Prediction of kinase-inhibitor binding affinity using energetic parameters.
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.
Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli - 620 024, Tamilnadu, India.
Singaravelu
S
Usha
Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli - 620 024, Tamilnadu, India.
Samuel
S
Selvaraj
Inhibition constant prediction; Kinase inhibitors; Protein-ligand interaction; energetic and solvent descriptors