations or in a global destabilization of structure. The methodology combines covalent labeling, mass spectrometry, and kinetic analyses in a straightforward workflow applicable to a range of systems, enabling the interrogation of changes in a protein’s conformation required for function at varied concentrations of substrates, and the consequences of mutations on these conformational transitions.},
	number = {17},
	urldate = {2018-01-17},
	journal = {Analytical Chemistry},
	author = {Calabrese, Antonio N. and Jackson, Scott M. and Jones, Lynsey N. and Beckstein, Oliver and Heinkel, Florian and Gsponer, Joerg and Sharples, David and Sans, Marta and Kokkinidou, Maria and Pearson, Arwen R. and Radford, Sheena E. and Ashcroft, Alison E. and Henderson, Peter J. F.},
	month = sep,
	year = {2017},
	pages = {8844--8852},
}

Cys accessibility and quantitative intact mass spectrometry (MS) analyses have been devised to study the topological transitions of Mhp1, the membrane protein for sodium-linked transport of hydantoins from Microbacterium liquefaciens. Mhp1 has been crystallized in three forms (outward-facing open, outward-facing occluded with substrate bound, and inward-facing open). We show that one natural cysteine residue, Cys327, out of three, has an enhanced solvent accessibility in the inward-facing (relative to the outward-facing) form. Reaction of the purified protein, in detergent, with the thiol-reactive N-ethylmalemide (NEM), results in modification of Cys327, suggesting that Mhp1 adopts predominantly inward-facing conformations. Addition of either sodium ions or the substrate 5-benzyl-l-hydantoin (L-BH) does not shift this conformational equilibrium, but systematic co-addition of the two results in an attenuation of labeling, indicating a shift toward outward-facing conformations that can be interpreted using conventional enzyme kinetic analyses. Such measurements can afford the Km for each ligand as well as the stoichiometry of ion–substrate-coupled conformational changes. Mutations that perturb the substrate binding site either result in the protein being unable to adopt outward-facing conformations or in a global destabilization of structure. The methodology combines covalent labeling, mass spectrometry, and kinetic analyses in a straightforward workflow applicable to a range of systems, enabling the interrogation of changes in a protein’s conformation required for function at varied concentrations of substrates, and the consequences of mutations on these conformational transitions.

@inproceedings{khoshlessan_parallel_2017,
	address = {Austin, TX},
	title = {Parallel {Analysis} in {MDAnalysis} using the {Dask} {Parallel} {Computing} {Library}},
	url = {http://conference.scipy.org/proceedings/scipy2017/mahzad_khoslessan.html},
	doi = {10.25080/shinma-7f4c6e7-00a},
	urldate = {2017-07-17},
	booktitle = {Proceedings of the 16th {Python} in {Science} {Conference}},
	author = {Khoshlessan, Mahzad and Paraskevakos, Ioannis and Jha, Shantenu and Beckstein, Oliver},
	editor = {Huff, Katy and Lippa, David and Niederhut, Dillon and Pacer, M},
	year = {2017},
	pages = {64--72},
}

@article{domanski_ligandbook:_2017,
	title = {Ligandbook: an online repository for small and drug-like molecule force field parameters},
	volume = {33},
	issn = {1367-4803},
	shorttitle = {Ligandbook},
	url = {https://doi.org/10.1093/bioinformatics/btx037},
	doi = {10.1093/bioinformatics/btx037},
	number = {11},
	urldate = {2017-06-12},
	journal = {Bioinformatics},
	author = {Domański, Jan and Beckstein, Oliver and Iorga, Bogdan I.},
	month = jun,
	year = {2017},
	pages = {1747--1749},
}

@inproceedings{gowers_mdanalysis:_2016,
	address = {Austin, TX},
	title = {{MDAnalysis}: {A} {Python} package for the rapid analysis of molecular dynamics simulations.},
	url = {http://conference.scipy.org/proceedings/scipy2016/oliver_beckstein.html},
	doi = {10.25080/Majora-629e541a-00e},
	abstract = {MDAnalysis (http://mdanalysis.org) is a library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. MD simulations of biological molecules have become an important tool to elucidate the relationship between molecular structure and physiological function. Simulations are performed with highly optimized software packages on HPC resources but most codes generate output trajectories in their own formats so that the development of new trajectory analysis algorithms is confined to specific user communities and widespread adoption and further development is delayed. MDAnalysis addresses this problem by abstracting access to the raw simulation data and presenting a uniform object-oriented Python interface to the user. It thus enables users to rapidly write code that is portable and immediately usable in virtually all biomolecular simulation communities. The user interface and modular design work equally well in complex scripted work flows, as foundations for other packages, and for interactive and rapid prototyping work in IPython / Jupyter notebooks, especially together with molecular visualization provided by nglview and time series analysis with pandas. MDAnalysis is written in Python and Cython and uses NumPy arrays for easy interoperability with the wider scientific Python ecosystem. It is widely used and forms the foundation for more specialized biomolecular simulation tools. MDAnalysis is available under the GNU General Public License v2.},
	booktitle = {Proceedings of the 15th {Python} in {Science} {Conference}},
	author = {Gowers, R. J and Linke, M. and Barnoud, J. and {T. J. E. Reddy} and Melo, M. N. and Seyler, S. L. and Dotson, D. L. and Domanski, J. and Buchoux, S. and Kenney, I. M. and Beckstein, O.},
	editor = {Benthall, Sebastian and Rostrup, Scott},
	year = {2016},
	pages = {102--109},
}

