Comprehensive Protein-Ligand Interaction Analysis: Fragment Molecular Orbital Calculation on the Complexes of Human Protease Renin and its Inhibitors

Yoichiro Yagi, Takatomo Kimura, Chiduru Watanabe, Yoshio Okiyama, Shigenori Tanaka, Teruki Honma, Kaori Fukuzawa

To elucidate the molecular recognition mechanism between renin and its inhibitor, we analyze intermolecular interaction energies based on fragment molecular orbital (FMO) calculations for twenty different complexes of various inhibitors. We discuss a relationship between the experimental activity value of inhibitors and the calculated binding energy, and clustering analyses for inter-fragment interaction energies (IFIEs) between the inhibitor and the amino acid residues in renin. We estimated the sum of IFIEs as binding energy between an inhibitor and renin, and found that the calculated binding energies have a relatively strong correlation (R2 = 0.73) with the experimental IC50 values of each inhibitor. The high-activity correlation between the calculated and experimental values can lead to predicting the effects of drugs and the activity value of new compounds. In addition, we carried out a detailed interaction energy analysis between inhibitors and the amino acid residues in renin, and performed clustering of inhibitors not only by their structure/binding mode but also by the characteristics of interaction, such as energy values, energy patterns, and interacting amino acid residues. As a result, we found that the difference in interaction due to a slight difference in structure, such as the addition/replacement of a single atom/functional group, can be related to the difference in IC50 values. Consequently, the inhibitors in the finally classified clusters tend to show the same order of IC50 value. These results indicate that the structure and the activity value of inhibitor are related to each other through the interaction between an inhibitor and relevant amino acid residues, and suggest that it is certainly possible to predict the IC50 values of inhibitors. Therefore, we consider that our FMO-IFIE analysis would be a useful method to contribute toward innovative drug discovery.

Chem-Bio Informatics Journal (CBI Journal)

情報計算化学生物学会 (CBI学会)

25

107

129

10.1273/cbij.25.107