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PLoS Comput Biol. 2015 Nov 3;11(11):e1004556. doi: 10.1371/journal.pcbi.1004556. eCollection 2015 Nov.

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

Author information

1
Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic.
2
Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic.
3
Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic; Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic.
4
Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey, United States of America.
5
Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Masaryk University, Brno, Czech Republic; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic; Enantis, Ltd., Brno, Czech Republic.
6
Department of Biochemistry, University of Washington, Seattle, Washington, United States of America.

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.

PMID:
26529612
PMCID:
PMC4631455
DOI:
10.1371/journal.pcbi.1004556
[Indexed for MEDLINE]
Free PMC Article

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