MDAnalysis (http://mdanalysis.org) is a library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. MD simulations of biological molecules have become an important tool to elucidate the relationship between molecular structure and physiological function. Simulations are performed with highly optimized software packages on HPC resources but most codes generate output trajectories in their own formats so that the development of new trajectory analysis algorithms is confined to specific user communities and widespread adoption and further development is delayed. MDAnalysis addresses this problem by abstracting access to the raw simulation data and presenting a uniform object-oriented Python interface to the user. It thus enables users to rapidly write code that is portable and immediately usable in virtually all biomolecular simulation communities. The user interface and modular design work equally well in complex scripted work flows, as foundations for other packages, and for interactive and rapid prototyping work in IPython / Jupyter notebooks, especially together with molecular visualization provided by nglview and time series analysis with pandas. MDAnalysis is written in Python and Cython and uses NumPy arrays for easy interoperability with the wider scientific Python ecosystem. It is widely used and forms the foundation for more specialized biomolecular simulation tools. MDAnalysis is available under the GNU General Public License v2.

@inproceedings{dotson_datreant:_2016,
	address = {Austin, TX},
	title = {datreant: persistent, {Pythonic} trees for heterogeneous data},
	url = {http://conference.scipy.org/proceedings/scipy2016/david_dotson.html},
	doi = {10.25080/Majora-629e541a-007},
	abstract = {n science the filesystem often serves as a de facto database, with directory trees being the zeroth-order scientific data structure. But it can be tedious and error prone to work directly with the filesystem to retrieve and store heterogeneous datasets. datreant makes working with directory structures and files Pythonic with Treants: specially marked directories with distinguishing characteristics that can be discovered, queried, and filtered. Treants can be manipulated individually and in aggregate, with mechanisms for granular access to the directories and files in their trees. Disparate datasets stored in any format (CSV, HDF5, NetCDF, Feather, etc.) scattered throughout a filesystem can thus be manipulated as meta-datasets of Treants. datreant is modular and extensible by design to allow specialized applications to be built on top of it, with MDSynthesis as an example for working with molecular dynamics simulation data. http://datreant.org/},
	booktitle = {Proceedings of the 15th {Python} in {Science} {Conference}},
	author = {Dotson, David L. and Seyler, Sean L and Linke, Max and Gowers, Richard J. and Beckstein, Oliver},
	editor = {Benthall, Sebastian and Rostrup, Scott},
	year = {2016},
	pages = {51 -- 56},
}

n science the filesystem often serves as a de facto database, with directory trees being the zeroth-order scientific data structure. But it can be tedious and error prone to work directly with the filesystem to retrieve and store heterogeneous datasets. datreant makes working with directory structures and files Pythonic with Treants: specially marked directories with distinguishing characteristics that can be discovered, queried, and filtered. Treants can be manipulated individually and in aggregate, with mechanisms for granular access to the directories and files in their trees. Disparate datasets stored in any format (CSV, HDF5, NetCDF, Feather, etc.) scattered throughout a filesystem can thus be manipulated as meta-datasets of Treants. datreant is modular and extensible by design to allow specialized applications to be built on top of it, with MDSynthesis as an example for working with molecular dynamics simulation data. http://datreant.org/

@article{coincon_crystal_2016,
	title = {Crystal structures reveal the molecular basis of ion translocation in sodium/proton antiporters},
	volume = {23},
	copyright = {© 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
	issn = {1545-9993},
	url = {http://www.nature.com/nsmb/journal/v23/n3/full/nsmb.3164.html},
	doi = {10.1038/nsmb.3164},
	abstract = {To fully understand the transport mechanism of Na+/H+ exchangers, it is necessary to clearly establish the global rearrangements required to facilitate ion translocation. Currently, two different transport models have been proposed. Some reports have suggested that structural isomerization is achieved through large elevator-like rearrangements similar to those seen in the structurally unrelated sodium-coupled glutamate-transporter homolog GltPh. Others have proposed that only small domain movements are required for ion exchange, and a conventional rocking-bundle model has been proposed instead. Here, to resolve these differences, we report atomic-resolution structures of the same Na+/H+ antiporter (NapA from Thermus thermophilus) in both outward- and inward-facing conformations. These data combined with cross-linking, molecular dynamics simulations and isothermal calorimetry suggest that Na+/H+ antiporters provide alternating access to the ion-binding site by using elevator-like structural transitions.},
	language = {en},
	number = {3},
	urldate = {2016-04-04},
	journal = {Nature Structural \& Molecular Biology},
	author = {Coincon, Mathieu and Uzdavinys, Povilas and Nji, Emmanuel and Dotson, David L. and Winkelmann, Iven and Abdul-Hussein, Saba and Cameron, Alexander D. and Beckstein, Oliver and Drew, David},
	month = mar,
	year = {2016},
	keywords = {Membrane proteins, X-ray crystallography},
	pages = {248--255},
}

To fully understand the transport mechanism of Na+/H+ exchangers, it is necessary to clearly establish the global rearrangements required to facilitate ion translocation. Currently, two different transport models have been proposed. Some reports have suggested that structural isomerization is achieved through large elevator-like rearrangements similar to those seen in the structurally unrelated sodium-coupled glutamate-transporter homolog GltPh. Others have proposed that only small domain movements are required for ion exchange, and a conventional rocking-bundle model has been proposed instead. Here, to resolve these differences, we report atomic-resolution structures of the same Na+/H+ antiporter (NapA from Thermus thermophilus) in both outward- and inward-facing conformations. These data combined with cross-linking, molecular dynamics simulations and isothermal calorimetry suggest that Na+/H+ antiporters provide alternating access to the ion-binding site by using elevator-like structural transitions.

@article{ulmschneider_peptide_2015,
	title = {Peptide {Folding} in {Translocon}-{Like} {Pores}},
	volume = {248},
	issn = {0022-2631, 1432-1424},
	url = {http://link.springer.com/article/10.1007/s00232-015-9808-7},
	doi = {10.1007/s00232-015-9808-7},
	abstract = {The cellular translocon, present in all three domains of life, is one of the most versatile and important biological nanopores. This complex molecular apparatus is directly responsible for the secretion of globular proteins across membranes as well as the insertion of integral membrane proteins into lipid bilayers. Recently determined structures of the archaean SecY translocon reveal an hour-glass-shaped pore, which accommodates the nascent peptide chain during translocation. While these structures provide important insights into ribosome binding to the translocon, threading of the nascent chain into the channel, and lateral gate opening for releasing the folded helical peptide into the membrane bilayer, the exact folding pathway of the peptide inside the protein-conducting channel during translocation and prior to the lateral release into the bilayer remains elusive. In the present study, we use molecular dynamics simulations to investigate atomic resolution peptide folding in hour-glass-shaped pore models that are based on the SecY translocon channel structure. The theoretical setup allows systematic variation of key determinants of folding, in particular the degree of confinement of the peptide and the hydration level of the pore. A 27-residue hydrophobic peptide was studied that is preferentially inserted into membranes by the translocon. Our results show that both pore diameter as well as channel hydration are important determinants for folding efficiency and helical stability of the peptide, therefore providing important insights into translocon gating and lateral peptide partitioning.},
	language = {en},
	number = {3},
	urldate = {2015-07-01},
	journal = {The Journal of Membrane Biology},
	author = {Ulmschneider, Martin B. and Leman, Julia Koehler and Fennell, Hayden and Beckstein, Oliver},
	month = may,
	year = {2015},
	keywords = {Biochemistry, general, Human Physiology, OPLS, Protein folding, SecY translocon, membrane protein, molecular dynamics},
	pages = {407--417},
}

The cellular translocon, present in all three domains of life, is one of the most versatile and important biological nanopores. This complex molecular apparatus is directly responsible for the secretion of globular proteins across membranes as well as the insertion of integral membrane proteins into lipid bilayers. Recently determined structures of the archaean SecY translocon reveal an hour-glass-shaped pore, which accommodates the nascent peptide chain during translocation. While these structures provide important insights into ribosome binding to the translocon, threading of the nascent chain into the channel, and lateral gate opening for releasing the folded helical peptide into the membrane bilayer, the exact folding pathway of the peptide inside the protein-conducting channel during translocation and prior to the lateral release into the bilayer remains elusive. In the present study, we use molecular dynamics simulations to investigate atomic resolution peptide folding in hour-glass-shaped pore models that are based on the SecY translocon channel structure. The theoretical setup allows systematic variation of key determinants of folding, in particular the degree of confinement of the peptide and the hydration level of the pore. A 27-residue hydrophobic peptide was studied that is preferentially inserted into membranes by the translocon. Our results show that both pore diameter as well as channel hydration are important determinants for folding efficiency and helical stability of the peptide, therefore providing important insights into translocon gating and lateral peptide partitioning.

@article{seyler_path_2015,
	title = {Path {Similarity} {Analysis}: {A} {Method} for {Quantifying} {Macromolecular} {Pathways}},
	volume = {11},
	shorttitle = {Path {Similarity} {Analysis}},
	url = {https://doi.org/10.1371/journal.pcbi.1004568},
	doi = {10.1371/journal.pcbi.1004568},
	abstract = {Author Summary Many proteins are nanomachines that perform mechanical or chemical work by changing their three-dimensional shape and cycle between multiple conformational states. Computer simulations of such conformational transitions provide mechanistic insights into protein function but such simulations have been challenging. In particular, it is not clear how to quantitatively compare current simulation methods or to assess their accuracy. To that end, we present a general and flexible computational framework for quantifying transition paths—by measuring mutual geometric similarity—that, compared with existing approaches, requires minimal a-priori assumptions and can take advantage of full atomic detail alongside heuristic information derived from intuition. Using our Path Similarity Analysis (PSA) framework in parallel with several existing quantitative approaches, we examine transitions generated for a toy model of a transition and two biological systems, the enzyme adenylate kinase and diphtheria toxin. Our results show that PSA enables the quantitative comparison of different path sampling methods and aids the identification of potentially important atomistic motions by exploiting geometric information in transition paths. The method has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing macromolecular conformational transitions.},
	number = {10},
	urldate = {2015-10-22},
	journal = {PLoS Comput Biol},
	author = {Seyler, Sean L. and Kumar, Avishek and Thorpe, M. F. and Beckstein, Oliver},
	month = oct,
	year = {2015},
	pages = {e1004568},
}

Author Summary Many proteins are nanomachines that perform mechanical or chemical work by changing their three-dimensional shape and cycle between multiple conformational states. Computer simulations of such conformational transitions provide mechanistic insights into protein function but such simulations have been challenging. In particular, it is not clear how to quantitatively compare current simulation methods or to assess their accuracy. To that end, we present a general and flexible computational framework for quantifying transition paths—by measuring mutual geometric similarity—that, compared with existing approaches, requires minimal a-priori assumptions and can take advantage of full atomic detail alongside heuristic information derived from intuition. Using our Path Similarity Analysis (PSA) framework in parallel with several existing quantitative approaches, we examine transitions generated for a toy model of a transition and two biological systems, the enzyme adenylate kinase and diphtheria toxin. Our results show that PSA enables the quantitative comparison of different path sampling methods and aids the identification of potentially important atomistic motions by exploiting geometric information in transition paths. The method has the potential to enhance our understanding of transition path sampling methods, validate them, and to provide a new approach to analyzing macromolecular conformational transitions.

@article{simmons_molecular_2014,
	title = {Molecular mechanism of ligand recognition by a membrane transport protein, {Mhp1}},
	volume = {33},
	copyright = {© 2014 The Authors. Published under the terms of the CC BY 4.0 license. This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.},
	issn = {0261-4189, 1460-2075},
	url = {http://emboj.embopress.org/content/33/16/1831},
	doi = {10.15252/embj.201387557},
	abstract = {The hydantoin transporter Mhp1 is a sodium‐coupled secondary active transport protein of the nucleobase‐cation‐symport family and a member of the widespread 5‐helix inverted repeat superfamily of transporters. The structure of Mhp1 was previously solved in three different conformations providing insight into the molecular basis of the alternating access mechanism. Here, we elucidate detailed events of substrate binding, through a combination of crystallography, molecular dynamics, site‐directed mutagenesis, biochemical/biophysical assays, and the design and synthesis of novel ligands. We show precisely where 5‐substituted hydantoin substrates bind in an extended configuration at the interface of the bundle and hash domains. They are recognised through hydrogen bonds to the hydantoin moiety and the complementarity of the 5‐substituent for a hydrophobic pocket in the protein. Furthermore, we describe a novel structure of an intermediate state of the protein with the external thin gate locked open by an inhibitor, 5‐(2‐naphthylmethyl)‐L‐hydantoin, which becomes a substrate when leucine 363 is changed to an alanine. We deduce the molecular events that underlie acquisition and transport of a ligand by Mhp1.
Synopsis



Structure‐function and molecular dynamics analysis of the hydantoin active transporter Mhp1 yields a novel intermediate state and delineates the basis for substrate specificity and membrane transport.

