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Performance evaluation of flexible macrocycle docking in AutoDock
Macrocycles represent an important class of ligands, both in natural products and designed drugs. In drug design, macrocyclizations can impart specific ligand conformations and contribute to passive permeation by encouraging intramolecular H-bonds. AutoDock-GPU and Vina can model macrocyclic ligands...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392634/ https://www.ncbi.nlm.nih.gov/pubmed/37529284 http://dx.doi.org/10.1017/qrd.2022.18 |
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author | Holcomb, Matthew Santos-Martins, Diogo Tillack, Andreas F. Forli, Stefano |
author_facet | Holcomb, Matthew Santos-Martins, Diogo Tillack, Andreas F. Forli, Stefano |
author_sort | Holcomb, Matthew |
collection | PubMed |
description | Macrocycles represent an important class of ligands, both in natural products and designed drugs. In drug design, macrocyclizations can impart specific ligand conformations and contribute to passive permeation by encouraging intramolecular H-bonds. AutoDock-GPU and Vina can model macrocyclic ligands flexibly, without requiring the enumeration of macrocyclic conformers before docking. Here, we characterize the performance of the method for handling macrocyclic compounds, which is implemented and the default behaviour for ligand preparation with our ligand preparation pipeline, Meeko. A pseudoatom is used to encode bond geometry and produce an anisotropic closure force for macrocyclic rings. This method is evaluated on a diverse set of small molecule and peptide macrocycles, ranging from 7- to 33-membered rings, showing little accuracy loss compared to rigid redocking of the X-ray macrocycle conformers. This suggests that for conformationally flexible macrocycles with unknown binding modes, this method can be effectively used to predict the macrocycle conformation. |
format | Online Article Text |
id | pubmed-10392634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103926342023-08-01 Performance evaluation of flexible macrocycle docking in AutoDock Holcomb, Matthew Santos-Martins, Diogo Tillack, Andreas F. Forli, Stefano QRB Discov Research Article Macrocycles represent an important class of ligands, both in natural products and designed drugs. In drug design, macrocyclizations can impart specific ligand conformations and contribute to passive permeation by encouraging intramolecular H-bonds. AutoDock-GPU and Vina can model macrocyclic ligands flexibly, without requiring the enumeration of macrocyclic conformers before docking. Here, we characterize the performance of the method for handling macrocyclic compounds, which is implemented and the default behaviour for ligand preparation with our ligand preparation pipeline, Meeko. A pseudoatom is used to encode bond geometry and produce an anisotropic closure force for macrocyclic rings. This method is evaluated on a diverse set of small molecule and peptide macrocycles, ranging from 7- to 33-membered rings, showing little accuracy loss compared to rigid redocking of the X-ray macrocycle conformers. This suggests that for conformationally flexible macrocycles with unknown binding modes, this method can be effectively used to predict the macrocycle conformation. Cambridge University Press 2022-10-17 /pmc/articles/PMC10392634/ /pubmed/37529284 http://dx.doi.org/10.1017/qrd.2022.18 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Research Article Holcomb, Matthew Santos-Martins, Diogo Tillack, Andreas F. Forli, Stefano Performance evaluation of flexible macrocycle docking in AutoDock |
title | Performance evaluation of flexible macrocycle docking in AutoDock |
title_full | Performance evaluation of flexible macrocycle docking in AutoDock |
title_fullStr | Performance evaluation of flexible macrocycle docking in AutoDock |
title_full_unstemmed | Performance evaluation of flexible macrocycle docking in AutoDock |
title_short | Performance evaluation of flexible macrocycle docking in AutoDock |
title_sort | performance evaluation of flexible macrocycle docking in autodock |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392634/ https://www.ncbi.nlm.nih.gov/pubmed/37529284 http://dx.doi.org/10.1017/qrd.2022.18 |
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