Quantitative Structure-activity Relationship (QSAR) Models for Docking Score Correction.

ABSTRACT: In order to improve docking score correction, we developed several structure-based quantitative structure activity relationship (QSAR) models by protein-drug docking simulations and applied these models to public affinity data. The prediction models used descriptor-based regression, and the compound descriptor was a set of docking scores against multiple (∼600) proteins including nontargets. The binding free energy that corresponded to the docking score was approximated by a weighted average of docking scores for multiple proteins, and we tried linear, weighted linear and polynomial regression models considering the compound similarities. In addition, we tried a combination of these regression models for individual data sets such as IC₅₀ , K_i , and %inhibition values.

SUBMITTER: Fukunishi Y 

PROVIDER: S-EPMC5297997 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature