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Combinatorial Chemistry & High Throughput Screening


ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

Identification of Therapeutic Drug Target of Stenotrophomonas maltophilia Through Subtractive Genomic Approach and in-silico Screening Based on 2D Similarity Filtration and Molecular Dynamic Simulation

Author(s): Rahul Chandela, Dhananjay Jade, Surender Mohan, Ridhi Sharma and Shobana Sugumar *

Volume 25, Issue 1, 2022

Published on: 22 November, 2020

Page: [123 - 138] Pages: 16

DOI: 10.2174/1871520620666201123094330

Price: $65


Background: Stenotrophomonas maltophilia is a multi-drug resistant, gram-negative bacterium that causes opportunistic infections and is associated with high morbidity and mortality in severely immunocompromised individuals.

Aim: The study aimed to find out the drug target and a novel inhibitor for Stenotrophomonas maltophilia.

Objectives: The current study focused on identifying specific drug targets by subtractive genomes analysis to determine the novel inhibitor for the specified target protein by virtual screening, molecular docking, and molecular simulation approach.

Materials and Methods: In this study, we performed a subtractive genomics approach to identify the novel drug target for S.maltophilia. After obtaining the specific target, the next step was to identify inhibitors that include calculating 2D similarity search, molecular docking, and molecular simulation for drug development for S.maltophilia.

Results: With an efficient subtractive genomic approach, out of 4386 proteins, five unique targets were found, in which UDP-D-acetylmuramic (murF) was the most remarkable target. Further virtual screening, docking, and dynamics analyses resulted in the identification of seven novel inhibitors.

Conclusion: Further, in vitro and in vivo bioassay of the identified novel inhibitors could facilitate effective drug use against S.maltophilia.

Keywords: Stenotrophomonas maltophilia, subtractive genomics approach, in silico, homology modeling, docking, molecular dynamic simulation.

Graphical Abstract
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