Automated Quantitative Structure-Activity Relationship: To Develop The Best Model To Identify Small-Molecule Glucokinase Activator For Type-2-Diabetes

Abstract

Glucokinase (GK, EC 2.7.1.2), is a crucial enzyme that catalyzes the conversion of glucose to glucose-6-phosphate. Type-2 diabetes (T2D) is a serious metabolic disorder that is still at the forefront without proper medication. Unfortunately, current treatment options are not effective and have many side effects. Hence this work aims to identify automated models that aid in the identification of small molecule glucokinase activators (GKA) that target GK and help in increasing the glucose utilization of the body cells. To realize a novel model, the analysis of the automated quantitative structure-activity relationship of compounds from identified bioassay series AID_504730 and AID_488612 was carried out using AutoQSAR from Schrodinger software. The developed best model revealed R2 =  0.8900 and Q2  =0.8520 with an RMSE of 0.2895. Thus this model can be used in identifying potential small molecules as GKAs