In Silico Phytochemicals Screening for Tuberculosis

Abstract

Tuberculosis (TB) is a highly contagious disease, and the increased mortality rate continues to be a cause for concern. Although anti-tuberculosis drugs are available, it still affects mankind, causing millions of deaths each year. By integrating biological data on gene sequences, gene expressions, protein structures, and drug target prioritization. The number of cheminformatics databases for small molecules and tools to assist drug discovery has also grown. Many researchers are investigating potential medication therapies that could assist in this battle along with the medical care system throughout the world. We present a docking?based screening using a quantum mechanical scoring of a library built from approved drugs and compounds that Bergenin, Laccaic acid, Swertiamarin, Magnolol, Curcumin, Emodin, Pasakbumin A, Umckalin, Plumbagin, Maritinone, Tetrahydro3,3?-biplumbagin and epigallocatechin with Proteins with PDB id’s 4W4I, 3Q0V could display antiviral activity against Tuberculosis. Ideally, these compounds should undergo experimental assays and clinical trials to verify their effectiveness against the disease. We hope that these findings may contribute to the rational drug design against Tuberculosis.