Title

Prediction of kinase-inhibitor binding affinity using energetic parameters

Authors

Singaravelu Usha and Samuel Selvaraj*

Affiliation

Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli - 620 024, Tamilnadu, India.

Email

Dr. Samuel Selvaraj - Email: selvarajsamuel@gmail.com; Mobile: +919894390363; *Corresponding author

Article Type

Hypothesis

Date

Received May 13, 2016; Revised May30, 2016; Accepted May 30, 2016; Published June 15, 2016

The combination of physicochemical properties and energetic parameters derived from protein-ligand complexes play a vital role in determining the biological activity of a molecule. In the present work, protein-ligand interaction energy along with logP values was used to predict the experimental log (IC50) values of 25 different kinase-inhibitors using multiple regressions which gave a correlation coefficient of 0.93. The regression equation obtained was tested on 93 kinase-inhibitor complexes and an average deviation of 0.92 from the experimental log IC50 values was shown. The same set of descriptors was used to predict binding affinities for a test set of five individual kinase families, with correlation values > 0.9. We show that the protein-ligand interaction energies and partition coefficient values form the major deterministic factors for binding affinity of the ligand for its receptor.

Keywords

Inhibition constant prediction, Protein-ligand interaction, energetic and solvent descriptors, Kinase inhibitors

Citation

Usha & Selvaraj, Bioinformation 12(3): 172-181 (2016)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.