FireProtDB 2.0: large-scale manually curated database of the protein stability data

Area of Science:

• Biochemistry and Molecular Biology
• Computational Biology
• Biotechnology

Background:

• Thermostable proteins are vital for biomedical and biotechnological applications.
• Improving protein stability through lab experiments is costly and time-consuming.
• Computational methods offer a scalable alternative but require high-quality data.

Purpose of the Study:

• To present FireProtDB 2.0, an updated large-scale database for protein stability data.
• To expand the database's capacity for diverse mutation types and data formats.
• To improve data accessibility and usability in accordance with FAIR principles.

Main Methods:

• Aggregation of protein stability data from multiple sources.
• Implementation of a new data storage and maintenance scheme.
• Inclusion of absolute and relative data types for various protein constructs and mutations.

Main Results:

• The database size increased from 16,000 to nearly 5,500,000 experiments.
• Support for complex mutations (insertions, deletions, multiple-point) was added.
• The abstract scheme is fully expandable for new measurements and annotations.

Conclusions:

• FireProtDB 2.0 significantly enhances the availability of high-quality protein stability data.
• The expanded database supports more reliable computational prediction of protein stability.
• The updated structure and FAIR compliance facilitate data integration and reuse.