Cargando…

Protein–ligand binding with the coarse-grained Martini model

The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein–ligand binding is an important tool to accomplish this task. Current approaches ty...

Descripción completa

Detalles Bibliográficos
Autores principales: Souza, Paulo C. T., Thallmair, Sebastian, Conflitti, Paolo, Ramírez-Palacios, Carlos, Alessandri, Riccardo, Raniolo, Stefano, Limongelli, Vittorio, Marrink, Siewert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382508/
https://www.ncbi.nlm.nih.gov/pubmed/32709852
http://dx.doi.org/10.1038/s41467-020-17437-5
_version_ 1783563256286150656
author Souza, Paulo C. T.
Thallmair, Sebastian
Conflitti, Paolo
Ramírez-Palacios, Carlos
Alessandri, Riccardo
Raniolo, Stefano
Limongelli, Vittorio
Marrink, Siewert J.
author_facet Souza, Paulo C. T.
Thallmair, Sebastian
Conflitti, Paolo
Ramírez-Palacios, Carlos
Alessandri, Riccardo
Raniolo, Stefano
Limongelli, Vittorio
Marrink, Siewert J.
author_sort Souza, Paulo C. T.
collection PubMed
description The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein–ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein–ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model.
format Online
Article
Text
id pubmed-7382508
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-73825082020-07-28 Protein–ligand binding with the coarse-grained Martini model Souza, Paulo C. T. Thallmair, Sebastian Conflitti, Paolo Ramírez-Palacios, Carlos Alessandri, Riccardo Raniolo, Stefano Limongelli, Vittorio Marrink, Siewert J. Nat Commun Article The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein–ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein–ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model. Nature Publishing Group UK 2020-07-24 /pmc/articles/PMC7382508/ /pubmed/32709852 http://dx.doi.org/10.1038/s41467-020-17437-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Souza, Paulo C. T.
Thallmair, Sebastian
Conflitti, Paolo
Ramírez-Palacios, Carlos
Alessandri, Riccardo
Raniolo, Stefano
Limongelli, Vittorio
Marrink, Siewert J.
Protein–ligand binding with the coarse-grained Martini model
title Protein–ligand binding with the coarse-grained Martini model
title_full Protein–ligand binding with the coarse-grained Martini model
title_fullStr Protein–ligand binding with the coarse-grained Martini model
title_full_unstemmed Protein–ligand binding with the coarse-grained Martini model
title_short Protein–ligand binding with the coarse-grained Martini model
title_sort protein–ligand binding with the coarse-grained martini model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382508/
https://www.ncbi.nlm.nih.gov/pubmed/32709852
http://dx.doi.org/10.1038/s41467-020-17437-5
work_keys_str_mv AT souzapauloct proteinligandbindingwiththecoarsegrainedmartinimodel
AT thallmairsebastian proteinligandbindingwiththecoarsegrainedmartinimodel
AT conflittipaolo proteinligandbindingwiththecoarsegrainedmartinimodel
AT ramirezpalacioscarlos proteinligandbindingwiththecoarsegrainedmartinimodel
AT alessandririccardo proteinligandbindingwiththecoarsegrainedmartinimodel
AT raniolostefano proteinligandbindingwiththecoarsegrainedmartinimodel
AT limongellivittorio proteinligandbindingwiththecoarsegrainedmartinimodel
AT marrinksiewertj proteinligandbindingwiththecoarsegrainedmartinimodel