Computational Prediction and Analysis of Associations between Small Molecules and Binding-Associated S-Nitrosylation Sites.

ABSTRACT: Interactions between drugs and proteins occupy a central position during the process of drug discovery and development. Numerous methods have recently been developed for identifying drug⁻target interactions, but few have been devoted to finding interactions between post-translationally modified proteins and drugs. We presented a machine learning-based method for identifying associations between small molecules and binding-associated S-nitrosylated (SNO-) proteins. Namely, small molecules were encoded by molecular fingerprint, SNO-proteins were encoded by the information entropy-based method, and the random forest was used to train a classifier. Ten-fold and leave-one-out cross validations achieved, respectively, 0.7235 and 0.7490 of the area under a receiver operating characteristic curve.

SUBMITTER: Huang G 

PROVIDER: S-EPMC6017196 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature