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Challenges and frontiers of computational modelling of biomolecular recognition

Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have prese...

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Detalles Bibliográficos
Autores principales: Wang, Jinan, Bhattarai, Apurba, Do, Hung N., Miao, Yinglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10299731/
https://www.ncbi.nlm.nih.gov/pubmed/37377636
http://dx.doi.org/10.1017/qrd.2022.11
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author Wang, Jinan
Bhattarai, Apurba
Do, Hung N.
Miao, Yinglong
author_facet Wang, Jinan
Bhattarai, Apurba
Do, Hung N.
Miao, Yinglong
author_sort Wang, Jinan
collection PubMed
description Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.
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spelling pubmed-102997312023-06-27 Challenges and frontiers of computational modelling of biomolecular recognition Wang, Jinan Bhattarai, Apurba Do, Hung N. Miao, Yinglong QRB Discov Perspective Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modelling. Here, we review the challenges and computational approaches developed to characterise biomolecular binding, including molecular docking, molecular dynamics simulations (especially enhanced sampling) and machine learning. Further improvements are still needed in order to accurately and efficiently characterise binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future. Cambridge University Press 2022-08-19 /pmc/articles/PMC10299731/ /pubmed/37377636 http://dx.doi.org/10.1017/qrd.2022.11 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 Perspective
Wang, Jinan
Bhattarai, Apurba
Do, Hung N.
Miao, Yinglong
Challenges and frontiers of computational modelling of biomolecular recognition
title Challenges and frontiers of computational modelling of biomolecular recognition
title_full Challenges and frontiers of computational modelling of biomolecular recognition
title_fullStr Challenges and frontiers of computational modelling of biomolecular recognition
title_full_unstemmed Challenges and frontiers of computational modelling of biomolecular recognition
title_short Challenges and frontiers of computational modelling of biomolecular recognition
title_sort challenges and frontiers of computational modelling of biomolecular recognition
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10299731/
https://www.ncbi.nlm.nih.gov/pubmed/37377636
http://dx.doi.org/10.1017/qrd.2022.11
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