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Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles
Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9703445/ https://www.ncbi.nlm.nih.gov/pubmed/36465086 http://dx.doi.org/10.1007/s12551-022-01015-8 |
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author | Fukunishi, Yoshifumi Higo, Junichi Kasahara, Kota |
author_facet | Fukunishi, Yoshifumi Higo, Junichi Kasahara, Kota |
author_sort | Fukunishi, Yoshifumi |
collection | PubMed |
description | Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied. |
format | Online Article Text |
id | pubmed-9703445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-97034452022-11-28 Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles Fukunishi, Yoshifumi Higo, Junichi Kasahara, Kota Biophys Rev Review Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied. Springer Berlin Heidelberg 2022-11-28 /pmc/articles/PMC9703445/ /pubmed/36465086 http://dx.doi.org/10.1007/s12551-022-01015-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Fukunishi, Yoshifumi Higo, Junichi Kasahara, Kota Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
title | Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
title_full | Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
title_fullStr | Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
title_full_unstemmed | Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
title_short | Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
title_sort | computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9703445/ https://www.ncbi.nlm.nih.gov/pubmed/36465086 http://dx.doi.org/10.1007/s12551-022-01015-8 |
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