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Predictive cartography of metal binders using generative topographic mapping

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dc.contributor.author Baskin I.
dc.contributor.author Solov’ev V.
dc.contributor.author Bagatur’yants A.
dc.contributor.author Varnek A.
dc.date.accessioned 2018-04-05T07:09:25Z
dc.date.available 2018-04-05T07:09:25Z
dc.date.issued 2017
dc.identifier.issn 0920-654X
dc.identifier.uri http://dspace.kpfu.ru/xmlui/handle/net/129722
dc.description.abstract © 2017, Springer International Publishing AG. Generative topographic mapping (GTM) approach is used to visualize the chemical space of organic molecules (L) with respect to binding a wide range of 41 different metal cations (M) and also to b uild predictive models for stability constants (logK) of 1:1 (M:L) complexes using “density maps,” “activity landscapes,” and “selectivity landscapes” techniques. A two-dimensional map describing the entire set of 2962 metal binders reveals the selectivity and promiscuity zones with respect to individual metals or groups of metals with similar chemical properties (lanthanides, transition metals, etc). The GTM-based global (for entire set) and local (for selected subsets) models demonstrate a good predictive performance in the cross-validation procedure. It is also shown that the data likelihood could be used as a definition of the applicability domain of GTM-based models. Thus, the GTM approach represents an efficient tool for the predictive cartography of metal binders, which can both visualize their chemical space and predict the affinity profile of metals for new ligands.
dc.relation.ispartofseries Journal of Computer-Aided Molecular Design
dc.subject Activity landscapes
dc.subject Cartography of chemical space
dc.subject Generative topographic mapping
dc.subject Metal binding
dc.title Predictive cartography of metal binders using generative topographic mapping
dc.type Article
dc.relation.ispartofseries-issue 8
dc.relation.ispartofseries-volume 31
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 701
dc.source.id SCOPUS0920654X-2017-31-8-SID85021943750


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