FireProt: web server for automated design of thermostable proteins

. 2017 Jul 03 ; 45 (W1) : W393-W399.

Jazyk angličtina Země Anglie, Velká Británie Médium print

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid28449074

There is a continuous interest in increasing proteins stability to enhance their usability in numerous biomedical and biotechnological applications. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. Here, we present FireProt, a web server for the automated design of multiple-point thermostable mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen tools and three protein engineering strategies for making reliable protein designs. The server is complemented with interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable mutants. FireProt is freely available at http://loschmidt.chemi.muni.cz/fireprot.

Zobrazit více v PubMed

Modarres H.P., Mofrad M.R., Sanati-Nezhad A.. Protein thermostability engineering. RSC Adv. 2016; 6:115252–115270.

Ferdjani S., Ionita M., Roy B., Dion M., Djeghaba Z., Rabiller C., Tellier C.. Correlation between thermostability and stability of glycosidases in ionic liquid. Biotechnol. Lett. 2011; 33:1215–1219. PubMed

Wijma H.J., Floor R.J., Janssen D.B.. Structure- and sequence-analysis inspired engineering of proteins for enhanced thermostability. Curr. Opin. Struct. Biol. 2013; 23:588–594. PubMed

Gao D., Narasimhan D.L., Macdonald J., Brim R., Ko M.C., Landry D.W., Woods J.H., Sunahara R.K., Zhan C.G.. Thermostable variants of cocaine esterase for long-time protection against cocaine toxicity. Mol. Pharmacol. 2009; 75:318–323. PubMed PMC

Polizzi K.M., Bommarius A.S., Broering J.M., Chaparro-Riggers J.F.. Stability of biocatalysts. Curr. Opin. Chem. Biol. 2007; 11:220–225. PubMed

Gray K.A., Richardson T.H., Kretz K., Short J.M., Bartnek F., Knowles R., Kan L., Swanson P.E., Robertson D.E.. Rapid evolution of reversible denaturation and elevated melting temperature in a microbial haloalkane dehalogenase. Adv. Synth. Catal. 2001; 343:607–617.

Folkman L., Stantic B., Sattar A., Zhou Y.. EASE-MM: sequence-based prediction of mutation-induced stability changes with feature-based multiple models. J. Mol. Biol. 2016; 428:1394–1405. PubMed

Capriotti E., Fariselli P., Casadio R.. I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 2005; W306–W310. PubMed PMC

Pires D.E., Ascher D.B., Blundell T.L.. mCSM: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics. 2014; 30:335–342. PubMed PMC

Kellogg E.H., Leaver-Fay A., Baker D.. Role of conformational sampling in computing mutation-induced changes in protein structure and stability. Proteins. 2011; 79:830–838. PubMed PMC

Yin S., Ding F., Dokholyan N.V.. Modeling backbone flexibility improves protein stability estimation. Structure. 2007; 15:1567–1576. PubMed

Dehouck Y., Grosfils A., Folch B., Gilis D., Bogaerts P., Rooman M.. Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0. Bioinformatics. 2009; 25:2537–2543. PubMed

Guerois R., Nielsen J.E., Serrano L.. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J. Mol. Biol. 2002; 320:369–387. PubMed

Gumulya Y., Reetz M.T.. Enhancing the thermal robustness of an enzyme by directed evolution: least favorable starting points and inferior mutants can map superior evolutionary pathways. ChemBioChem. 2011; 12:2502–2510. PubMed

Bommarius A.S., Paye M.F.. Stabilizing biocatalysts. Chem. Soc. Rev. 2013; 42:6534–6565. PubMed

Bednar D., Beerens K., Sebestova E., Bendl J., Khare S., Chaloupkova R., Prokop Z., Brezovsky J., Baker D., Damborsky J.. FireProt: energy- and evolution-based computational design of thermostable multiple-point mutants. PLoS Comput. Biol. 2015; 11:e1004556. PubMed PMC

Goldenzweig A., Goldsmith M., Hill S.E., Gertman O., Laurino P., Ashani Y., Dym O., Unger T., Albeck S., Prilusky J. et al. . Automated structure- and sequence-based design of proteins for high bacterial expression and stability. Mol. Cell. 2016; 63:337–346. PubMed PMC

Camacho C., Coulouris G., Avagyan V., Ma N., Papadopoulos J., Bealer K., Madden T.L.. BLAST+: architecture and applications. BMC Bioinformatics. 2009; 10:421. PubMed PMC

Suzek B.E., Wang Y., Huang H., McGarvey P.B., Wu C.H.. UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics. 2015; 31:926–932. PubMed PMC

Edgar R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010; 26:2460–2461. PubMed

Sievers F., Wilm A., Dineen D., Gibson T.J., Karplus K., Li W., Lopez R., McWilliam H., Remmert M., Soding J. et al. . Fast, scalable generation of high-quality protein multiple sequence alignments using clustal omega. Mol. Syst. Biol. 2011; 7:539. PubMed PMC

