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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F15%3A00063745" target="_blank" >RIV/00159816:_____/15:00063745 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1371/journal.pcbi.1004556" target="_blank" >http://dx.doi.org/10.1371/journal.pcbi.1004556</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pcbi.1004556" target="_blank" >10.1371/journal.pcbi.1004556</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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 dehalog

Název v anglickém jazyce

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

Popis výsledku anglicky

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 dehalog

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

CE - Biochemie

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.100%2F02%2F0123" target="_blank" >ED1.100/02/0123: Fakultní nemocnice u sv. Anny v Brně - Mezinárodní centrum klinického výzkumu (FNUSA - ICRC)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PLoS Computational Biology

ISSN

1553-7358

e-ISSN

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Svazek periodika

11

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

20

Strana od-do

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Kód UT WoS článku

000365801600026

EID výsledku v databázi Scopus

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