Drug-Target Interactions: Prediction Methods and Applications

Title:Drug-Target Interactions: Prediction Methods and Applications

Volume: 19 Issue: 6

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

Affiliation:

• Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai - 600036, Tamil Nadu,India

• Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai - 600036, Tamil Nadu,India

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

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.

Cite this article as:

Anusuya Shanmugam*, Kesherwani Manish, Priya Vishnu K., Vimala Antonydhason, Shanmugam Gnanendra, Velmurugan Devadasan and Gromiha Michael M.*, Drug-Target Interactions: Prediction Methods and Applications, Current Protein & Peptide Science 2018; 19 (6) . https://dx.doi.org/10.2174/1389203718666161108091609