title: Toward the prediction of FBPase inhibitory activity using chemoinformatic methods.
abstract: Currently, Chemoinformatic methods are used to perform the prediction for FBPase inhibitory activity. A genetic algorithm-random forest coupled method (GA-RF) was proposed to predict fructose 1,6-bisphosphatase (FBPase) inhibitors to treat type 2 diabetes mellitus using the Mold(2) molecular descriptors. A data set of 126 oxazole and thiazole analogs was used to derive the GA-RF model, yielding the significant non-cross-validated correlation coefficient r(2) (ncv) and cross-validated r(2) (cv) values of 0.96 and 0.67 for the training set, respectively. The statistically significant model was validated by a test set of 64 compounds, producing the prediction correlation coefficient r(2) (pred) of 0.90. More importantly, the building GA-RF model also passed through various criteria suggested by Tropsha and Roy with r(2) (o) and r(2) (m) values of 0.90 and 0.83, respectively. In order to compare with the GA-RF model, a pure RF model developed based on the full descriptors was performed as well for the same data set. The resulting GA-RF model with significantly internal and external prediction capacities is beneficial to the prediction of potential oxazole and thiazole series of FBPase inhibitors prior to chemical synthesis in drug discovery programs.
authors: Department of Materials Science and Chemical Engineering, Dalian University of Technology, Dalian 116023, Liaoning, China.
authors: Ming
authors: M
authors: Hao
authors: Department of Materials Science and Chemical Engineering, Dalian University of Technology, Dalian 116023, Liaoning, China.
authors: Shuwei
authors: S
authors: Zhang
authors: Department of Materials Science and Chemical Engineering, Dalian University of Technology, Dalian 116023, Liaoning, China.
authors: Jieshan
authors: J
authors: Qiu
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy; D055808:Drug Discovery; D006597:Fructose-Bisphosphatase / Q000037:antagonists & inhibitors* / Q000737:chemistry; D006801:Humans; D020128:Inhibitory Concentration 50; D008958:Models, Molecular; D015233:Models, Statistical; D010080:Oxazoles / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
chemical_list: D010080:Oxazoles; D006597:Fructose-Bisphosphatase