Study of the structure, QSAR properties and molecular docking of some amino-pyrimidine derivatives as Novel Mycobacterium tuberculosis inhibitors for drug design

Abstract

The discovery of anti-tuberculosis agents is crucial for effective tuberculosis therapy. The present strategy for new drug development is directed towards identifying essential enzyme systems in the bacteria and developing potent molecules to inhibit them.We have study the inhibition of 29 amino-pyrimidine derivatives of Mycobacterium tuberculosis PKnB using different CADD approaches to search for potential drug candidates. The multi-parameter optimization (MPO) process to predict the best balance of properties of these compounds was expressed by various approaches such as Lipophilic Efficiency (LipE), Lipinski, Veber rules. The Multiple linear regression method (MLR) was applied to derive QSAR model which was further validated for statistical significance by internal and external validation. In Silico molecular docking and ADMET properties used to predict novel PKnB inhibitors and guide the discovery of new potential analogs.