Genetic functional algorithm model, docking studies and in silico design of novel proposed compounds against Mycobacterium tuberculosis. Issue 1 (1st January 2020) - Adeniji, Shola Elijah
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.