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sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces

sensaas is a tool developed for aligning and comparing molecular shapes and sub‐shapes. Alignment is obtained by registration of 3D point‐based representations of the van der Waals surface. The method uses local properties of the shape to identify the correspondence relationships between two point c...

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Autores principales: Douguet, Dominique, Payan, Frédéric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507133/
https://www.ncbi.nlm.nih.gov/pubmed/32573978
http://dx.doi.org/10.1002/minf.202000081
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author Douguet, Dominique
Payan, Frédéric
author_facet Douguet, Dominique
Payan, Frédéric
author_sort Douguet, Dominique
collection PubMed
description sensaas is a tool developed for aligning and comparing molecular shapes and sub‐shapes. Alignment is obtained by registration of 3D point‐based representations of the van der Waals surface. The method uses local properties of the shape to identify the correspondence relationships between two point clouds containing up to several thousand colored (labeled) points. Our rigid‐body superimposition method follows a two‐stage approach. An initial alignment is obtained by matching pose‐invariant local 3D descriptors, called FPFH, of the input point clouds. This stage provides a global superimposition of the molecular surfaces, without any knowledge of their initial pose in 3D space. This alignment is then refined by optimizing the matching of colored points. In our study, each point is colored according to its closest atom, which itself belongs to a user defined physico‐chemical class. Finally, sensaas provides an alignment and evaluates the molecular similarity by using Tversky coefficients. To assess the efficiency of this approach, we tested its ability to reproduce the superimposition of X‐ray structures of the benchmarking AstraZeneca (AZ) data set and, compared its results with those generated by the two shape‐alignment approaches shaep and shafts. We also illustrated submatching properties of our method with respect to few substructures and bioisosteric fragments. The code is available upon request from the authors (demo version at https://chemoinfo.ipmc.cnrs.fr/SENSAAS).
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spelling pubmed-75071332020-09-28 sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces Douguet, Dominique Payan, Frédéric Mol Inform Full Papers sensaas is a tool developed for aligning and comparing molecular shapes and sub‐shapes. Alignment is obtained by registration of 3D point‐based representations of the van der Waals surface. The method uses local properties of the shape to identify the correspondence relationships between two point clouds containing up to several thousand colored (labeled) points. Our rigid‐body superimposition method follows a two‐stage approach. An initial alignment is obtained by matching pose‐invariant local 3D descriptors, called FPFH, of the input point clouds. This stage provides a global superimposition of the molecular surfaces, without any knowledge of their initial pose in 3D space. This alignment is then refined by optimizing the matching of colored points. In our study, each point is colored according to its closest atom, which itself belongs to a user defined physico‐chemical class. Finally, sensaas provides an alignment and evaluates the molecular similarity by using Tversky coefficients. To assess the efficiency of this approach, we tested its ability to reproduce the superimposition of X‐ray structures of the benchmarking AstraZeneca (AZ) data set and, compared its results with those generated by the two shape‐alignment approaches shaep and shafts. We also illustrated submatching properties of our method with respect to few substructures and bioisosteric fragments. The code is available upon request from the authors (demo version at https://chemoinfo.ipmc.cnrs.fr/SENSAAS). John Wiley and Sons Inc. 2020-06-23 2020-08 /pmc/articles/PMC7507133/ /pubmed/32573978 http://dx.doi.org/10.1002/minf.202000081 Text en © 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full Papers
Douguet, Dominique
Payan, Frédéric
sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces
title sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces
title_full sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces
title_fullStr sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces
title_full_unstemmed sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces
title_short sensaas: Shape‐based Alignment by Registration of Colored Point‐based Surfaces
title_sort sensaas: shape‐based alignment by registration of colored point‐based surfaces
topic Full Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507133/
https://www.ncbi.nlm.nih.gov/pubmed/32573978
http://dx.doi.org/10.1002/minf.202000081
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