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A brief review of protein–ligand interaction prediction

The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in vitro experiments. There is a need to develop PLI computational prediction approaches to speed up the dru...

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Detalles Bibliográficos
Autores principales: Zhao, Lingling, Zhu, Yan, Wang, Junjie, Wen, Naifeng, Wang, Chunyu, Cheng, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189993/
https://www.ncbi.nlm.nih.gov/pubmed/35765652
http://dx.doi.org/10.1016/j.csbj.2022.06.004
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author Zhao, Lingling
Zhu, Yan
Wang, Junjie
Wen, Naifeng
Wang, Chunyu
Cheng, Liang
author_facet Zhao, Lingling
Zhu, Yan
Wang, Junjie
Wen, Naifeng
Wang, Chunyu
Cheng, Liang
author_sort Zhao, Lingling
collection PubMed
description The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in vitro experiments. There is a need to develop PLI computational prediction approaches to speed up the drug discovery process. In this review, we summarize a brief introduction to various computation-based PLIs. We discuss these approaches, in particular, machine learning-based methods, with illustrations of different emphases based on mainstream trends. Moreover, we analyzed three research dynamics that can be further explored in future studies.
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spelling pubmed-91899932022-06-27 A brief review of protein–ligand interaction prediction Zhao, Lingling Zhu, Yan Wang, Junjie Wen, Naifeng Wang, Chunyu Cheng, Liang Comput Struct Biotechnol J Mini Review The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in vitro experiments. There is a need to develop PLI computational prediction approaches to speed up the drug discovery process. In this review, we summarize a brief introduction to various computation-based PLIs. We discuss these approaches, in particular, machine learning-based methods, with illustrations of different emphases based on mainstream trends. Moreover, we analyzed three research dynamics that can be further explored in future studies. Research Network of Computational and Structural Biotechnology 2022-06-03 /pmc/articles/PMC9189993/ /pubmed/35765652 http://dx.doi.org/10.1016/j.csbj.2022.06.004 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Mini Review
Zhao, Lingling
Zhu, Yan
Wang, Junjie
Wen, Naifeng
Wang, Chunyu
Cheng, Liang
A brief review of protein–ligand interaction prediction
title A brief review of protein–ligand interaction prediction
title_full A brief review of protein–ligand interaction prediction
title_fullStr A brief review of protein–ligand interaction prediction
title_full_unstemmed A brief review of protein–ligand interaction prediction
title_short A brief review of protein–ligand interaction prediction
title_sort brief review of protein–ligand interaction prediction
topic Mini Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189993/
https://www.ncbi.nlm.nih.gov/pubmed/35765652
http://dx.doi.org/10.1016/j.csbj.2022.06.004
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