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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...

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Detalles Bibliográficos
Autores principales: Holcomb, Matthew, Santos-Martins, Diogo, Tillack, Andreas F., Forli, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
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.
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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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