2018
DOI: 10.1101/346817
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Mapping the ligand binding landscape

Abstract: The interaction between a ligand and a protein involves a multitude of conformational states. To achieve a particular deeply-bound pose the ligand must search across a rough free energy landscape, with many metastable minima. Creating maps of the ligand binding landscape is a great challenge, as binding and release events typically occur on timescales that are beyond the reach of molecular simulation. The WExplore enhanced sampling method is well-suited to build these maps, as it is designed to broadly explore… Show more

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Cited by 11 publications
(19 citation statements)
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“…Distance Metric. Here we will use a common distance metric for ligand release processes: the root mean squared distance of the ligand atoms after alignment to the host binding site [29,30,43]. This captures ligand translation with respect to the binding site, and (for systems with more complicated ligands) captures ligand rotation as well as internal degrees of freedom.…”
Section: Preparing the Simulationmentioning
confidence: 99%
“…Distance Metric. Here we will use a common distance metric for ligand release processes: the root mean squared distance of the ligand atoms after alignment to the host binding site [29,30,43]. This captures ligand translation with respect to the binding site, and (for systems with more complicated ligands) captures ligand rotation as well as internal degrees of freedom.…”
Section: Preparing the Simulationmentioning
confidence: 99%
“…The ligand in the SF simulation can be seen to move around to multiple other locations on the surface of the protein before ultimately unbinding. Wepy is a useful and exible implementation of advanced weighted ensemble simulations with a growing number of applications [33,46,49,69]. In our experience wepy has been particularly useful in three major ways.…”
Section: Unbinding Events and Trajectoriesmentioning
confidence: 99%
“…Approaches involving CVs are typically limited to low-dimensional representations (often ≤ 3), while WE-based resamplers like WExplore [45] and REVO [46] perform well in high-dimensional spaces. High-dimensional adaptive resampling algorithms have been especially successful in obtaining preliminary rare event simulations for systems with waiting times well beyond what is typical [33,41,[47][48][49]. Notably, WExplore simulations produced unbinding trajectories of a drug ligand (TPPU) from its target (soluble epoxide hydrolase) that has an experimentally determined mean rst passage time of 11 min, using less than 1 µs of simulation; a speed-up of 10 9 -fold [48].…”
Section: Introductionmentioning
confidence: 99%
“…However in the MSM, the Markovian assumption (that transitions are independent of history) is only guaranteed to be fulfilled in the limit of long τ , in practice tens of nanoseconds. 8 It can also be sensitive to clustering parameters and feature selection 9 and typically requires a very long simulation time.…”
Section: Introductionmentioning
confidence: 99%
“…WExplore has been applied to sample a variety of rare events, including ligand (un)binding pathways, 9,[12][13][14] protein folding pathways 11 and RNA conformational changes. 15 Despite this success, WExplore is limited by three main issues related to the definitions of these hierarchical regions.…”
Section: Introductionmentioning
confidence: 99%