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Current Medicinal Chemistry

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ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

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Review Article

A Survey for Predicting ATP Binding Residues of Proteins Using Machine Learning Methods

Author(s): Yu-He Yang, Jia-Shu Wang, Shi-Shi Yuan, Meng-Lu Liu, Wei Su, Hao Lin* and Zhao-Yue Zhang*

Volume 29, Issue 5, 2022

Published on: 10 January, 2022

Page: [789 - 806] Pages: 18

DOI: 10.2174/0929867328666210910125802

Price: $65

Abstract

Protein-ligand interactions are necessary for majority protein functions. Adenosine- 5’-triphosphate (ATP) is one such ligand that plays vital role as a coenzyme in providing energy for cellular activities, catalyzing biological reaction and signaling. Knowing ATP binding residues of proteins is helpful for annotation of protein function and drug design. However, due to the huge amounts of protein sequences influx into databases in the post-genome era, experimentally identifying ATP binding residues is costineffective and time-consuming. To address this problem, computational methods have been developed to predict ATP binding residues. In this review, we briefly summarized the application of machine learning methods in detecting ATP binding residues of proteins. We expect this review will be helpful for further research.

Keywords: Adenosine-5’-triphosphate (ATP), binding residues, prediction, machine learning, feature extraction, proteins.

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