Calculation of Protein-Ligand Binding Free Energy Using Smooth Reaction Path Generation (SRPG) Method; a Comparison of the Explicit Water Model, GB/SA Model and Docking Score Function

Daisuke Mitomo[1] (
Yoshifumi Fukunishi[2][3] (
Junichi Higo[4] (
Haruki Nakamura[2][5] (

[1] Japan Biological Informatics Consortium (JBIC), 2-41-6, Aomi, Koto-ku, Tokyo 135-0064, Japan
[2] Biomedicinal Information Research Center (BIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6, Aomi, Koto-ku, Tokyo 135-0064, Japan
[3] Pharmaceutical Innovation Value Chain, BioGrid Center Kansai, 1-4-2 Shinsenri-Higashimachi, Toyonaka, Osaka 560-0082, Japan
[4] The Center for Advanced Medical Engineering and Informatics, Osaka University, Open Laboratories for Advanced Bioscience and Biotechnology, 6-2-3, Furuedai, Suita, Osaka 565-0874, Japan
[5] Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan


We compared the proteinligand binding free energies (G) obtained by the explicit water model, the MM-GB/SA (molecular-mechanics generalized Born surface area) model, and the docking scoring function. The free energies by the explicit water model and the MM-GB/SA model were calculated by the previously developed Smooth Reaction Path Generation (SRPG) method. In the SRPG method, a smooth reaction path was generated by linking two coordinates, one a bound state and the other an unbound state. The free energy surface along the path was calculated by a molecular dynamics (MD) simulation, and the binding free energy was estimated from the free energy surface. We applied these methods to the streptavidin-and-biotin system. The G value by the explicit water model was close to the experimental value. The G value by the MM-GB/SA model was overestimated and that by the scoring function was underestimated. The free energy surface by the explicit water model was close to that by the GB/SA model around the bound state (distances of < 6 ), but the discrepancy appears at distances of > 6 . Thus, the difference in long-range Coulomb interaction should cause the error in G. The scoring function cannot take into account the entropy change of the protein. Thus, the error of G could depend on the target protein.

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Japanese Society for Bioinformatics