Hydantoin substrates like indolylmethylhydantoin (IMH) bind to the LeuT‐like Mhp1 transporter in an extended conformationSelectivity of Mhp1 for the substrate is conferred by hydrogen bonds to the hydantoin moiety and the fit of aromatic substituent into a hydrophobic pocketNaphthylmethylhydantoin (NMH) inhibits Mhp1 but is not transportedCrystal structure of Mhp1 with NMH shows TMH10 to adopt the position seen in the outward‐open rather than the occluded state.Mutation of Leu363Ala in TMH10 of Mhp1 converts NMH from an inhibitor to a substrate.},
	language = {en},
	urldate = {2014-06-25},
	journal = {The EMBO Journal},
	author = {Simmons, Katie J. and Jackson, Scott M. and Brueckner, Florian and Patching, Simon G. and Beckstein, Oliver and Ivanova, Ekaterina and Geng, Tian and Weyand, Simone and Drew, David and Lanigan, Joseph and Sharples, David J. and Sansom, Mark SP and Iwata, So and Fishwick, Colin WG and Johnson, A. Peter and Cameron, Alexander D. and Henderson, Peter JF},
	month = jun,
	year = {2014},
	keywords = {Mhp1, five helix inverted repeat superfamily, hydantoin, membrane transport, molecular recognition, nucleobase‐cation‐symport, NCS1, family},
	pages = {1831--1844},
}

The hydantoin transporter Mhp1 is a sodium‐coupled secondary active transport protein of the nucleobase‐cation‐symport family and a member of the widespread 5‐helix inverted repeat superfamily of transporters. The structure of Mhp1 was previously solved in three different conformations providing insight into the molecular basis of the alternating access mechanism. Here, we elucidate detailed events of substrate binding, through a combination of crystallography, molecular dynamics, site‐directed mutagenesis, biochemical/biophysical assays, and the design and synthesis of novel ligands. We show precisely where 5‐substituted hydantoin substrates bind in an extended configuration at the interface of the bundle and hash domains. They are recognised through hydrogen bonds to the hydantoin moiety and the complementarity of the 5‐substituent for a hydrophobic pocket in the protein. Furthermore, we describe a novel structure of an intermediate state of the protein with the external thin gate locked open by an inhibitor, 5‐(2‐naphthylmethyl)‐L‐hydantoin, which becomes a substrate when leucine 363 is changed to an alanine. We deduce the molecular events that underlie acquisition and transport of a ligand by Mhp1. Synopsis Structure‐function and molecular dynamics analysis of the hydantoin active transporter Mhp1 yields a novel intermediate state and delineates the basis for substrate specificity and membrane transport. Hydantoin substrates like indolylmethylhydantoin (IMH) bind to the LeuT‐like Mhp1 transporter in an extended conformationSelectivity of Mhp1 for the substrate is conferred by hydrogen bonds to the hydantoin moiety and the fit of aromatic substituent into a hydrophobic pocketNaphthylmethylhydantoin (NMH) inhibits Mhp1 but is not transportedCrystal structure of Mhp1 with NMH shows TMH10 to adopt the position seen in the outward‐open rather than the occluded state.Mutation of Leu363Ala in TMH10 of Mhp1 converts NMH from an inhibitor to a substrate.

@article{lee_two-domain_2013,
	title = {A two-domain elevator mechanism for sodium/proton antiport},
	volume = {501},
	url = {http://dx.doi.org/10.1038/nature12484},
	doi = {10.1038/nature12484},
	abstract = {Sodium/proton (Na+/H+) antiporters, located at the plasma membrane in every cell, are vital for cell homeostasis. In humans, their dysfunction has been linked to diseases, such as hypertension, heart failure and epilepsy, and they are well-established drug targets. The best understood model system for Na+/H+ antiport is NhaA from Escherichia coli, for which both electron microscopy and crystal structures are available. NhaA is made up of two distinct domains: a core domain and a dimerization domain. In the NhaA crystal structure a cavity is located between the two domains, providing access to the ion-binding site from the inward-facing surface of the protein. Like many Na+/H+ antiporters, the activity of NhaA is regulated by pH, only becoming active above pH 6.5, at which point a conformational change is thought to occur. The only reported NhaA crystal structure so far is of the low pH inactivated form. Here we describe the active-state structure of a Na+/H+ antiporter, NapA from Thermus thermophilus, at 3 {\textbackslash}AA resolution, solved from crystals grown at pH 7.8. In the NapA structure, the core and dimerization domains are in different positions to those seen in NhaA, and a negatively charged cavity has now opened to the outside. The extracellular cavity allows access to a strictly conserved aspartate residue thought to coordinate ion binding directly, a role supported here by molecular dynamics simulations. To alternate access to this ion-binding site, however, requires a surprisingly large rotation of the core domain, some 20$^{\textrm{{\textbackslash}circ\$}}$ against the dimerization interface. We conclude that despite their fast transport rates of up to 1,500 ions per second, Na+/H+ antiporters operate by a two-domain rocking bundle model, revealing themes relevant to secondary-active transporters in general.},
	number = {7468},
	journal = {Nature},
	author = {Lee, Chiara and Kang, Hae Joo and von Ballmoos, Christoph and Newstead, Simon and Uzdavinys, Povilas and Dotson, David L. and Iwata, So and Beckstein, Oliver and Cameron, Alexander D. and Drew, David},
	month = sep,
	year = {2013},
	keywords = {MD SIMULATION, Na+, NapA, NhaA, antiporter, transporter},
	pages = {573--577},
}

