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.
{"title":"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.","authors":"D. Mitomo, Y. Fukunishi, J. Higo, Haruki Nakamura","doi":"10.1142/9781848165632_0008","DOIUrl":null,"url":null,"abstract":"We compared the protein-ligand 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 A), but the discrepancy appears at distances of > 6 A. 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.","PeriodicalId":73143,"journal":{"name":"Genome informatics. International Conference on Genome Informatics","volume":"6 1","pages":"85-97"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome informatics. International Conference on Genome Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/9781848165632_0008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
We compared the protein-ligand 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 A), but the discrepancy appears at distances of > 6 A. 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.