{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T05:43:13Z","timestamp":1793166193176,"version":"4.5.0"},"reference-count":48,"publisher":"American Chemical Society (ACS)","issue":"3","license":[{"start":{"date-parts":[[2020,1,15]],"date-time":"2020-01-15T00:00:00Z","timestamp":1579046400000},"content-version":"vor","delay-in-days":365,"URL":"https:\/\/pubs.acs.org\/page\/policy\/authorchoice_termsofuse.html"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R01GM127359"],"award-info":[{"award-number":["R01GM127359"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000082","name":"Division of Graduate Education","doi-asserted-by":"publisher","award":["DGE1656518"],"award-info":[{"award-number":["DGE1656518"]}],"id":[{"id":"10.13039\/100000082","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007065","name":"Nvidia","doi-asserted-by":"publisher","award":["NA"],"award-info":[{"award-number":["NA"]}],"id":[{"id":"10.13039\/100007065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,3,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>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\u2015in which one performs multiple rounds of simulation, with the initial conditions of each round based on the results of previous rounds\u2015offer 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\u2013ligand systems typical of those encountered in drug discovery. Moreover, most previous work presupposes knowledge of the ligand\u2019s 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\u2013ligand 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\u2013ligand binding is an example of an exploration\u2013exploitation dilemma. Existing adaptive sampling methods for ligand binding in the absence of a known bound pose vastly favor the broad exploration of protein\u2013ligand space, sometimes failing to sufficiently exploit intermediate states as they are discovered. We suggest potential avenues for future research to address this shortcoming.<\/jats:p>","DOI":"10.1021\/acs.jctc.8b00913","type":"journal-article","created":{"date-parts":[[2019,1,15]],"date-time":"2019-01-15T14:59:31Z","timestamp":1547564371000},"page":"2053-2063","source":"Crossref","is-referenced-by-count":62,"title":["How Effectively Can Adaptive Sampling Methods Capture\nSpontaneous Ligand Binding?"],"prefix":"10.1021","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6781-7101","authenticated-orcid":true,"given":"Robin M.","family":"Betz","sequence":"first","affiliation":[{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ron O.","family":"Dror","sequence":"additional","affiliation":[{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]},{"name":"Stanford University , , , ,","place":["Stanford, California, United States, 94305"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2019,1,15]]},"reference":[{"key":"2026090303042064700_cit1","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1016\/j.drudis.2013.02.007","article-title":"Molecular determinants\nof drug-receptor binding kinetics","volume":"18","author":"Pan","year":"2013","journal-title":"Drug Discovery\nToday"},{"key":"2026090303042064700_cit2","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1016\/j.drudis.2017.02.002","article-title":"Kinetics for Drug Discovery: an industry-driven effort\nto target drug residence time","volume":"22","author":"Schuetz","year":"2017","journal-title":"Drug Discovery\nToday"},{"key":"2026090303042064700_cit3","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.sbi.2009.03.004","article-title":"Long-timescale molecular\ndynamics simulations of protein structure and function","volume":"19","author":"Klepeis","year":"2009","journal-title":"Curr. 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