Computational Approach to Design Antagonists of Mycobacterium Tuberculosis Lipoprotein Lprg (RV1411C) Protein

Authors

  • Syed Asif Hassan Department of Computer Science, Faculty of Computing and Information Technology Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia
  • Tabrej Khan Department of Information Systems, Faculty of Computing and Information Technology Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia
  • Arshad Hashmi Department of Information Systems, Faculty of Computing and Information Technology Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia

DOI:

https://doi.org/10.21015/vtcs.v10i2.443

Abstract

. Evolution of multi-drug resistance strains of Mycobacterium tuberculosis (MTB) has in the past caused severe epidemics of tuberculosis across the globe thereby it raises a question on the potency or efficacy of the current scaffolds of drugs targeting MTB. Therefore, there an urgency to identify novel antimycobacterial compounds targeting proteins important for the viability of Multi-Drug-Resistant Tuberculosis (MDR-TB) strains. In this regard Mtb LprG (Rv1411c) a lipoprotein involved in the evasion of cell-mediated immune response within infected host macrophages is an important target for screening antimycobacterial compounds against Mtb. In the current study, a workflow involving ligand-based virtual screening namely USRCAT (Ultra Shape Recognition) and molecular docking studies were employed to identify novel antituberculosis compounds. Based on USRCAT and docking studies XPX an analog of triacylated glycolipid was screened as a promising lead molecule that shows higher specificity and binding affinity for Mtb LprG protein. Further, in vitro experimentations are required to testify the role of XPX as an anti-TB drug for the treatment of MDT-TB.  

 

Keywords: Multi-drug Resistant Tuberculosis; Toll-like receptor 2 (TLR2); antagonist; Molecular docking; Virtual screening

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Published

2016-08-12

Issue

Vol. 4 No. 1 (2016): January-December

Section

Articles

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