Sodium/proton (Na+/H+) antiporters, located at the plasma membrane in every cell, are vital for cell homeostasis. In humans, their dysfunction has been linked to diseases, such as hypertension, heart failure and epilepsy, and they are well-established drug targets. The best understood model system for Na+/H+ antiport is NhaA from Escherichia coli, for which both electron microscopy and crystal structures are available. NhaA is made up of two distinct domains: a core domain and a dimerization domain. In the NhaA crystal structure a cavity is located between the two domains, providing access to the ion-binding site from the inward-facing surface of the protein. Like many Na+/H+ antiporters, the activity of NhaA is regulated by pH, only becoming active above pH 6.5, at which point a conformational change is thought to occur. The only reported NhaA crystal structure so far is of the low pH inactivated form. Here we describe the active-state structure of a Na+/H+ antiporter, NapA from Thermus thermophilus, at 3 \AA resolution, solved from crystals grown at pH 7.8. In the NapA structure, the core and dimerization domains are in different positions to those seen in NhaA, and a negatively charged cavity has now opened to the outside. The extracellular cavity allows access to a strictly conserved aspartate residue thought to coordinate ion binding directly, a role supported here by molecular dynamics simulations. To alternate access to this ion-binding site, however, requires a surprisingly large rotation of the core domain, some 20$^{\textrm{{\}circ$$ against the dimerization interface. We conclude that despite their fast transport rates of up to 1,500 ions per second, Na+/H+ antiporters operate by a two-domain rocking bundle model, revealing themes relevant to secondary-active transporters in general.

@incollection{cameron_5-helix_2013,
	address = {Berlin, Heidelberg},
	title = {The 5-helix inverted repeat superfamily of membrane transport proteins},
	isbn = {978-3-642-16711-9},
	url = {https://doi.org/10.1007/978-3-642-16712-6_772},
	booktitle = {Encylopedia of {Biophysics}},
	publisher = {Springer},
	author = {Cameron, Alexander D and Beckstein, Oliver and Henderson, Peter JF},
	editor = {Roberts, Gordon C. K.},
	year = {2013},
	pages = {1481--1485},
}

@incollection{jackson_mhp1_2013,
	address = {Berlin, Heidelberg},
	title = {Mhp1, the {Na}⁺-{Hydantoin} {Membrane} {Transport} {Protein}},
	isbn = {978-3-642-16711-9},
	url = {https://doi.org/10.1007/978-3-642-16712-6_670},
	abstract = {Mhp1 is a member of the Nucleobase-Cation-Symport-1 (NCS-1) family designated A.2.39.5 (Saier et al 2006, 2009; Ren and Paulsen, 2010), which carries out transport across membranes of hydantoins substituted with aromatic rings in the 5-position. The wild-type protein contains 489 amino acids (Suzuki and Henderson 2006), modestly modified in a genetic construct at the N-terminus and C-terminus, where a (His)6 tag is incorporated to facilitate amplified expression, purification and crystallisation (Suzuki and Henderson 2006; Shimamura et al, 2008). The transport reaction of Mhp1 is Hydantoin (out) + Na+ (out) –{\textgreater} Hydantoin (in) + Na+ (in) This reaction is of commercial interest, because of the potential for converting waste hydantoins to compounds of added value, for example L-amino acids (Suzuki et al 2005; Javier et al 2009).},
	booktitle = {Encylopedia of {Biophysics}},
	publisher = {Springer},
	author = {Jackson, Scott M and Ivanova, Ekaterina and Simmons, Katie and Patching, Simon G and Weyand, Simone and Shimamura, Tatsuro and Brückner, Florian and Iwata, So and Sharples, David J and Baldwin, Stephen A and Sansom, Mark PS and Beckstein, Oliver and Cameron, Alexander D and Henderson, Peter JF},
	editor = {Roberts, Gordon C. K.},
	year = {2013},
	pages = {1514--1521},
}

