Discovery of new Mycobacterium tuberculosis proteasome inhibitors using a knowledge-based computational screening approach

• Published in: Molecular diversity 2015-11, Vol.19 (4), p.1003-1019
• Main Authors: Mehra, Rukmankesh, Chib, Reena, Munagala, Gurunadham, Yempalla, Kushalava Reddy, Khan, Inshad Ali, Singh, Parvinder Pal, Khan, Farrah Gul, Nargotra, Amit
• Format: Article
• Language: English
• Subjects: Antitubercular Agents - chemistry; Antitubercular Agents - pharmacology; Computational Biology - methods; High-Throughput Screening Assays - methods; Humans; Molecular Docking Simulation; Molecular Dynamics Simulation; Mycobacterium tuberculosis - drug effects; Mycobacterium tuberculosis - enzymology; Proteasome Inhibitors - chemistry; Proteasome Inhibitors - pharmacology; Protein Binding; Quantitative Structure-Activity Relationship; Small Molecule Libraries - chemistry; Small Molecule Libraries - pharmacology
• ISSN: 1573-501X
• DOI: 10.1007/s11030-015-9624-0

Mycobacterium tuberculosis bacteria cause deadly infections in patients [Corrected]. The rise of multidrug resistance associated with tuberculosis further makes the situation worse in treating the disease. M. tuberculosis proteasome is necessary for the pathogenesis of the bacterium validated as an anti-tubercular target, thus making it an attractive enzyme for designing Mtb inhibitors. In this study, a computational screening approach was applied to identify new proteasome inhibitor candidates from a library of 50,000 compounds. This chemical library was procured from the ChemBridge (20,000 compounds) and the ChemDiv (30,000 compounds) databases. After a detailed analysis of the computational screening results, 50 in silico hits were retrieved and tested in vitro finding 15 compounds with IC₅₀ values ranging from 35.32 to 64.15 μM on lysate. A structural analysis of these hits revealed that 14 of these compounds probably have non-covalent mode of binding to the target and have not reported for anti-tubercular or anti-proteasome activity. The binding interactions of all the 14 protein-inhibitor complexes were analyzed using molecular docking studies. Further, molecular dynamics simulations of the protein in complex with the two most promising hits were carried out so as to identify the key interactions and validate the structural stability.