Literature DB >> 26232029

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

Rukmankesh Mehra1, Reena Chib2,3, Gurunadham Munagala4,3, Kushalava Reddy Yempalla4,3, Inshad Ali Khan2,3, Parvinder Pal Singh4,3, Farrah Gul Khan5, Amit Nargotra6,7.   

Abstract

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.

Entities:  

Keywords:  In silico screening; Mycobacterium tuberculosis inhibitors; Pharmacophore modeling; Proteasome inhibitors; QSAR; Similarity search

Mesh:

Substances:

Year:  2015        PMID: 26232029     DOI: 10.1007/s11030-015-9624-0

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  46 in total

1.  Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy.

Authors:  Richard A Friesner; Jay L Banks; Robert B Murphy; Thomas A Halgren; Jasna J Klicic; Daniel T Mainz; Matthew P Repasky; Eric H Knoll; Mee Shelley; Jason K Perry; David E Shaw; Perry Francis; Peter S Shenkin
Journal:  J Med Chem       Date:  2004-03-25       Impact factor: 7.446

2.  Virtual screening of biogenic amine-binding G-protein coupled receptors: comparative evaluation of protein- and ligand-based virtual screening protocols.

Authors:  Andreas Evers; Gerhard Hessler; Hans Matter; Thomas Klabunde
Journal:  J Med Chem       Date:  2005-08-25       Impact factor: 7.446

3.  PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results.

Authors:  Steven L Dixon; Alexander M Smondyrev; Eric H Knoll; Shashidhar N Rao; David E Shaw; Richard A Friesner
Journal:  J Comput Aided Mol Des       Date:  2006-11-24       Impact factor: 3.686

4.  Protein protein interaction inhibition (2P2I) combining high throughput and virtual screening: Application to the HIV-1 Nef protein.

Authors:  Stéphane Betzi; Audrey Restouin; Sandrine Opi; Stefan T Arold; Isabelle Parrot; Françoise Guerlesquin; Xavier Morelli; Yves Collette
Journal:  Proc Natl Acad Sci U S A       Date:  2007-11-27       Impact factor: 11.205

Review 5.  Three-dimensional pharmacophore methods in drug discovery.

Authors:  Andrew R Leach; Valerie J Gillet; Richard A Lewis; Robin Taylor
Journal:  J Med Chem       Date:  2010-01-28       Impact factor: 7.446

Review 6.  Proteasome inhibitors: Dozens of molecules and still counting.

Authors:  Geoffroy de Bettignies; Olivier Coux
Journal:  Biochimie       Date:  2010-07-06       Impact factor: 4.079

Review 7.  Covalent and non-covalent reversible proteasome inhibition.

Authors:  Philipp Beck; Christian Dubiella; Michael Groll
Journal:  Biol Chem       Date:  2012-10       Impact factor: 3.915

8.  Distinct specificities of Mycobacterium tuberculosis and mammalian proteasomes for N-acetyl tripeptide substrates.

Authors:  Gang Lin; Christopher Tsu; Lawrence Dick; Xi K Zhou; Carl Nathan
Journal:  J Biol Chem       Date:  2008-10-01       Impact factor: 5.157

9.  N,C-Capped dipeptides with selectivity for mycobacterial proteasome over human proteasomes: role of S3 and S1 binding pockets.

Authors:  Gang Lin; Tamutenda Chidawanyika; Christopher Tsu; Thulasi Warrier; Julien Vaubourgeix; Christopher Blackburn; Kenneth Gigstad; Michael Sintchak; Lawrence Dick; Carl Nathan
Journal:  J Am Chem Soc       Date:  2013-06-25       Impact factor: 15.419

10.  Ligand-based pharmacophore modeling and virtual screening for the discovery of novel 17β-hydroxysteroid dehydrogenase 2 inhibitors.

Authors:  Anna Vuorinen; Roger Engeli; Arne Meyer; Fabio Bachmann; Ulrich J Griesser; Daniela Schuster; Alex Odermatt
Journal:  J Med Chem       Date:  2014-07-10       Impact factor: 7.446

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  3 in total

1.  A structural-chemical explanation of fungal laccase activity.

Authors:  Rukmankesh Mehra; Jan Muschiol; Anne S Meyer; Kasper P Kepp
Journal:  Sci Rep       Date:  2018-11-23       Impact factor: 4.379

Review 2.  Predictive Power of In Silico Approach to Evaluate Chemicals against M. tuberculosis: A Systematic Review.

Authors:  Giulia Oliveira Timo; Rodrigo Souza Silva Valle Dos Reis; Adriana Françozo de Melo; Thales Viana Labourdette Costa; Pérola de Oliveira Magalhães; Mauricio Homem-de-Mello
Journal:  Pharmaceuticals (Basel)       Date:  2019-09-16

3.  Identification of New Mycobacterium tuberculosis Proteasome Inhibitors Using a Knowledge-Based Computational Screening Approach.

Authors:  Tahani M Almeleebia; Mesfer Al Shahrani; Mohammad Y Alshahrani; Irfan Ahmad; Abdullah M Alkahtani; Md Jahoor Alam; Mohd Adnan Kausar; Amir Saeed; Mohd Saeed; Sana Iram
Journal:  Molecules       Date:  2021-04-16       Impact factor: 4.411

  3 in total

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