Publication Details
FireProt:Energy- and evolution-based computational design of thermostable multiple-point mutants
Beerens Koen, Ph.D. (LL)
Šebestová Eva, Mgr., Ph.D. (LL)
Bendl Jaroslav, Ing. (DIFS FIT BUT)
Khare Sagar, Ph.D. (RUTGERS)
Chaloupková Radka, Mgr., Ph.D. (LL)
Prokop Zbyněk, doc. RnDr., Ph.D. (LL)
Brezovský Jan, Mgr., Ph.D. (LL)
Baker David, prof., Ph.D. (UWASH)
Damborský Jiří, prof. Mgr., Dr. (LL)
protein stability
protein thermostability
improvement of enzymatic properties
multi-point mutants
There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nano-materials. 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, then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present a robust computational strategy for predicting highly stable multiple-point mutants, called FireProt, combining energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. We show that thermostability of the model enzyme haloalkane dehalogenase DhaA can be substantially increased (dTm , 24 o C) by constructing and characterizing as few as six multiple-point mutants. The method is generally applicable to all proteins with known tertiary structure and homologous sequences, and should facilitate rapid development of robust proteins for biomedical and biotechnological applications.
@ARTICLE{FITPUB10784, author = "David Bedn\'{a}\v{r} and Koen Beerens and Eva \v{S}ebestov\'{a} and Jaroslav Bendl and Sagar Khare and Radka Chaloupkov\'{a} and Zbyn\v{e}k Prokop and Jan Brezovsk\'{y} and David Baker and Ji\v{r}\'{i} Damborsk\'{y}", title = "FireProt:Energy- and evolution-based computational design of thermostable multiple-point mutants", pages = "1--20", journal = "PLoS Computational Biology", volume = 11, number = 11, year = 2015, ISSN = "1553-7358", doi = "10.1371/journal.pcbi.1004556", language = "english", url = "https://www.fit.vut.cz/research/publication/10784" }