year 19, Issue 1 (January - February 2025)
Iran J Med Microbiol 2025, 19(1): 2-2 |
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Nawan N, Handayani S, Immanuela Toemon A. Bioinformatic Analysis of Dihomo-γ-linolenic Acid (DGLA) Targeting Virulence Factors in Bacteria Causing Infectious Diseases. Iran J Med Microbiol 2025; 19 (1) :2-2
URL: http://ijmm.ir/article-1-2520-en.html
URL: http://ijmm.ir/article-1-2520-en.html
1- Departement of Microbiology, Faculty of Medicine, University of Palangka Raya, Palangkaraya, Indonesia , nawan@med.upr.ac.id
2- Departement of Biochemistry, Faculty of Medicine, University of Palangka Raya, Palangkaraya, Indonesia
3- Departement of Parasitology, Faculty of Medicine, University of Palangka Raya, Palangkaraya, Indonesia
2- Departement of Biochemistry, Faculty of Medicine, University of Palangka Raya, Palangkaraya, Indonesia
3- Departement of Parasitology, Faculty of Medicine, University of Palangka Raya, Palangkaraya, Indonesia
Abstract: (137 Views)
Background and Objective: Some bacteria, including Staphylococcus aureus (S. aureus), Pseudomonas aeruginosa (P. aeruginosa), and Streptococcus pyogenes (S. pyogenes), contribute to the development of infectious diseases. Bacterial diseases are becoming more common due to the increasing resistance of microorganisms to various antibiotics. The global health community grapples with a major challenge posed by the increasing prevalence of antibiotic resistance. As a result, there’s a need for novel therapies to replace ineffective antimicrobial drugs. Streptomyces, known for its abundant production of natural compounds, plays a significant role in the arsenal of antimicrobial agents. Dihomo-γ-linolenic acid (DGLA) shows potential as a novel antibacterial compound derived from Streptomyces actinomycinicus (S. actinomycinicus) PJ85. The study investigated bioinformatically how DGLA impacts the virulence factors of S. aureus, P. aeruginosa, and S. pyogenes.
Methods: The study examined the interaction of DGLA with virulence factors of the mentioned bacteria using STITCH v5.0 for protein-compound interactions. Functional classification of targeted proteins was done using VICMPred, while VirulentPred 2.0 assessed their virulence properties. BepiPred v.2 was used for B cell epitope analysis, and PSORTb v.3 for subcellular protein localization.
Results: Based on the analysis results, various virulent proteins from organisms interact with DGLA. For instance, in S. aureus COL, we find epiP. In P. aeruginosa, proteins such as PA5371, tesB, PA3829, PA3741, and PA2168 are involved. Additionally, S. pyogenes features scpA15, SPy_0843, and cepA.” Moreover, the characteristics or properties of these proteins were also identified.
Conclusion: DGLA has a significant impact on virulence factors by interacting with various proteins from S. aureus, P. aeruginosa, and S. pyogenes, as evidenced by bioinformatics analysis.
Keywords: DGLA, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus pyogenes, Bioinformatics, Antibiotic Resistance
Type of Study: Original Research Article |
Subject:
Microbial Bioinformatics
Received: 2024/12/12 | Accepted: 2025/03/13 | ePublished: 2025/03/30
Received: 2024/12/12 | Accepted: 2025/03/13 | ePublished: 2025/03/30
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