FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

Area of Science:

• Protein engineering
• Computational biology
• Biotechnology

Background:

• Increasing protein stability is crucial for applications like biocatalysis and therapeutics.
• Current methods like directed evolution are labor-intensive.
• Computational prediction of multiple stabilizing mutations is challenging due to potential antagonistic effects.

Purpose of the Study:

• To develop a robust computational strategy, FireProt, for predicting highly stable multiple-point protein mutants.
• To reduce the experimental screening required for protein stabilization.

Main Methods:

• FireProt combines energy- and evolution-based approaches with smart filtering.
• Identifies additive stabilizing mutations for enhanced protein thermostability.
• Validated against 656 mutations from the ProTherm database.

Main Results:

• FireProt successfully predicted stabilizing mutations for model enzymes.
• Thermostability of haloalkane dehalogenase (DhaA) increased by 24°C (ΔTm).
• Thermostability of γ-hexachlorocyclohexane dehydrochlorinase (LinA) increased by 21°C (ΔTm).

Conclusions:

• FireProt enables substantial increases in protein thermostability with minimal mutants.
• The method is applicable to any protein with available structure and homologous sequences.
• Facilitates rapid development of robust proteins for biomedical and biotechnological applications.