As computer hardware and software algorithms have increased the timescales and statistical sampling accessible by all-atom molecular simulations, modeling ligand binding mechanisms using Markov State Model (MSM) approaches has become increasingly useful. MSMs, which describe conformational dynamics as a kinetic network of transitions between metastable states, can provide estimates of ligand binding kinetics and pathways in atomic detail, as well as receptor dynamics important to allostery. In this presentation, I will discuss some lessons learned from building MSMs of ligand binding, of designed peptidomimetics to protein targets, and to understand the allosteric regulation of a key metabolic enzyme phenylalanine hydroxylase.  One of the main challenges in constructing MSMs of ligand binding is the difficulty of estimating affinities and off-rates because trajectory data is typically non-equilibrium. I will discuss our recent attempts to remedy this problem by constructing multi-ensemble Markov Models (MEMMs) from simulations performed with bias potentials that encourage productive binding and unbinding events. <br/>

Unveiling ligand binding mechanisms through molecular simulation: Lessons and progress from Markov model approaches

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.