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Generative Topographic Mapping of the Docking Conformational Space

Following previous efforts to render the Conformational Space (CS) of flexible compounds by Generative Topographic Mapping (GTM), this polyvalent mapping technique is here adapted to the docking problem. Contact fingerprints (CF) characterize ligands from the perspective of the binding site by monit...

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Autores principales: Horvath, Dragos, Marcou, Gilles, Varnek, Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631714/
https://www.ncbi.nlm.nih.gov/pubmed/31216756
http://dx.doi.org/10.3390/molecules24122269
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author Horvath, Dragos
Marcou, Gilles
Varnek, Alexandre
author_facet Horvath, Dragos
Marcou, Gilles
Varnek, Alexandre
author_sort Horvath, Dragos
collection PubMed
description Following previous efforts to render the Conformational Space (CS) of flexible compounds by Generative Topographic Mapping (GTM), this polyvalent mapping technique is here adapted to the docking problem. Contact fingerprints (CF) characterize ligands from the perspective of the binding site by monitoring protein atoms that are “touched” by those of the ligand. A “Contact” (CF) map was built by GTM-driven dimensionality reduction of the CF vector space. Alternatively, a “Hybrid” (Hy) map used a composite descriptor of CFs concatenated with ligand fragment descriptors. These maps indirectly represent the active site and integrate the binding information of multiple ligands. The concept is illustrated by a docking study into the ATP-binding site of CDK2, using the S4MPLE program to generate thousands of poses for each ligand. Both maps were challenged to (1) Discriminate native from non-native ligand poses, e.g., create RMSD-landscapes “colored” by the conformer ensemble of ligands of known binding modes in order to highlight “native” map zones (poses with RMSD to PDB structures < 2Å). Then, projection of poses of other ligands on such landscapes might serve to predict those falling in native zones as being well-docked. (2) Distinguish ligands–characterized by their ensemble of conformers–by their potency, e.g., testing the hypotheses whether zones privileged by potent binders are clearly separated from the ones preferred by decoys on the maps. Hybrid maps were better in both challenges and outperformed the classical energy and individual contact satisfaction scores in discriminating ligands by potency. Moreover, the intuitive visualization and analysis of docking CS may, as already mentioned, have several applications–from highlighting of key contacts to monitoring docking calculation convergence.
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spelling pubmed-66317142019-08-19 Generative Topographic Mapping of the Docking Conformational Space Horvath, Dragos Marcou, Gilles Varnek, Alexandre Molecules Article Following previous efforts to render the Conformational Space (CS) of flexible compounds by Generative Topographic Mapping (GTM), this polyvalent mapping technique is here adapted to the docking problem. Contact fingerprints (CF) characterize ligands from the perspective of the binding site by monitoring protein atoms that are “touched” by those of the ligand. A “Contact” (CF) map was built by GTM-driven dimensionality reduction of the CF vector space. Alternatively, a “Hybrid” (Hy) map used a composite descriptor of CFs concatenated with ligand fragment descriptors. These maps indirectly represent the active site and integrate the binding information of multiple ligands. The concept is illustrated by a docking study into the ATP-binding site of CDK2, using the S4MPLE program to generate thousands of poses for each ligand. Both maps were challenged to (1) Discriminate native from non-native ligand poses, e.g., create RMSD-landscapes “colored” by the conformer ensemble of ligands of known binding modes in order to highlight “native” map zones (poses with RMSD to PDB structures < 2Å). Then, projection of poses of other ligands on such landscapes might serve to predict those falling in native zones as being well-docked. (2) Distinguish ligands–characterized by their ensemble of conformers–by their potency, e.g., testing the hypotheses whether zones privileged by potent binders are clearly separated from the ones preferred by decoys on the maps. Hybrid maps were better in both challenges and outperformed the classical energy and individual contact satisfaction scores in discriminating ligands by potency. Moreover, the intuitive visualization and analysis of docking CS may, as already mentioned, have several applications–from highlighting of key contacts to monitoring docking calculation convergence. MDPI 2019-06-18 /pmc/articles/PMC6631714/ /pubmed/31216756 http://dx.doi.org/10.3390/molecules24122269 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Horvath, Dragos
Marcou, Gilles
Varnek, Alexandre
Generative Topographic Mapping of the Docking Conformational Space
title Generative Topographic Mapping of the Docking Conformational Space
title_full Generative Topographic Mapping of the Docking Conformational Space
title_fullStr Generative Topographic Mapping of the Docking Conformational Space
title_full_unstemmed Generative Topographic Mapping of the Docking Conformational Space
title_short Generative Topographic Mapping of the Docking Conformational Space
title_sort generative topographic mapping of the docking conformational space
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631714/
https://www.ncbi.nlm.nih.gov/pubmed/31216756
http://dx.doi.org/10.3390/molecules24122269
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