Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1785064436279541760 |
---|---|
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. |
format | Online Article Text |
id | pubmed-10299731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wangjinan challengesandfrontiersofcomputationalmodellingofbiomolecularrecognition AT bhattaraiapurba challengesandfrontiersofcomputationalmodellingofbiomolecularrecognition AT dohungn challengesandfrontiersofcomputationalmodellingofbiomolecularrecognition AT miaoyinglong challengesandfrontiersofcomputationalmodellingofbiomolecularrecognition |