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Updated: May 22, 2025
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
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PPI network identifies interacting pathogenic signaling pathways in Candida albicans
Deepanjan Chattopadhyay1, Sanjib Das1, Paromita Saha Mondal1
1Department of Molecular Biology and Biotechnology, University of Kalyani, Kalyani 741235, Nadia, West Bengal, India. sahatanima@yahoo.co.in.
Molecular Omics
|May 20, 2025
Summary
This study maps protein interactions in Candida albicans, identifying key hub proteins involved in fungal pathogenesis. Understanding these signaling pathways aids in developing targeted therapies against this opportunistic pathogen.
Area of Science:
- Mycology
- Bioinformatics
- Systems Biology
Background:
- Candida albicans is an opportunistic fungus causing various infections.
- It exists in yeast and hyphae forms, contributing to its virulence.
- Understanding its complex signaling pathways is crucial for therapeutic development.
Purpose of the Study:
- To construct and analyze a protein-protein interaction (PPI) network for Candida albicans.
- To identify key proteins and signaling pathways involved in fungal pathogenesis.
- To explore novel bioinformatics strategies for targeted therapeutic interventions.
Main Methods:
- Identified 20 signaling pathways and 177 proteins from Candida albicans.
- Constructed a protein-protein interaction (PPI) network.
- Performed network topology, modular, ontology, and functional enrichment analyses.
Main Results:
- The PPI network was biologically robust and scale-free.
- Identified 10 hub proteins crucial for pathogenesis and virulence.
- Discovered proteins associated with transcription regulation, plasma membrane, and nucleic acid binding.
- Highlighted involvement in oxidative phosphorylation and purine metabolism pathways.
Conclusions:
- The study elucidated the complex signaling network in Candida albicans.
- Identified key proteins and pathways offer potential targets for antifungal therapies.
- Bioinformatics approaches are valuable for understanding fungal pathogenesis.
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