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dc.contributor.authorLi, Xiuming
dc.contributor.authorYan, Xin
dc.contributor.authorYang, Yuedong
dc.contributor.authorGu, Qiong
dc.contributor.authorZhou, Huihao
dc.contributor.authorDu, Yunfei
dc.contributor.authorLu, Yutong
dc.contributor.authorLiao, Jielou
dc.contributor.authorXu, Jun
dc.date.accessioned2019-10-16T23:30:37Z
dc.date.available2019-10-16T23:30:37Z
dc.date.issued2019
dc.identifier.issn2046-2069
dc.identifier.doi10.1039/c8ra08915a
dc.identifier.urihttp://hdl.handle.net/10072/388450
dc.description.abstractSimilar structures having similar activities is a dogma for identifying new functional molecules. However, it is not rare that a minor structural change can cause a significant activity change. Methods to measure the molecular similarity can be classified into two categories of overall three-dimensional shape based methods and local substructure based methods. The former states the relation between overall similarity and activity, and is represented by conventional similarity algorithms. The latter states the relation between local substructure and activity, and is represented by conventional substructure match algorithms. Practically, the similarity of two molecules with similar activity depends on the contributions from both overall similarity and local substructure match. We report a new tool termed as a local-weighted structural alignment (LSA) tool for pharmaceutical virtual screening, which computes the similarity of two molecular structures by considering the contributions of both overall similarity and local substructure match. LSA consists of three steps: (1) mapping a common substructure between two molecular topological structures; (2) superimposing two three-dimensional molecular structures with substructure focus; (3) computing the similarity score based on superimposing. LSA has been validated with 102 testing compound libraries from DUD-E collection with the average AUC (the area under a receiver-operating characteristic curve) value of 0.82 and an average EF1% (the enrichment factor at top 1%) of 27.0, which had consistently better performance than conventional approaches. LSA is implemented in C++ and run on Linux and Windows systems.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherRoyal Society of Chemistry
dc.relation.ispartofpagefrom3912
dc.relation.ispartofpageto3917
dc.relation.ispartofissue7
dc.relation.ispartofjournalRSC Advances
dc.relation.ispartofvolume9
dc.subject.fieldofresearchChemical sciences
dc.subject.fieldofresearchcode34
dc.subject.keywordsScience & Technology
dc.subject.keywordsPhysical Sciences
dc.subject.keywordsChemistry, Multidisciplinary
dc.subject.keywordsSEARCH
dc.titleLSA: a local-weighted structural alignment tool for pharmaceutical virtual screening
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationLi, X; Yan, X; Yang, Y; Gu, Q; Zhou, H; Du, Y; Lu, Y; Liao, J; Xu, J, LSA: a local-weighted structural alignment tool for pharmaceutical virtual screening, RSC Advances, 2019, 9 (7), pp. 3912-3917
dcterms.licensehttp://creativecommons.org/licenses/by-nc/3.0/
dc.date.updated2019-10-16T23:27:04Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2019. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) License, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorYang, Yuedong


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