Proteome-Wide Detection and Annotation of Receptor Tyrosine Kinases (RTKs): RTK-PRED and the TyReK Database

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Receptor tyrosine kinases (RTKs) are crucial cell membrane proteins regulating vital cellular functions and signaling networks.
• RTK mutations are linked to various cancers and diseases, yet experimental studies are limited across species.
• A centralized database for RTK information (function, expression, interactions) is currently lacking.

Purpose of the Study:

• To develop a novel pipeline for identifying and classifying RTKs in eukaryotic organisms.
• To create a comprehensive relational database, TyReK-DB, for curated RTK information.
• To facilitate broader research into RTK roles in cellular processes and disease.

Main Methods:

• Utilized a novel RTK detection pipeline (RTK-PRED) combining profile Hidden Markov Models (HMMs) with transmembrane topology prediction.
• Applied RTK-PRED to all eukaryotic reference proteomes from the UniProt database.
• Collected and integrated RTK data from multiple sources to build the TyReK-DB.

Main Results:

• Identified and filtered a dataset of 20,478 potential RTKs from eukaryotic proteomes.
• Successfully created the relational Receptor Tyrosine Kinases Database (TyReK-DB).
• RTK-PRED demonstrated efficacy in identifying and classifying RTKs across diverse species.

Conclusions:

• The RTK-PRED pipeline and TyReK-DB provide a valuable resource for studying RTKs.
• This work addresses the gap in RTK knowledge across different eukaryotic species.
• The database will support future research on RTK function, evolution, and disease association.