MUSIL, Miloš, Jan ŠTOURAČ, Jaroslav BENDL, Jan BREZOVSKÝ, Zbyněk PROKOP, J. ZENDULKA, Tomáš MARTÍNEK, David BEDNÁŘ and Jiří DAMBORSKÝ. FireProt 1.0. 2017.
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Basic information
Original name FireProt 1.0
Authors MUSIL, Miloš (203 Czech Republic, belonging to the institution), Jan ŠTOURAČ (203 Czech Republic, belonging to the institution), Jaroslav BENDL (203 Czech Republic, belonging to the institution), Jan BREZOVSKÝ (203 Czech Republic, belonging to the institution), Zbyněk PROKOP (203 Czech Republic, belonging to the institution), J. ZENDULKA (203 Czech Republic), Tomáš MARTÍNEK (203 Czech Republic), David BEDNÁŘ (203 Czech Republic, belonging to the institution) and Jiří DAMBORSKÝ (203 Czech Republic, guarantor, belonging to the institution).
Edition 2017.
Other information
Original language English
Type of outcome Software
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/00216224:14310/17:00100360
Organization unit Faculty of Science
Keywords in English protein engineering; thermostable proteins; multiple-point mutant prediction; protein stability
Technical parameters licenční smlouva není uzavřená
Changed by Changed by: prof. Mgr. Jiří Damborský, Dr., učo 1441. Changed: 14/3/2018 11:06.
Abstract
FireProt is a web server for an automated design of thermostable mutants. The design of thermostable mutants is based on the integration of structural and evolutionary information obtained from several bioinformatics databases and computational tools. FireProt strategy combines energy- and evolution-based approaches together with several filters that accelerate the calculation by omitting potentially deleterious mutations. Within its workflow, FireProt integrates 16 computational tools, utilizing both sequence and structural information in the process. FireProt web server provides users with a one-stop-shop solution for the design of thermostable proteins, constructed by three distinct strategies: (i) evolution-based approach, utilizing back-to-consensus analysis; (ii) energy-based approach, using conservation, correlation and energy information and (iii) combined approach. Furthermore, the server allows users to include user-defined mutations into the constructed thermostable protein and generate corresponding sequences in the FASTA format. The results are visualized in the web browser in an intuitive and comprehensive way, allowing users to directly analyze the designed proteins.
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