Identification of potent aldose reductase inhibitors as antidiabetic (Anti-hyperglycemic) agents using QSAR based virtual Screening, molecular Docking, MD simulation and MMGBSA approaches.

ABSTRACT: The aldose reductase (AR) enzyme is an important target enzyme in the development of therapeutics against hyperglycaemia induced health complications such as retinopathy, etc. In the present study, a quantitative structure activity relationship (QSAR) evaluation of a dataset of 226 reported AR inhibitor (ARi) molecules is performed using a genetic algorithm - multi linear regression (GA-MLR) technique. Multi-criteria decision making (MCDM) analysis furnished two five variables based QSAR models with acceptably high performance reflected in various statistical parameters such as, R² = 0.79-0.80, Q² _LOO = 0.78-0.79, Q² _LMO = 0.78-0.79. The QSAR model analysis revealed some of the molecular features that play crucial role in deciding inhi

SUBMITTER: Bakal RL 

PROVIDER: S-EPMC9257878 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature