4.7 Review

A brief review of protein-ligand interaction prediction

Journal

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 20, Issue -, Pages 2831-2838

Publisher

ELSEVIER
DOI: 10.1016/j.csbj.2022.06.004

Keywords

Protein-ligand interactions; Drug-target binding affinity; Drug discovery; Machine learning

Funding

  1. National Natural Science Foundation of China [62171164, 62102191, 61872114, 62131004]

Ask authors/readers for more resources

This review provides a brief introduction to computation-based protein-ligand interactions (PLIs) and discusses various approaches, with a particular focus on machine learning methods. It also analyzes three research dynamics that can be further explored in future studies.
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.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available