Drug-Target Interactions: Prediction Methods and Applications

Author(s): Shanmugam Anusuya*, Manish Kesherwani, K. Vishnu Priya, Antonydhason Vimala, Gnanendra Shanmugam, Devadasan Velmurugan, M. Michael Gromiha*

Journal Name: Current Protein & Peptide Science

Volume 19 , Issue 6 , 2018

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Graphical Abstract:


Identifying the interactions between drugs and target proteins is a key step in drug discovery. This not only aids to understand the disease mechanism, but also helps to identify unexpected therapeutic activity or adverse side effects of drugs. Hence, drug-target interaction prediction becomes an essential tool in the field of drug repurposing. The availability of heterogeneous biological data on known drug-target interactions enabled many researchers to develop various computational methods to decipher unknown drug-target interactions. This review provides an overview on these computational methods for predicting drug-target interactions along with available webservers and databases for drug-target interactions. Further, the applicability of drug-target interactions in various diseases for identifying lead compounds has been outlined.

Keywords: Drug-target interaction, machine learning, supervised method, semi-supervised method, drug repurposing, polypharmacology, similarity based method, feature based method, drug design.

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Article Details

Year: 2018
Published on: 07 November, 2016
Page: [537 - 561]
Pages: 25
DOI: 10.2174/1389203718666161108091609
Price: $65

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