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Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses
Ligand docking at a protein site can be improved by prioritizing poses by similarity to validated binding modes found in the crystal structures of ligand/protein complexes. The interactions formed in the predicted model are searched in each of the reference 3D structures, taken individually. We prop...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6681060/ https://www.ncbi.nlm.nih.gov/pubmed/31323745 http://dx.doi.org/10.3390/molecules24142610 |
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author | Jacquemard, Célien Tran-Nguyen, Viet-Khoa Drwal, Malgorzata N. Rognan, Didier Kellenberger, Esther |
author_facet | Jacquemard, Célien Tran-Nguyen, Viet-Khoa Drwal, Malgorzata N. Rognan, Didier Kellenberger, Esther |
author_sort | Jacquemard, Célien |
collection | PubMed |
description | Ligand docking at a protein site can be improved by prioritizing poses by similarity to validated binding modes found in the crystal structures of ligand/protein complexes. The interactions formed in the predicted model are searched in each of the reference 3D structures, taken individually. We propose to merge the information provided by all references, creating a single representation of all known binding modes. The method is called LID, an acronym for Local Interaction Density. LID was benchmarked in a pose prediction exercise on 19 proteins and 1382 ligands using PLANTS as docking software. It was also tested in a virtual screening challenge on eight proteins, with a dataset of 140,000 compounds from DUD-E and PubChem. LID significantly improved the performance of the docking program in both pose prediction and virtual screening. The gain is comparable to that obtained with a rescoring approach based on the individual comparison of reference binding modes (the GRIM method). Importantly, LID is effective with a small number of references. LID calculation time is negligible compared to the docking time. |
format | Online Article Text |
id | pubmed-6681060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66810602019-08-09 Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses Jacquemard, Célien Tran-Nguyen, Viet-Khoa Drwal, Malgorzata N. Rognan, Didier Kellenberger, Esther Molecules Article Ligand docking at a protein site can be improved by prioritizing poses by similarity to validated binding modes found in the crystal structures of ligand/protein complexes. The interactions formed in the predicted model are searched in each of the reference 3D structures, taken individually. We propose to merge the information provided by all references, creating a single representation of all known binding modes. The method is called LID, an acronym for Local Interaction Density. LID was benchmarked in a pose prediction exercise on 19 proteins and 1382 ligands using PLANTS as docking software. It was also tested in a virtual screening challenge on eight proteins, with a dataset of 140,000 compounds from DUD-E and PubChem. LID significantly improved the performance of the docking program in both pose prediction and virtual screening. The gain is comparable to that obtained with a rescoring approach based on the individual comparison of reference binding modes (the GRIM method). Importantly, LID is effective with a small number of references. LID calculation time is negligible compared to the docking time. MDPI 2019-07-18 /pmc/articles/PMC6681060/ /pubmed/31323745 http://dx.doi.org/10.3390/molecules24142610 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 Jacquemard, Célien Tran-Nguyen, Viet-Khoa Drwal, Malgorzata N. Rognan, Didier Kellenberger, Esther Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses |
title | Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses |
title_full | Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses |
title_fullStr | Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses |
title_full_unstemmed | Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses |
title_short | Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses |
title_sort | local interaction density (lid), a fast and efficient tool to prioritize docking poses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6681060/ https://www.ncbi.nlm.nih.gov/pubmed/31323745 http://dx.doi.org/10.3390/molecules24142610 |
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