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DBT-NER Advanced Level Institutional Biotech Hub at Assam University, Silchar, Assam

Implementing Organization

Principal Investigator
Dr.Manabendra Dutta Choudhury
Assam University, Silchar, Assam
drmdc@bioinfoaus.ac.in
CO-Principal Investigator
Dr. Amitabha Bhattacharjee
Assam University, Silchar, Assam
ab0404@gmail.com

Project Overview

Irrational use of antibiotics has resulted in substantial stress on the target bacterium which in turn has led to the emergence of newer anti-microbial resistance mechanisms. Hence, newer and sustainable strategy formulation going beyond conventional one is the need of the hour. Anti-virulence strategy, a very recent concept, focuses on targeting virulence signaling pathway is a good option because expression of these traits is metabolically expensive and such gene expression is exquisitely regulated only during their colonization in the host. Silencing these traits can make the bacteria incapable of colonization and reduce invasiveness. As this strategy does not directly kill bacteria, there is less evolutionary pressure for the development of resistant phenotype. Opting for such strategies shall be a way forward in overcoming multi-drug resistance. Present work focuses on identification of anti-virulence markers in pathogenic strains using in silico, in vitro and in vivo approach.

Achievements

For Klebsiella pneumoniae, hypervirulence and hypermucoviscous genes rmpA, rmpA2 and iron acquisition gene, iroC were considered. In silico studies were performed to determine the best fit for these hypervirulence genes. Complete structures of rmp A, rmp A2 and iro C proteins were modeled using I - TASSER (https://zhanglab.ccmb.med.umich.edu/ITASSER/). Six natural compounds possessing anti - virulence properties were selected as ligands for docking analysis. Imipenem was used as positive control. The SMILES of ligands were extracted from PubChem (https://pubchem.ncbi.nlm.nih.gov/). Molegro Virtual Docker (MVD) was employed in order to find the best fit for the proteins under consideration. In case of all the 3 receptors, the computational model showed that Linoleic acid could effectively bind to the active sites and had the highest number of H-bonds for all the 3 receptors.

Source

Source
E-promis and Information received by Investigator
Funding Organization
Funding Organization
Department of Science and Technology (DBT)
Quick Information
Area of Research
Other Areas
Focus Area
Infrastructure Support
Start Date
06 Jan 2023
End Date
05 Jul 2026
Status
ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
00
Publications
01
No. of Patents
Filed : 00
Grant : 00
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