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

Authors

Bednar, D., Beerens, K., Sebestova, E., Bendl, J., Khare, S., Chaloupkova, R., Prokop, Z., Brezovsky, J., Baker, D., Damborsky, J.

Source

PLOS COMPUTATIONAL BIOLOGY 11: e1004556 (2015)

Abstract

There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt’s reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

Full text

Citation

Bednar, D., Beerens, K., Sebestova, E., Bendl, J., Khare, S., Chaloupkova, R., Prokop, Z., Brezovsky, J., Baker, D., Damborsky, J., 2015: FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants. PLOS Computational Biology 11: e1004556.

Laboratory growing international
G. Dankova and A. Kunka awarded Brno Ph.D. Talent
Jaroslav Bendl, Ph.D.: From Loschmidt Laboratories to Mount Sinai School of Medicine in New York
Open Postdoc Position: Bioinformatics & Modeling
Open Postdoc Position / Senior Scientist: Structural Biology
New Collaboration Stanford University
New Advisor