DOCKING STUDIES FOR TUBERCULOSIS TAKING ALANINE RACEMASE AS A RECEPTOR AND A NOVEL PLANT SOURCE QUERCETIN AS A POTENTIAL DRUG SOURCE

Abstract

Tuberculosis is known to be a fatal infectious disease causing a large number of deaths every year. The causative agent of TB is the pathogenic bacteria Mycobacterium tuberculosis. Although vaccines and drugs have been developed, cases of TB infections are still widespread largely due to development of drug resistant strains of Mycobacterium tuberculosis which makes it imperative to search for a novel drug target.  Due to its essential nature and the requirement of new drug targets for better anti mycobacterial drug, an essential and uniquely prokaryotic enzyme alanine racemase has been pursued as a target. A scrutinization of the published writings supported the role of mycolic acid a major component of cell wall synthesis of bacteria increasing the novelty of alanine racemase as a drug target for noble drug discovery. Our study is based on designing natural inhibitors taking alanine racemase as a target. The ligands were drawn using Marvin Sketch. The choice of the ligands was based on the criterion that the ligands would be chosen from plant sources to minimize the mutagenic behavior of the selected ligands. Further we have done docking calculations using Molegro Virtual Docker where alanine racemase was used as a receptor and was docked by all the potential ligands including the ones derived from plant sources like kaemferol, mimosine, naphthoquinone, quercetin and xanthone and the traditional drugs used to cure TB. Based on the total energy value calculated on the basis of a scoring function designed it has been seen that Quercitin with cavity -3 (Mol Doc Score -102.489 Kcal/mol) has the best inhibitory effect followed by Mimosine (Mol Doc Score -100.51 Kcal/mol). The results suggest that the energy of the chosen ligand is better than the existing drugs, and can be considered as a novel and effective drug in the specific remedy of pulmonary tuberculosis. This computational predicted data could be further validated using suitable assays for further consideration.