000841293 001__ 841293
000841293 005__ 20210129232009.0
000841293 0247_ $$2doi$$a10.1002/wcms.1320
000841293 0247_ $$2ISSN$$a1759-0876
000841293 0247_ $$2ISSN$$a1759-0884
000841293 0247_ $$2WOS$$aWOS:000419101000002
000841293 0247_ $$2altmetric$$aaltmetric:21039085
000841293 037__ $$aFZJ-2017-08384
000841293 082__ $$a004
000841293 1001_ $$0P:(DE-Juel1)167585$$aDe Vivo, Marco$$b0$$eCorresponding author$$ufzj
000841293 245__ $$aRecent advances in dynamic docking for drug discovery
000841293 260__ $$aMalden, MA$$bWiley-Blackwell$$c2017
000841293 3367_ $$2DRIVER$$aarticle
000841293 3367_ $$2DataCite$$aOutput Types/Journal article
000841293 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1513233015_28644
000841293 3367_ $$2BibTeX$$aARTICLE
000841293 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000841293 3367_ $$00$$2EndNote$$aJournal Article
000841293 520__ $$aMolecular docking allows the evaluation of ligand-target complementarity. This is the crucial first step in small-molecule drug discovery. Over the last decade, increasing computer power and more efficient molecular dynamics (MD) software have prompted the use of MD for molecular docking. The resulting dynamic docking offers major improvements by (1) taking full account of the structural flexibility of the drug-target system and (2) allowing the computation of the free energy and kinetics associated with drug binding. Here, we examine the recent advances in dynamic docking, while also considering the challenges and limitations that this powerful approach must overcome to impact fast-paced drug discovery.
000841293 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000841293 588__ $$aDataset connected to CrossRef
000841293 7001_ $$0P:(DE-HGF)0$$aCavalli, Andrea$$b1$$eCorresponding author
000841293 773__ $$0PERI:(DE-600)2599565-0$$a10.1002/wcms.1320$$gVol. 7, no. 6, p. e1320 -$$n6$$pe1320 -$$tWiley interdisciplinary reviews / Computational Molecular Science$$v7$$x1759-0876$$y2017
000841293 909CO $$ooai:juser.fz-juelich.de:841293$$pVDB
000841293 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)167585$$aForschungszentrum Jülich$$b0$$kFZJ
000841293 9131_ $$0G:(DE-HGF)POF3-574$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vTheory, modelling and simulation$$x0
000841293 9141_ $$y2017
000841293 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bWIRES COMPUT MOL SCI : 2015
000841293 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000841293 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000841293 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000841293 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000841293 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000841293 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences
000841293 915__ $$0StatID:(DE-HGF)9910$$2StatID$$aIF >= 10$$bWIRES COMPUT MOL SCI : 2015
000841293 920__ $$lyes
000841293 9201_ $$0I:(DE-Juel1)IAS-5-20120330$$kIAS-5$$lComputational Biomedicine$$x0
000841293 9201_ $$0I:(DE-Juel1)INM-9-20140121$$kINM-9$$lComputational Biomedicine$$x1
000841293 980__ $$ajournal
000841293 980__ $$aVDB
000841293 980__ $$aI:(DE-Juel1)IAS-5-20120330
000841293 980__ $$aI:(DE-Juel1)INM-9-20140121
000841293 980__ $$aUNRESTRICTED