Mhp1 is a member of the Nucleobase-Cation-Symport-1 (NCS-1) family designated A.2.39.5 (Saier et al 2006, 2009; Ren and Paulsen, 2010), which carries out transport across membranes of hydantoins substituted with aromatic rings in the 5-position. The wild-type protein contains 489 amino acids (Suzuki and Henderson 2006), modestly modified in a genetic construct at the N-terminus and C-terminus, where a (His)6 tag is incorporated to facilitate amplified expression, purification and crystallisation (Suzuki and Henderson 2006; Shimamura et al, 2008). The transport reaction of Mhp1 is Hydantoin (out) + Na+ (out) –\textgreater Hydantoin (in) + Na+ (in) This reaction is of commercial interest, because of the potential for converting waste hydantoins to compounds of added value, for example L-amino acids (Suzuki et al 2005; Javier et al 2009).

@incollection{weyand_nucleobase-cation-symport-1_2011,
	series = {Encyclopedia of {Inorganic} and {Bioinorganic} {Chemistry}},
	title = {The {Nucleobase}-{Cation}-{Symport}-1 {Family} of {Membrane} {Transport} {Proteins}},
	url = {https://doi.org/10.1002/9781119951438.eibc0685},
	abstract = {The evolutionary relationships of membrane transport proteins of the nucleobase-cation-symport (NCS-1) family from bacteria, fungi, and plants are described. The reported substrates of the NCS-1 family include nucleobases, hydantoins, and vitamins. Secondary active transport of substrate accompanied by a sodium ion, or possibly a proton, is the usual mechanism of energization. A strategy for the amplified expression, purification, and activity assays of bacterial members of the NCS-1 family is described. Conditions are given for the production of diffracting crystals of one member, the Na+-coupled transporter for aromatic hydantoins, `Mhp1', from Microbacterium liquefaciens. The 3D structures of three forms of the Mhp1 protein are discussed in terms of one open-outward, one substrate-occluded, and one inward-open conformation contributing to a molecular dynamics simulation of the alternating-access model of membrane transport. The unexpected similarity of the protein fold of Mhp1 to those of transport proteins, hitherto thought to be from different evolutionary families, is discussed.},
	booktitle = {Handbook of {Metalloproteins}},
	publisher = {Wiley},
	author = {Weyand, Simone and Ma, Pikyee and Saidijam, Massoud and Baldwin, Jocelyn and Beckstein, Oliver and Jackson, Scott and Suzuki, Shun'ichi and Patching, Simon G and Shimamura, Tatsuro and Sansom, Mark S. P. and Iwata, So and Cameron, Alexander D and Baldwin, Stephen A and Henderson, Peter J. F.},
	editor = {Messerschmidt, Albrecht},
	year = {2011},
	keywords = {CodB, HMET 268, MD SIMULATION, Membrane Transport, Mhp1, Na+, PacI, hydantoin, membrane transport protein, nucleobase, review, sodium, transporter structure},
}

The evolutionary relationships of membrane transport proteins of the nucleobase-cation-symport (NCS-1) family from bacteria, fungi, and plants are described. The reported substrates of the NCS-1 family include nucleobases, hydantoins, and vitamins. Secondary active transport of substrate accompanied by a sodium ion, or possibly a proton, is the usual mechanism of energization. A strategy for the amplified expression, purification, and activity assays of bacterial members of the NCS-1 family is described. Conditions are given for the production of diffracting crystals of one member, the Na+-coupled transporter for aromatic hydantoins, `Mhp1', from Microbacterium liquefaciens. The 3D structures of three forms of the Mhp1 protein are discussed in terms of one open-outward, one substrate-occluded, and one inward-open conformation contributing to a molecular dynamics simulation of the alternating-access model of membrane transport. The unexpected similarity of the protein fold of Mhp1 to those of transport proteins, hitherto thought to be from different evolutionary families, is discussed.

