TrypsNetDB: An integrated framework for the functional characterization of trypanosomatid proteins

Area of Science:

• Parasitology
• Bioinformatics
• Genomics

Background:

• Trypanosomatid parasites cause severe human diseases and livestock losses.
• High genetic divergence hinders functional prediction of trypanosomatid proteins using homology-based methods.
• Many trypanosomatid proteins remain uncharacterized due to limited functional annotation.

Purpose of the Study:

• To develop TrypsNetDB, a web-based resource for functional annotation of trypanosomatid proteins.
• To provide insights into the biological roles of proteins across 16 trypanosomatid species/strains.
• To facilitate research on trypanosomatid biology and identify potential therapeutic targets.

Main Methods:

• Integrated multiple genome-wide and focused studies on trypanosomatid interactomes.
• Developed a web-based database (TrypsNetDB) for protein functional annotation.
• Implemented network visualization and analysis tools for biological contexts, pathways, and regulatory elements.

Main Results:

• TrypsNetDB integrates 101,187 protein-protein interactions among 13,395 trypanosomatid proteins.
• The database offers analysis of protein network responses in over 50 biological contexts.
• Provides enrichment analysis for biological terms, pathways, sequence signatures, and RNA regulatory elements.

Conclusions:

• TrypsNetDB serves as a valuable resource for the functional annotation of trypanosomatid proteins.
• The database facilitates a deeper understanding of trypanosomatid biology and protein functions.
• Enables exploration of protein interaction networks and their roles in various biological processes.