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Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing

[Image: see text] Small-molecule docking remains one of the most valuable computational techniques for the structure prediction of protein–small-molecule complexes. It allows us to study the interactions between compounds and the protein receptors they target at atomic detail in a timely and efficie...

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Autores principales: Koukos, Panagiotis I., Réau, Manon, Bonvin, Alexandre M. J. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479858/
https://www.ncbi.nlm.nih.gov/pubmed/34436890
http://dx.doi.org/10.1021/acs.jcim.1c00796
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author Koukos, Panagiotis I.
Réau, Manon
Bonvin, Alexandre M. J. J.
author_facet Koukos, Panagiotis I.
Réau, Manon
Bonvin, Alexandre M. J. J.
author_sort Koukos, Panagiotis I.
collection PubMed
description [Image: see text] Small-molecule docking remains one of the most valuable computational techniques for the structure prediction of protein–small-molecule complexes. It allows us to study the interactions between compounds and the protein receptors they target at atomic detail in a timely and efficient manner. Here, we present a new protocol in HADDOCK (High Ambiguity Driven DOCKing), our integrative modeling platform, which incorporates homology information for both receptor and compounds. It makes use of HADDOCK’s unique ability to integrate information in the simulation to drive it toward conformations, which agree with the provided data. The focal point is the use of shape restraints derived from homologous compounds bound to the target receptors. We have developed two protocols: in the first, the shape is composed of dummy atom beads based on the position of the heavy atoms of the homologous template compound, whereas in the second, the shape is additionally annotated with pharmacophore data for some or all beads. For both protocols, ambiguous distance restraints are subsequently defined between those beads and the heavy atoms of the ligand to be docked. We have benchmarked the performance of these protocols with a fully unbound version of the widely used DUD-E (Database of Useful Decoys-Enhanced) dataset. In this unbound docking scenario, our template/shape-based docking protocol reaches an overall success rate of 81% when a reliable template can be identified (which was the case for 99 out of 102 complexes in the DUD-E dataset), which is close to the best results reported for bound docking on the DUD-E dataset.
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spelling pubmed-84798582021-09-30 Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing Koukos, Panagiotis I. Réau, Manon Bonvin, Alexandre M. J. J. J Chem Inf Model [Image: see text] Small-molecule docking remains one of the most valuable computational techniques for the structure prediction of protein–small-molecule complexes. It allows us to study the interactions between compounds and the protein receptors they target at atomic detail in a timely and efficient manner. Here, we present a new protocol in HADDOCK (High Ambiguity Driven DOCKing), our integrative modeling platform, which incorporates homology information for both receptor and compounds. It makes use of HADDOCK’s unique ability to integrate information in the simulation to drive it toward conformations, which agree with the provided data. The focal point is the use of shape restraints derived from homologous compounds bound to the target receptors. We have developed two protocols: in the first, the shape is composed of dummy atom beads based on the position of the heavy atoms of the homologous template compound, whereas in the second, the shape is additionally annotated with pharmacophore data for some or all beads. For both protocols, ambiguous distance restraints are subsequently defined between those beads and the heavy atoms of the ligand to be docked. We have benchmarked the performance of these protocols with a fully unbound version of the widely used DUD-E (Database of Useful Decoys-Enhanced) dataset. In this unbound docking scenario, our template/shape-based docking protocol reaches an overall success rate of 81% when a reliable template can be identified (which was the case for 99 out of 102 complexes in the DUD-E dataset), which is close to the best results reported for bound docking on the DUD-E dataset. American Chemical Society 2021-08-26 2021-09-27 /pmc/articles/PMC8479858/ /pubmed/34436890 http://dx.doi.org/10.1021/acs.jcim.1c00796 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Koukos, Panagiotis I.
Réau, Manon
Bonvin, Alexandre M. J. J.
Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
title Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
title_full Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
title_fullStr Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
title_full_unstemmed Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
title_short Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing
title_sort shape-restrained modeling of protein–small-molecule complexes with high ambiguity driven docking
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479858/
https://www.ncbi.nlm.nih.gov/pubmed/34436890
http://dx.doi.org/10.1021/acs.jcim.1c00796
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