FusionPDB: a knowledgebase of human fusion proteins

Area of Science:

• Computational biology and bioinformatics
• Structural biology
• Cancer genomics

Background:

• Fusion proteins, resulting from gene fusions, play significant roles in tumorigenesis and other cellular processes.
• Targeting fusion proteins offers therapeutic potential, but a lack of sequence and structural data hinders drug development.
• Existing resources lack comprehensive information on the complete sequences and 3D structures of human fusion proteins.

Purpose of the Study:

• To develop a computational pipeline and resource for human fusion proteins.
• To provide comprehensive data on human fusion protein sequences and 3D structures.
• To facilitate the development of targeted therapeutic strategies against fusion proteins.

Main Methods:

• Development of a computational pipeline for identifying and analyzing fusion proteins.
• Creation of FusionPDB, a curated database of human fusion protein sequences and 3D structures.
• Integration of protein structure prediction, quality assessment (pLDDT scores), and virtual screening data.

Main Results:

• FusionPDB contains over 43,000 fusion protein sequences, including 14,700 in-frame fusion genes.
• The database includes over 3,500 unique fusion protein 3D structures.
• pLDDT score analysis and virtual screening outcomes are provided for selected fusion proteins.

Conclusions:

• FusionPDB is a unique resource offering complete 3D structures and comprehensive data on human fusion proteins.
• This resource addresses critical knowledge gaps, enabling further research and development of targeted therapeutics.
• FusionPDB will be continuously updated to encompass all human fusion proteins.