QSAR Based Pharmacophore Modeling, Design, Molecular Simulation and Computational ADME/Pharmacokinetics Validation

Abstract Background: Persistent resistance of Mycobacterium tuberculosis towards anti-tubercular drugs have raised global concern to cure tuberculosis. Recent advancements of the chemical world particularly that of computational chemistry, has given the scientists, a new dimension to curtail the challenges of drug development and discovery. This has become necessary to develop efficient anti-tubercular agents against the multi-drug resistant strain.Aim: In this research, we aimed to build in-silico an anti-tubercular model to predict reported experimental activities via Genetic Function Algorithm, use the model to design novel hypothetical compounds, carryout virtual docking screening and compute the ADME properties, pharmacokinetics and drug-likeness for the designed compounds.Results: Confirmed molecular descriptors ‘‘MATS7s, SpMin4_Bhv, SM1_DzZ, TDB3v and RDF70v’’ were selected via the Genetic Function Algorithm for model development. Three prominent hypothetical compounds; 6a, 6b and 6c having enhanced activities against tuberculosis were successfully designed with efficient binding affinities which ranged from -13.34 to -15.36Kcal/mol. These compounds demonstrate good binding pose and efficient interactions with the protein binding pocket via virtual docking screening. ADME, pharmacokinetics and drug-likeness prediction suggested that the compounds are orally soluble, have a good lipophilicity index for lipid environments with high gastrointestinal absorption and show zero violation to be considered as drug candidates. Conclusion: Our finding revealed that the designed compounds are founds to be orally bioavailable and demonstrate good drugs candidates. Hence,in-vitro and an in-vivo test for these compounds are strongly recommended to determine their toxicities and biological assay.