An all atom energy based computational protocol for predicting binding affinities of protein-ligand complexes.
We report here a computationally fast protocol for predicting binding affinities of non-metallo protein-ligand complexes. The protocol builds in an all atom energy based empirical scoring function comprising electrostatics, van der Waals, hydrophobicity and loss of conformational entropy of protein side chains upon ligand binding. The method is designed to ensure transferability across diverse systems and has been validated on a heterogenous dataset of 161 complexes consisting of 55 unique protein targets. The scoring function trained on a dataset of 61 complexes yielded a correlation of r=0.92 for the predicted binding free energies against the experimental binding affinities. Model validation and parameter analysis studies ensure the predictive ability of the scoring function. When tested on the remaining 100 protein-ligand complexes a correlation of r=0.92 was recovered. The high correlation obtained underscores the potential applicability of the methodology in drug design endeavors. The scoring function has been web enabled at as binding affinity prediction of protein-ligand (BAPPL) server.
Jain
Tarun
T
Department of Chemistry and Supercomputing Facility for Bioinformatics and Computational Biology, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India.
Jayaram
B
B
D015195:Drug Design; D008024:Ligands; D008958:Models, Molecular; D008962:Models, Theoretical; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
D008024:Ligands; D011506:Proteins