Department of Biotechnology
inStem (Institute for Stem Cell Science and Regenerative Medicine)

Identification of Mtb GlmU Uridyltransferase Domain Inhibitors by Ligand-Based and Structure-Based Drug Design Approaches.

Publication Type

Journal Article

Date of Publication

April 28, 2022

Journal

Molecules (Basel, Switzerland)

Volume/Issue

27/9

ISSN

1420-3049

Targeting enzymes that play a role in the biosynthesis of the bacterial cell wall has long been a strategy for antibacterial discovery. In particular, the cell wall of (Mtb) is a complex of three layers, one of which is Peptidoglycan, an essential component providing rigidity and strength. UDP-GlcNAc, a precursor for the synthesis of peptidoglycan, is formed by GlmU, a bi-functional enzyme. Inhibiting GlmU Uridyltransferase activity has been proven to be an effective anti-bacterial, but its similarity with human enzymes has been a deterrent to drug development. To develop Mtb selective hits, the Mtb GlmU substrate binding pocket was compared with structurally similar human enzymes to identify selectivity determining factors. Substrate binding pockets and conformational changes upon substrate binding were analyzed and MD simulations with substrates were performed to quantify crucial interactions to develop critical pharmacophore features. Thereafter, two strategies were applied to propose potent and selective bacterial GlmU Uridyltransferase domain inhibitors: (i) optimization of existing inhibitors, and (ii) identification by virtual screening. The binding modes of hits identified from virtual screening and ligand growing approaches were evaluated further for their ability to retain stable contacts within the pocket during 20 ns MD simulations. Hits that are predicted to be more potent than existing inhibitors and selective against human homologues could be of great interest for rejuvenating drug discovery efforts towards targeting the Mtb cell wall for antibacterial discovery.

Alternate Journal

Molecules

PubMed ID

35566155

PubMed Central ID

PMC9105790

Authors

Manvi Singh
Priya Kempanna
Kavitha Bharatham

Keywords

Humans
Molecular Docking Simulation
Mycobacterium tuberculosis
Anti-Bacterial Agents
Drug Design
Enzyme Inhibitors
Ligands
Peptidoglycan
UDPglucose-Hexose-1-Phosphate Uridylyltransferase