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How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?

[Image: see text] Molecular dynamics (MD) simulations that capture the spontaneous binding of drugs and other ligands to their target proteins can reveal a great deal of useful information, but most drug-like ligands bind on time scales longer than those accessible to individual MD simulations. Adap...

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Autores principales: Betz, Robin M., Dror, Ron O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2019
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795214/
https://www.ncbi.nlm.nih.gov/pubmed/30645108
http://dx.doi.org/10.1021/acs.jctc.8b00913
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author Betz, Robin M.
Dror, Ron O.
author_facet Betz, Robin M.
Dror, Ron O.
author_sort Betz, Robin M.
collection PubMed
description [Image: see text] Molecular dynamics (MD) simulations that capture the spontaneous binding of drugs and other ligands to their target proteins can reveal a great deal of useful information, but most drug-like ligands bind on time scales longer than those accessible to individual MD simulations. Adaptive sampling methods―in which one performs multiple rounds of simulation, with the initial conditions of each round based on the results of previous rounds―offer a promising potential solution to this problem. No comprehensive analysis of the performance gains from adaptive sampling is available for ligand binding, however, particularly for protein–ligand systems typical of those encountered in drug discovery. Moreover, most previous work presupposes knowledge of the ligand’s bound pose. Here we outline existing methods for adaptive sampling of the ligand-binding process and introduce several improvements, with a focus on methods that do not require prior knowledge of the binding site or bound pose. We then evaluate these methods by comparing them to traditional, long MD simulations for realistic protein–ligand systems. We find that adaptive sampling simulations typically fail to reach the bound pose more efficiently than traditional MD. However, adaptive sampling identifies multiple potential binding sites more efficiently than traditional MD and also provides better characterization of binding pathways. We explain these results by showing that protein–ligand binding is an example of an exploration–exploitation dilemma. Existing adaptive sampling methods for ligand binding in the absence of a known bound pose vastly favor the broad exploration of protein–ligand space, sometimes failing to sufficiently exploit intermediate states as they are discovered. We suggest potential avenues for future research to address this shortcoming.
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spelling pubmed-67952142020-01-15 How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding? Betz, Robin M. Dror, Ron O. J Chem Theory Comput [Image: see text] Molecular dynamics (MD) simulations that capture the spontaneous binding of drugs and other ligands to their target proteins can reveal a great deal of useful information, but most drug-like ligands bind on time scales longer than those accessible to individual MD simulations. Adaptive sampling methods―in which one performs multiple rounds of simulation, with the initial conditions of each round based on the results of previous rounds―offer a promising potential solution to this problem. No comprehensive analysis of the performance gains from adaptive sampling is available for ligand binding, however, particularly for protein–ligand systems typical of those encountered in drug discovery. Moreover, most previous work presupposes knowledge of the ligand’s bound pose. Here we outline existing methods for adaptive sampling of the ligand-binding process and introduce several improvements, with a focus on methods that do not require prior knowledge of the binding site or bound pose. We then evaluate these methods by comparing them to traditional, long MD simulations for realistic protein–ligand systems. We find that adaptive sampling simulations typically fail to reach the bound pose more efficiently than traditional MD. However, adaptive sampling identifies multiple potential binding sites more efficiently than traditional MD and also provides better characterization of binding pathways. We explain these results by showing that protein–ligand binding is an example of an exploration–exploitation dilemma. Existing adaptive sampling methods for ligand binding in the absence of a known bound pose vastly favor the broad exploration of protein–ligand space, sometimes failing to sufficiently exploit intermediate states as they are discovered. We suggest potential avenues for future research to address this shortcoming. American Chemical Society 2019-01-15 2019-03-12 /pmc/articles/PMC6795214/ /pubmed/30645108 http://dx.doi.org/10.1021/acs.jctc.8b00913 Text en Copyright © 2019 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Betz, Robin M.
Dror, Ron O.
How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
title How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
title_full How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
title_fullStr How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
title_full_unstemmed How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
title_short How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
title_sort how effectively can adaptive sampling methods capture spontaneous ligand binding?
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795214/
https://www.ncbi.nlm.nih.gov/pubmed/30645108
http://dx.doi.org/10.1021/acs.jctc.8b00913
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