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Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations

[Image: see text] The prediction of ligand efficacy has long been linked to thermodynamic properties such as the equilibrium dissociation constant, which considers both the association and the dissociation rates of a defined protein–ligand complex. In the last 15 years, there has been a paradigm shi...

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Autores principales: Pavan, Matteo, Menin, Silvia, Bassani, Davide, Sturlese, Mattia, Moro, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709921/
https://www.ncbi.nlm.nih.gov/pubmed/36315402
http://dx.doi.org/10.1021/acs.jcim.2c00995
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author Pavan, Matteo
Menin, Silvia
Bassani, Davide
Sturlese, Mattia
Moro, Stefano
author_facet Pavan, Matteo
Menin, Silvia
Bassani, Davide
Sturlese, Mattia
Moro, Stefano
author_sort Pavan, Matteo
collection PubMed
description [Image: see text] The prediction of ligand efficacy has long been linked to thermodynamic properties such as the equilibrium dissociation constant, which considers both the association and the dissociation rates of a defined protein–ligand complex. In the last 15 years, there has been a paradigm shift, with an increased interest in the determination of kinetic properties such as the drug–target residence time since they better correlate with ligand efficacy compared to other parameters. In this article, we present thermal titration molecular dynamics (TTMD), an alternative computational method that combines a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein–ligand interaction fingerprints for the qualitative estimation of protein–ligand-binding stability. The protocol has been applied to four different pharmaceutically relevant test cases, including protein kinase CK1δ, protein kinase CK2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease, on a variety of ligands with different sizes, structures, and experimentally determined affinity values. In all four cases, TTMD was successfully able to distinguish between high-affinity compounds (low nanomolar range) and low-affinity ones (micromolar), proving to be a useful screening tool for the prioritization of compounds in a drug discovery campaign.
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spelling pubmed-97099212022-12-01 Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations Pavan, Matteo Menin, Silvia Bassani, Davide Sturlese, Mattia Moro, Stefano J Chem Inf Model [Image: see text] The prediction of ligand efficacy has long been linked to thermodynamic properties such as the equilibrium dissociation constant, which considers both the association and the dissociation rates of a defined protein–ligand complex. In the last 15 years, there has been a paradigm shift, with an increased interest in the determination of kinetic properties such as the drug–target residence time since they better correlate with ligand efficacy compared to other parameters. In this article, we present thermal titration molecular dynamics (TTMD), an alternative computational method that combines a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein–ligand interaction fingerprints for the qualitative estimation of protein–ligand-binding stability. The protocol has been applied to four different pharmaceutically relevant test cases, including protein kinase CK1δ, protein kinase CK2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease, on a variety of ligands with different sizes, structures, and experimentally determined affinity values. In all four cases, TTMD was successfully able to distinguish between high-affinity compounds (low nanomolar range) and low-affinity ones (micromolar), proving to be a useful screening tool for the prioritization of compounds in a drug discovery campaign. American Chemical Society 2022-10-31 2022-11-28 /pmc/articles/PMC9709921/ /pubmed/36315402 http://dx.doi.org/10.1021/acs.jcim.2c00995 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Pavan, Matteo
Menin, Silvia
Bassani, Davide
Sturlese, Mattia
Moro, Stefano
Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations
title Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations
title_full Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations
title_fullStr Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations
title_full_unstemmed Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations
title_short Qualitative Estimation of Protein–Ligand Complex Stability through Thermal Titration Molecular Dynamics Simulations
title_sort qualitative estimation of protein–ligand complex stability through thermal titration molecular dynamics simulations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709921/
https://www.ncbi.nlm.nih.gov/pubmed/36315402
http://dx.doi.org/10.1021/acs.jcim.2c00995
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