RANK-ORDERING THE BINDING AFFINITY FOR FKBP12 AND H1N1 NEURAMINIDASE INHIBITORS IN THE COMBINATION OF A PROTEIN MODEL WITH DENSITY FUNCTIONAL THEORY

Abstract

The quantum mechanical interaction energies between FKBP12 as well as H1N1 neuraminidase and their inhibitors were directly calculated with an efficient density functional theory by mimicking the whole protein with a protein model composed of the amino acids surrounding the ligands. It was found that the calculated quantum mechanical interaction energies correlate well with the experimental binding free energies with the correlation coefficients of 0.88, 0.86, and the standard deviation of 0.93 and 1.00 kcal/mol, respectively. To compare with force field approach, the binding free energies with the correlation coefficient R = 0.80 and 0.47 were estimated by AutoDock 4.0 programs. It was indicated that the quantum interaction energy shows a better performance in rank-ordering the binding affinity between FKBP12 and H1N1 neuraminidase inhibitors than those of AutoDock 4.0 program. In combination protein model with density functional theory, the estimated quantum interaction energy could be a good predictor or scoring function in structure-based computer-aided drug design. Finally, five new FKBP12 inhibitors were designed based on calculated quantum mechanical interaction energy. In particular, the theoretical K i value of one compound is as low as 0.05 nM, nearly 8-fold more active than FK506.