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dc.contributor.authorSridhar, Akshay
dc.contributor.authorRoss, Gregory A
dc.contributor.authorBiggin, Philip C
dc.date.accessioned2018-07-19T08:29:58Z
dc.date.available2018-07-19T08:29:58Z
dc.date.issued2018-02-24
dc.identifier.issn1932-6203
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/278241
dc.description.abstractWater is often found to mediate interactions between a ligand and a protein. It can play a significant role in orientating the ligand within a binding pocket and contribute to the free energy of binding. It would thus be extremely useful to be able to accurately predict the position and orientation of water molecules within a binding pocket. Recently, we developed the WaterDock protocol that was able to predict 97% of the water molecules in a test set. However, this approach generated false positives at a rate of over 20% in most cases and whilst this might be acceptable for some applications, in high throughput scenarios this is not desirable. Here we tackle this problem via the inclusion of knowledge regarding the solvation structure of ligand functional groups. We call this new protocol WaterDock2 and demonstrate that this protocol maintains a similar true positive rate to the original implementation but is capable of reducing the false-positive rate by over 50%. To improve the usability of the method, we have also developed a plugin for the popular graphics program PyMOL. The plugin also contains an implementation of the original WaterDock.
dc.description.sponsorshipGAR is supported by the Memorial Sloan Kettering Cancer Center, NIH grant P30 CA008748.
dc.languageeng
dc.publisherPLOS
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectBinding Sites
dc.subjectLigands
dc.subjectProtein Binding
dc.subjectProtein Conformation
dc.subjectProteins
dc.subjectSoftware
dc.subjectWater
dc.titleWaterdock 2.0: Water placement prediction for Holo-structures with a pymol plugin.
dc.typeArticle
prism.endingPagee0172743
prism.issueIdentifier2
prism.publicationDate2018
prism.publicationNamePLoS One
prism.startingPagee0172743
prism.volume12
dc.identifier.doi10.17863/CAM.23231
dcterms.dateAccepted2017-02-08
rioxxterms.versionofrecord10.1371/journal.pone.0172743
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.licenseref.startdate2018-02-24
dc.identifier.eissn1932-6203
dc.publisher.urlhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0172743#abstract0
rioxxterms.typeJournal Article/Review
cam.issuedOnline2017-02-24
dc.identifier.urlhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0172743#abstract0


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International