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2000
Volume 22, Issue 1
  • ISSN: 1875-6921
  • E-ISSN: 1875-6913

Abstract

Introduction

a gram-negative, facultative anaerobic coccobacillus, is a member of the family. It causes a variety of invasive and non-invasive bacterial infections known as infections. The increasing prevalence of antibiotic resistance highlights the need to identify novel therapeutic targets for treating infections. The emerging trends in the field of Pharmacoinformatics have aided in the prediction of novel putative therapeutic targets.

Objective

This study aims to identify novel putative therapeutic targets in using a subtractive genomic approach.

Methods

Subtractive Genomics, a simple yet powerful approach for the identification of novel therapeutic targets for bacterial pathogens, was employed in this study. The core proteome of 72 strains of was analysed through a multi-step filtration process to exclude the non-essential proteins and those homologous to the human proteome. Metabolic pathway analysis was conducted to identify pathogen-specific proteins, followed by druggability analysis and three-dimensional structure prediction.

Results and Discussion

On analysing the core proteome, 115 proteins were found to be unique and non-homologous to the human proteome. Further screening of these proteins led to the identification of 25 proteins involved in the 29 unique metabolic pathways of bacteria. Subsequent analysis finally resulted in the identification of five novel therapeutic targets for that are unique, non-homologous to the human proteome, essential for bacterial survival, and involved in unique metabolic pathways of bacteria.

Conclusion

This study successfully identified five novel therapeutic targets through subtractive genomics, contributing to the efforts against antimicrobial resistance in . Further experimental validation is necessary to strengthen these findings and advance therapeutic development.

© 2025 Bentham Science Publishers
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Computational Study for the Identification of Novel Therapeutic Targets in Haemophilus influenzae by Subtractive Genomics Approach
Curr. Pharm. and. Per. Med. 22, E18756921369289 (2025); https://doi.org/10.2174/0118756921369289250514051055
/content/journals/cppm/10.2174/0118756921369289250514051055
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  • Article Type:     Research Article
Keyword(s): antimicrobial resistance; Haemophilus influenzae; KEGG metabolic pathways; novel therapeutic targets; proteomic analysis; subtractive genomics

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