Tag 1 | Beckstein Lab

Fiona was a postdoc in the lab. Her research interests include free energy calculations, enhanced sampling methods and software development for MD. Her current project aims to use computational methods to characterise the structural and energetic underpinnings of bile acid transporters.

The enzyme adenylate kinase (AdK) undergoes a large hinge-like motion. In 2009, we studied the conformational transition between open and closed E. coli AdK without substrate, i.e. “apo AdK”, with a variety of computational methods. As part of the study we also produced a free energy landscape (a potential of mean force or PMF) as a function of the two domain angles. Here we make the data of the underlying free energy landscape available to other researchers so that they can use them in their own research.

This summer’s Lab Book Club is designed to provide a thorough review of fundamental concepts for understanding biomolecular simulation and, in particular,molecular dynamics simulations (MD). The material is primarily based on chapters from Statistical Mechanics: Theory and Molecular Simulation by Mark Tuckerman.

Ian is a Postdoctoral Research Scholar working on sustainable and expandable software for the analysis of molecular simulations. He graduated with a PhD in Physics from ASU in 2022. He worked on quantitative simulations of transporter proteins and methods and protocols to accurately calculate solvation energies of small and drug-like molecules.

While equilibrium MD is considered the most robust approach to simulating macromolecular conformational changes, conformational transitions are rare events that take place on much faster timescales than the waiting times spent in metastable equilibrium states. Equilibrium simulations thus spend relatively little time sampling actual transition events. Fast transition path sampling methods seek to mitigate the rare event sampling problem, though the full extent to which biased or coarse-grained approaches can replicate physical ensembles of transitions is unknown.