@phdthesis{beckstein_principles_2005,
	address = {Oxford, UK},
	type = {{DPhil} {Thesis}},
	title = {Principles of {Gating} {Mechanisms} of {Ion} {Channels}},
	url = {https://doi.org/10.6084/m9.figshare.1166494},
	abstract = {Ion channels such as the nicotinic acetylcholine receptor (nAChR) fulfil essential roles in fast nerve transmission and cell signalling by converting an external signal into an ionic current, which in turn triggers further down-stream signalling events in the cell. Increasing structural evidence suggests that the actual mechanisms by which channels gate i.e. switch their ion permeability) are fairly universal: Conduction pathways are either physically occluded by localised sidechains or the pore is narrowed by large-scale protein motions so that a constriction lined by hydrophobic sidechains is formed. In this work the latter mechanism, termed hydrophobic gating, is investigated by atomistic computer simulations.
Simple hydrophobic model pores were constructed with dimensions estimated for the putative gate region of nAChR (length 0.8 nm, radius varied between 0.15 nm and 1.0 nm). In long classical molecular dynamics (MD) simulations, water confined in the pore was found to oscillate between a liquid and a vapour phase on a nano second time scale. Water would rarely permeate a pore less wide than three water molecules. A simple thermodynamic model based on surface energies was developed, which explains the observed liquid-vapour oscillations and their dependence on pore radius and surface hydrophobicity. Similarly, sodium ion flux is only appreciable for pore radii greater than 0.6 nm. Calculation of the free energy profile of translocating ions showed barriers to permeation of greater 10 kT for pore radii less than 0.4 nm. Comparison to continuum-electrostatic Poisson-Boltzmann calculations indicates that the behaviour of the solvent, i.e. water, is crucial for a correct description of ions in apolar pores. Together, these results indicate that a hydrophobic constriction site can act as a hydrophobic gate.
An ongoing debate concerns the nature and position of the gate in nAChR. Based on the recent cryo-electron microscopy structure of the transmembrane domain at 4 Å resolution, and using techniques established for the model pores, equilibrium densities and free energy profiles were calculated for Na+, Cl-, and water. It was found that ions would have to overcome a sizable free energy barrier of about 10 kT at a hydrophobic girdle between residues L9' and V13', previously implicated in gating. This suggests strongly that nAChR contains a hydrophobic gate. Furthermore, charged rings at both ends of the pore act as concentrators of ions up to about six times the bulk concentration; an effect which would increase the ion current in the open state. The robustness of the results is discussed with respect to different parameter sets (force fields) and the applied modelling procedure.},
	language = {English},
	urldate = {2014-11-06},
	school = {University of Oxford},
	author = {Beckstein, Oliver},
	year = {2005},
	keywords = {Gibbs free energy, Ion Channels, gating, hydrophobic gating, hydrophobicity, ion permeation, molecular dynamics, potential of mean force, water},
}

Ion channels such as the nicotinic acetylcholine receptor (nAChR) fulfil essential roles in fast nerve transmission and cell signalling by converting an external signal into an ionic current, which in turn triggers further down-stream signalling events in the cell. Increasing structural evidence suggests that the actual mechanisms by which channels gate i.e. switch their ion permeability) are fairly universal: Conduction pathways are either physically occluded by localised sidechains or the pore is narrowed by large-scale protein motions so that a constriction lined by hydrophobic sidechains is formed. In this work the latter mechanism, termed hydrophobic gating, is investigated by atomistic computer simulations. Simple hydrophobic model pores were constructed with dimensions estimated for the putative gate region of nAChR (length 0.8 nm, radius varied between 0.15 nm and 1.0 nm). In long classical molecular dynamics (MD) simulations, water confined in the pore was found to oscillate between a liquid and a vapour phase on a nano second time scale. Water would rarely permeate a pore less wide than three water molecules. A simple thermodynamic model based on surface energies was developed, which explains the observed liquid-vapour oscillations and their dependence on pore radius and surface hydrophobicity. Similarly, sodium ion flux is only appreciable for pore radii greater than 0.6 nm. Calculation of the free energy profile of translocating ions showed barriers to permeation of greater 10 kT for pore radii less than 0.4 nm. Comparison to continuum-electrostatic Poisson-Boltzmann calculations indicates that the behaviour of the solvent, i.e. water, is crucial for a correct description of ions in apolar pores. Together, these results indicate that a hydrophobic constriction site can act as a hydrophobic gate. An ongoing debate concerns the nature and position of the gate in nAChR. Based on the recent cryo-electron microscopy structure of the transmembrane domain at 4 Å resolution, and using techniques established for the model pores, equilibrium densities and free energy profiles were calculated for Na+, Cl-, and water. It was found that ions would have to overcome a sizable free energy barrier of about 10 kT at a hydrophobic girdle between residues L9' and V13', previously implicated in gating. This suggests strongly that nAChR contains a hydrophobic gate. Furthermore, charged rings at both ends of the pore act as concentrators of ions up to about six times the bulk concentration; an effect which would increase the ion current in the open state. The robustness of the results is discussed with respect to different parameter sets (force fields) and the applied modelling procedure.