Genetic functional algorithm model, docking studies and in silico design of novel proposed compounds against Mycobacterium tuberculosis

Abstract

Tuberculosis still persist a major challenge to healthcare system around the world. Increasing rates of morbidity, mortality and the reoccurrence of the resistant strains of the disease to accessible drugs/medications have made it crucial to search for a new therapy in term of novel and prominent hypothetical compound treat tuberculosis. Therefore, Quantitative Structure-Activity Relationship (QSAR) was employed as a modelling technique to predict and design new compounds with improved and efficient biological activities against Mycobacterium tuberculosis. To accomplish the purpose of this work, Genetic function approximation was adopted to derive the model. The established model was swayed with topological descriptors; MATS9s, SM1_DzZ, SpMin4_Bhv, TDB2v and RDF70v.More also, interactions between the compounds and the target protein ''DNA gyrase'' indicated that compound 20 has the most perceptible binding affinity of-18.12kcal/mol. Consequently, compound 20 served as a reference structural template and insight to design fourteen novel hypothetical agents with more prominent anti-tubercular activities. More also, compound 20j was observed with high activity among the designed compounds with more a prominent binding affinities of-24.3 kcal/mol. Therefore this research recommends in-vivo, in-vitro screening and pharmacokinetic properties to be carried out in order to determine the toxicity of the designed compounds.