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Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics
Macrocycles are attractive structures for drug development due to their favorable structural features, potential in binding to targets with flat featureless surfaces, and their ability to disrupt protein–protein interactions. Moreover, large novel highly diverse libraries of low-molecular-weight mac...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438215/ https://www.ncbi.nlm.nih.gov/pubmed/34532343 http://dx.doi.org/10.3389/fmolb.2021.707661 |
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author | Hassankalhori, Mahdi Bolcato, Giovanni Bissaro, Maicol Sturlese, Mattia Moro, Stefano |
author_facet | Hassankalhori, Mahdi Bolcato, Giovanni Bissaro, Maicol Sturlese, Mattia Moro, Stefano |
author_sort | Hassankalhori, Mahdi |
collection | PubMed |
description | Macrocycles are attractive structures for drug development due to their favorable structural features, potential in binding to targets with flat featureless surfaces, and their ability to disrupt protein–protein interactions. Moreover, large novel highly diverse libraries of low-molecular-weight macrocycles with therapeutically favorable characteristics have been recently established. Considering the mentioned facts, having a validated, fast, and accurate computational protocol for studying the molecular recognition and binding mode of this interesting new class of macrocyclic peptides deemed to be helpful as well as insightful in the quest of accelerating drug discovery. To that end, the ability of the in-house supervised molecular dynamics protocol called SuMD in the reproduction of the X-ray crystallography final binding state of a macrocyclic non-canonical tetrapeptide—from a novel library of 8,988 sub-kilodalton macrocyclic peptides—in the thrombin active site was successfully validated. A comparable binding mode with the minimum root-mean-square deviation (RMSD) of 1.4 Å at simulation time point 71.6 ns was achieved. This method validation study extended the application domain of the SuMD sampling method for computationally cheap, fast but accurate, and insightful macrocycle–protein molecular recognition studies. |
format | Online Article Text |
id | pubmed-8438215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84382152021-09-15 Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics Hassankalhori, Mahdi Bolcato, Giovanni Bissaro, Maicol Sturlese, Mattia Moro, Stefano Front Mol Biosci Molecular Biosciences Macrocycles are attractive structures for drug development due to their favorable structural features, potential in binding to targets with flat featureless surfaces, and their ability to disrupt protein–protein interactions. Moreover, large novel highly diverse libraries of low-molecular-weight macrocycles with therapeutically favorable characteristics have been recently established. Considering the mentioned facts, having a validated, fast, and accurate computational protocol for studying the molecular recognition and binding mode of this interesting new class of macrocyclic peptides deemed to be helpful as well as insightful in the quest of accelerating drug discovery. To that end, the ability of the in-house supervised molecular dynamics protocol called SuMD in the reproduction of the X-ray crystallography final binding state of a macrocyclic non-canonical tetrapeptide—from a novel library of 8,988 sub-kilodalton macrocyclic peptides—in the thrombin active site was successfully validated. A comparable binding mode with the minimum root-mean-square deviation (RMSD) of 1.4 Å at simulation time point 71.6 ns was achieved. This method validation study extended the application domain of the SuMD sampling method for computationally cheap, fast but accurate, and insightful macrocycle–protein molecular recognition studies. Frontiers Media S.A. 2021-08-31 /pmc/articles/PMC8438215/ /pubmed/34532343 http://dx.doi.org/10.3389/fmolb.2021.707661 Text en Copyright © 2021 Hassankalhori, Bolcato, Bissaro, Sturlese and Moro. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Hassankalhori, Mahdi Bolcato, Giovanni Bissaro, Maicol Sturlese, Mattia Moro, Stefano Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics |
title | Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics |
title_full | Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics |
title_fullStr | Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics |
title_full_unstemmed | Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics |
title_short | Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics |
title_sort | shedding light on the molecular recognition of sub-kilodalton macrocyclic peptides on thrombin by supervised molecular dynamics |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438215/ https://www.ncbi.nlm.nih.gov/pubmed/34532343 http://dx.doi.org/10.3389/fmolb.2021.707661 |
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