ThermoMutDB: a thermodynamic database for missense mutations

Area of Science:

• Biochemistry
• Structural Biology
• Bioinformatics

Background:

• Proteins are dynamic structures sensitive to amino acid sequence changes.
• Predicting the effects of mutations on protein stability is crucial for research.

Purpose of the Study:

• To develop and evaluate methods for predicting protein mutation effects.
• To create a comprehensive, manually curated database of protein thermodynamic data.

Main Methods:

• Manual curation of experimental thermodynamic data for wild-type and mutant proteins.
• Data compilation including unfolding Gibbs free energy and melting temperature changes.
• Integration of experimental structural information with thermodynamic data.

Main Results:

• Developed ThermoMutDB, containing >14,669 experimental data points for protein thermodynamic parameters.
• Achieved an 83% increase in unique mutations compared to previous databases.
• Included thermodynamic data for 204 new proteins and corrected existing annotations.

Conclusions:

• ThermoMutDB significantly expands the available data for studying protein mutation effects.
• The database facilitates the development and validation of computational prediction methods.
• ThermoMutDB provides programmatic access and supports user contributions for ongoing data enrichment.