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Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives
Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747661/ https://www.ncbi.nlm.nih.gov/pubmed/35023931 http://dx.doi.org/10.2147/AABC.S247950 |
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author | Pawnikar, Shristi Bhattarai, Apurba Wang, Jinan Miao, Yinglong |
author_facet | Pawnikar, Shristi Bhattarai, Apurba Wang, Jinan Miao, Yinglong |
author_sort | Pawnikar, Shristi |
collection | PubMed |
description | Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design. |
format | Online Article Text |
id | pubmed-8747661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-87476612022-01-11 Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives Pawnikar, Shristi Bhattarai, Apurba Wang, Jinan Miao, Yinglong Adv Appl Bioinform Chem Review Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design. Dove 2022-01-06 /pmc/articles/PMC8747661/ /pubmed/35023931 http://dx.doi.org/10.2147/AABC.S247950 Text en © 2022 Pawnikar et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Review Pawnikar, Shristi Bhattarai, Apurba Wang, Jinan Miao, Yinglong Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives |
title | Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives |
title_full | Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives |
title_fullStr | Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives |
title_full_unstemmed | Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives |
title_short | Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives |
title_sort | binding analysis using accelerated molecular dynamics simulations and future perspectives |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747661/ https://www.ncbi.nlm.nih.gov/pubmed/35023931 http://dx.doi.org/10.2147/AABC.S247950 |
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