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

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


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Computer Simulation
  • Databases, Genetic
  • Enzyme Stability / genetics*
  • Lyases / chemistry
  • Lyases / genetics
  • Lyases / metabolism
  • Models, Molecular
  • Point Mutation / genetics
  • Point Mutation / physiology*
  • Protein Engineering / methods*
  • Temperature


  • Lyases

Grants and funding

The work was supported by the Grant Agency of the Czech Republic (P503/12/0572; and the Czech Ministry of Education of the Czech Republic (LO1214 and LH14027; DBe received a Brno Ph.D. Talent Scholarship funded by the Brno City Municipality and his stay at Rutgers University was supported by European Regional Development Fund – project FNUSA-ICRC (CZ.1.05/1.1.00/02.0123;, European Social Fund and the state budget of the Czech Republic and project ICRC Human Bridge – "Support of Study Stays of Czech Researchers Abroad III: Young Talent Incubator" (CZ.1.07/2.3.00/20.0239; KB and JBr were supported by the “Employment of Best Young Scientists for International Cooperation Empowerment” (CZ.1.07/2.3.00/30.0037) project co-financed by the European Social Fund ( and the state budget of the Czech Republic ( The work of JBe was supported by the Research and Application of Advanced Methods in ICT project (FIT-S-14-2299; MetaCentrum and CERIT-SC are acknowledged for providing access to computing facilities (LM2010005 and CZ.1.05/3.2.00/08.0144; The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.