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Binding mode information improves fragment docking

Docking is commonly used in drug discovery to predict how ligand binds to protein target. Best programs are generally able to generate a correct solution, yet often fail to identify it. In the case of drug-like molecules, the correct and incorrect poses can be sorted by similarity to the crystallogr...

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Autores principales: Jacquemard, Célien, Drwal, Malgorzata N., Desaphy, Jérémy, Kellenberger, Esther
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431075/
https://www.ncbi.nlm.nih.gov/pubmed/30903304
http://dx.doi.org/10.1186/s13321-019-0346-7
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author Jacquemard, Célien
Drwal, Malgorzata N.
Desaphy, Jérémy
Kellenberger, Esther
author_facet Jacquemard, Célien
Drwal, Malgorzata N.
Desaphy, Jérémy
Kellenberger, Esther
author_sort Jacquemard, Célien
collection PubMed
description Docking is commonly used in drug discovery to predict how ligand binds to protein target. Best programs are generally able to generate a correct solution, yet often fail to identify it. In the case of drug-like molecules, the correct and incorrect poses can be sorted by similarity to the crystallographic structure of the protein in complex with reference ligands. Fragments are particularly sensitive to scoring problems because they are weak ligands which form few interactions with protein. In the present study, we assessed the utility of binding mode information in fragment pose prediction. We compared three approaches: interaction fingerprints, 3D-matching of interaction patterns and 3D-matching of shapes. We prepared a test set composed of high-quality structures of the Protein Data Bank. We generated and evaluated the docking poses of 586 fragment/protein complexes. We observed that the best approach is twice as accurate as the native scoring function, and that post-processing is less effective for smaller fragments. Interestingly, fragments and drug-like molecules both proved to be useful references. In the discussion, we suggest the best conditions for a successful pose prediction with the three approaches. [Image: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-019-0346-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-64310752019-04-04 Binding mode information improves fragment docking Jacquemard, Célien Drwal, Malgorzata N. Desaphy, Jérémy Kellenberger, Esther J Cheminform Research Article Docking is commonly used in drug discovery to predict how ligand binds to protein target. Best programs are generally able to generate a correct solution, yet often fail to identify it. In the case of drug-like molecules, the correct and incorrect poses can be sorted by similarity to the crystallographic structure of the protein in complex with reference ligands. Fragments are particularly sensitive to scoring problems because they are weak ligands which form few interactions with protein. In the present study, we assessed the utility of binding mode information in fragment pose prediction. We compared three approaches: interaction fingerprints, 3D-matching of interaction patterns and 3D-matching of shapes. We prepared a test set composed of high-quality structures of the Protein Data Bank. We generated and evaluated the docking poses of 586 fragment/protein complexes. We observed that the best approach is twice as accurate as the native scoring function, and that post-processing is less effective for smaller fragments. Interestingly, fragments and drug-like molecules both proved to be useful references. In the discussion, we suggest the best conditions for a successful pose prediction with the three approaches. [Image: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13321-019-0346-7) contains supplementary material, which is available to authorized users. Springer International Publishing 2019-03-22 /pmc/articles/PMC6431075/ /pubmed/30903304 http://dx.doi.org/10.1186/s13321-019-0346-7 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Jacquemard, Célien
Drwal, Malgorzata N.
Desaphy, Jérémy
Kellenberger, Esther
Binding mode information improves fragment docking
title Binding mode information improves fragment docking
title_full Binding mode information improves fragment docking
title_fullStr Binding mode information improves fragment docking
title_full_unstemmed Binding mode information improves fragment docking
title_short Binding mode information improves fragment docking
title_sort binding mode information improves fragment docking
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6431075/
https://www.ncbi.nlm.nih.gov/pubmed/30903304
http://dx.doi.org/10.1186/s13321-019-0346-7
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