Regression Analysis and Docking Study of Pyrimidine Based Compounds as anti-Tuberculosis Therapeutic Agents

Received: 09/Apr/2019, Accepted: 19/Apr/2019, Online: 30/Apr/2019 AbstractIn the drug-design process, structure activity relationship is an important tool for estimation of biological activity of the unknown compounds. In this process, the objective is development of a relationship between structural features of molecules and the property of interest i. e. biological activity. On the basis of this relationship, the biological activity can be predicted for new candidate structures. Initially, the forty two substituted pyrimidine molecules with known biological activities were considered as known set for regression analysis model building purpose. The properties module from Datawarrior used to calculate descriptors. Structure activity model indicates that these descriptors have significant relationships with observed bioactivity. We have observed a high relationship between experimental and predicted activity values, indicating the validation and the excellent quality of the derived model. In the present study, the new substituted pyrimidine molecules are designed, optimized and their descriptors were calculated using Datawarrior modules. Then by using the Regression analysis model, their biological activities are studied as well as inhibition studies for the 1QPQ by molecular docking method are also carried out. Thus on the basis of regression analysis study and docking study of substituted pyrimidine derivatives, we can conclude that these compounds on further studies may prove to be therapeutic agent against tuberculosis.