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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
- Source :
- Combinatorial Chemistry & High Throughput Screening. 25:123-138
- Publication Year :
- 2021
- Publisher :
- Bentham Science Publishers Ltd., 2021.
-
Abstract
- 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, five unique targets as the impressive therapeutics founded out of 4386 protein genes. In which UDP-D-acetylmuramic (murF) was the most remarkable target. Further virtual screening, docking, and dynamics 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.
- Subjects :
- Virtual screening
Subtractive Hybridization Techniques
biology
Stenotrophomonas maltophilia
In silico
Organic Chemistry
Genomics
General Medicine
Computational biology
Molecular Dynamics Simulation
biology.organism_classification
Anti-Bacterial Agents
Computer Science Applications
Molecular Docking Simulation
Drug development
Docking (molecular)
Drug Discovery
Humans
Homology modeling
Target protein
Gram-Negative Bacterial Infections
Subjects
Details
- ISSN :
- 13862073
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- Combinatorial Chemistry & High Throughput Screening
- Accession number :
- edsair.doi.dedup.....655a7a3e86671b6e295718439981d172
- Full Text :
- https://doi.org/10.2174/1871520620666201123094330