Vikas Gautam, Archana Singh, Irin Sarah Jacob, Sarika N Suryawanshi
Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER) EPIP Campus, Industrial Area, Hajipur – 844102, Bihar, India.


Tuberculosis is one of the most prevalent infections of human beings and contributes considerably to illness and death around the world. One-third of the world’s population is thought to be infected with Mycobacterium tuberculosis and new infections occur at a rate of about one per second. The proportion of people who become sick with tuberculosis each year is stable or falling worldwide but because of population growth, the absolute number of new cases is still increasing. In 2007, there were an estimated 13.7 million chronic active cases, 9.3 million new cases and 1.8 million deaths, mostly in developing countries. In addition, more people in the developed world are infected by tuberculosis because their immune systems are more likely to be compromised due to higher exposure toimmunosuppressive drugs, substance abuse or AIDS. Despite the fact that several drugs are available for the treatment of infection caused by M. tuberculosis, most of them fail to eliminate clinical symptoms. The present work is based on arylamine Nacetyltransferase (NAT) in M. tuberculosis as a potential drug target. The pathway of cholesterol catabolism is an attractive target for therapeutic intervention. The NAT enzyme from M. tuberculosis (TBNAT) was found to be able to utilize the cholesterol metabolite n-propionyl-CoA, linking it to cholesterol metabolism. Inhibition of this enzyme prevents the survival of the microorganisminside macrophages, rendering the mycobacterium sensitive to antibioticsto which it is normally resistant. The objective of this study is to utilize in silico techniques to develop appropriate model of BNAT and to design potential inhibitors against the same using fragment-based drug design approach. The workflow includes the model-building using 2VFB as template by using Swiss model server and Prime module of Schrodinger 9.2.The model showed good structure quality as validated by using validation tools like Procheck, Verify3D. The Ramachandran plot showed 85.2% most favoured regions, 13.1%allowed region and 0.4%generously allowed regions. Protein preparation was done through Protein preparation workflow of Schrodinger 9.2. The next step was screening of fragment library from Zinc database for finding potential inhibitors for TBNAT of M. tuberculosis by using FlexX. Filtering of the molecules with good score was made more refined with the help of ADMET analysis using QikProp module of Schrodinger 9.2. With the results as per the prediction studies, it is believed that the reported novel molecules could be proved worthy if assayed biologically against the target in future.Read more…

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