Title:Advances in Computational Studies of Potential Drug Targets in Mycobacterium tuberculosis
Volume: 18
Issue: 13
Author(s): Subha Mahadevi Alladi*
Affiliation:
- Independent Researcher, Hazelwood, Redmond, WA 98052,United States
Keywords:
Tuberculosis, Virtual screening, Fingerprints, Docking, Molecular dynamics, QM/MM, Machine learning techniques,
Metalloproteins.
Abstract: Tuberculosis continues to remain as one of the leading causes of death worldwide, in spite of
significant progress being made in the last twenty years through increased compliance to treatment. The
current review gives an overview of the recent efforts made in the endeavor to identify novel inhibitors
and promising drug targets for Mycobacterium tuberculosis with structure and ligand-based approaches
along with bioinformatics studies following complete sequencing of its genome. A large number of
these studies target biomolecules in metabolic pathways that are vital for the survival of the microorganism.
A discussion on efforts to study metalloproteins as relatively underexplored targets in the context of
their druggability is also presented.