GTExome: Modeling commonly expressed missense mutations in the human genome

Area of Science:

• Genomics
• Proteomics
• Bioinformatics

Background:

• Missense mutations are common genetic variations impacting protein function.
• Understanding mutation consequences requires integrating genomic and expression data.
• Existing tools may lack comprehensive analysis of mutation impact on protein structure and function.

Approach:

• Introduced GTExome, a web application integrating genomic mutation data with Genotype-Tissue Expression (GTEx) project data.
• Developed functionalities to identify, classify, and model missense mutations in commonly expressed human proteins.
• Incorporated detailed mutation consequence analysis, including effects on bonding, charge, and residue properties, and binding pocket assessment.

Key Points:

• GTExome categorizes mutations based on tissue-specific expression, enabling targeted analysis.
• Provides critical information on mutation-induced structural changes (e.g., bond disruption, charge alteration).
• Facilitates protein structure modeling using experimental or computational data (FASPR, AlphaFold) with confidence scores.

Conclusions:

• GTExome is an effective open-source tool for modeling missense mutations in human proteins.
• The tool facilitates studies of protein-protein and protein-drug interactions by providing structural insights.
• GTExome is freely available, promoting broader research in functional genomics and personalized medicine.