Capra J.A., Singh M.. Predicting functionally important residues from sequence conservation. Bioinformatics. 2007; 23:1875–1882. PubMed

Kass I., Horovitz A.. Mapping pathways of allosteric communication in GroEL by analysis of correlated mutations. Proteins. 2002; 48:611–617. PubMed

Korber B.T.M., Farber R.M., Wolpert D.H., Lapedes A.S.. Covariation of mutations in the V3 loop of human immunodeficiency virus type 1 envelope protein: an information theoretic analysis. Proc. Natl. Acad. Sci. U.S.A. 1993; 90:7176–7180. PubMed PMC

Lee B.C., Kim D.. A new method for revealing correlated mutations under the structural and functional constraints in proteins. Bioinformatics. 2009; 25:2506–2513. PubMed

Weigt M., White R.A., Szurmant H., Hoch J.A., Hwa T.. Identification of direct residue contacts in protein–protein interaction by message passing. Proc. Natl. Acad. Sci. U.S.A. 2008; 106:67–72. PubMed PMC

Lockless S.W., Ranganathan R.. Evolutionarily conserved pathways of energetic connectivity in protein families. Science. 1999; 286:295–299. PubMed

Dekker J.P., Fodor A., Aldrich R.W., Yellen G.. A perturbation-based method for calculating explicit likelihood of evolutionary co-variance in multiple sequence alignments. Bioinformatics. 2004; 20:1565–1572. PubMed

Valencia A. Multiple sequence alignments as tools for protein structure and function prediction. Compar. Funct. Genomics. 2003; 4:424–427. PubMed PMC

Benner S.A., Gerloff D.. Patterns of divergence in homologous proteins as indicators of secondary and tertiary structure: a prediction of the structure of the catalytic domain of protein kinases. Adv. Enzyme Regul. 1991; 31:121–181. PubMed

Brenner S. The molecular evolution of genes and proteins: a tale of two serines. Nature. 1988; 334:528–530. PubMed

Cooperman B.S., Baykov A.A., Lahti R.. Evolutionary conservation of the active site of soluble inorganic pyrophosphatase. Trends Biochem. Sci. 1992; 17:262–266. PubMed

Howell N. Evolutionary conservation of protein regions in the protonmotive cytochrome b and their possible roles in redox catalysis. J. Mol. Evol. 1989; 29:157–169. PubMed

Gobel U., Sander C., Schneider R., Valencia A.. Correlated mutations and residue contacts in proteins. Proteins. 1994; 18:309–317. PubMed

Neher E. How frequent are correlated changes in families of protein sequences. Proc. Natl. Acad. Sci. U.S.A. 1994; 91:98–102. PubMed PMC

Taylor W.R., Hatrick K.. Compensating changes in protein multiple sequence alignments. Protein Eng. 1994; 7:341–348. PubMed

Bava K.A., Gromiha M.M., Uedaira H., Kitajima K., Sarai A.. ProTherm, version 4.0: thermodynamic database for proteins and mutants. Nucleic Acids Res. 2004; 32:D120–D121. PubMed PMC

Pucci F., Bourgeas R., Rooman M.. Predicting protein thermal stability changes upon point mutations using statistical potentials: introducing HoTMuSiC. Scientific Rep. 2016; 6:23257. PubMed PMC

Amin N., Liu A.D., Ramer S., Aehle W., Meijer D., Metin M., Wong S., Gualfetti P., Schellenberger V.. Construction of stabilized proteins by combinatorial consensus mutagenesis. Protein Eng. Des. Select. 2004; 17:787–793. PubMed

Lehmann M., Loch C., Middendorf A., Studer D., Lassen S.F., Pasamontes L., van Loon A.P., Wyss M.. The consensus concept for thermostability engineering of proteins: further proof of concept. Protein Eng. 2002; 15:403–411. PubMed

Pey A.L., Rodriguez-Larrea D., Bomke S., Dammers S., Godoy-Ruiz R., Garcia-Mira M.M., Sanchez-Ruiz J.M.. Engineering proteins with tunable thermodynamic and kinetic stabilities. Proteins. 2008; 71:165–174. PubMed

Sullivan B.J., Nguyen T., Durani V., Mathur D., Rojas S., Thomas M., Syu T., Magliery T.J.. Stabilizing proteins from sequence statistics: the interplay of conservation and correlation in triosephosphate isomerase stability. J. Mol. Biol. 2012; 420:384–399. PubMed PMC

Bendl J., Stourac J., Sebestova E., Vavra O., Musil M., Brezovsky J., Damborsky J.. HotSpot wizard 2.0: automated design of site-specific mutations and smart libraries in protein engineering. Nucleic Acids Res. 2016; 44:W479–W487. PubMed PMC

Floor R.J.1, Wijma H.J., Colpa D.I., Ramos-Silva A., Jekel P.A., Szymański W., Feringa B.L., Marrink S.J., Janssen D.B.. Computational library design for increasing haloalkane dehalogenase stability. ChemBioChem. 2014; 15:1660–1672. PubMed

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...