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EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities
Millions of protein sequences are being discovered at an incredible pace, representing an inexhaustible source of biocatalysts. Despite genomic databases growing exponentially, classical biochemical characterization techniques are time-demanding, cost-ineffective and low-throughput. Therefore, compu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319543/ https://www.ncbi.nlm.nih.gov/pubmed/32392342 http://dx.doi.org/10.1093/nar/gkaa372 |
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author | Hon, Jiri Borko, Simeon Stourac, Jan Prokop, Zbynek Zendulka, Jaroslav Bednar, David Martinek, Tomas Damborsky, Jiri |
author_facet | Hon, Jiri Borko, Simeon Stourac, Jan Prokop, Zbynek Zendulka, Jaroslav Bednar, David Martinek, Tomas Damborsky, Jiri |
author_sort | Hon, Jiri |
collection | PubMed |
description | Millions of protein sequences are being discovered at an incredible pace, representing an inexhaustible source of biocatalysts. Despite genomic databases growing exponentially, classical biochemical characterization techniques are time-demanding, cost-ineffective and low-throughput. Therefore, computational methods are being developed to explore the unmapped sequence space efficiently. Selection of putative enzymes for biochemical characterization based on rational and robust analysis of all available sequences remains an unsolved problem. To address this challenge, we have developed EnzymeMiner—a web server for automated screening and annotation of diverse family members that enables selection of hits for wet-lab experiments. EnzymeMiner prioritizes sequences that are more likely to preserve the catalytic activity and are heterologously expressible in a soluble form in Escherichia coli. The solubility prediction employs the in-house SoluProt predictor developed using machine learning. EnzymeMiner reduces the time devoted to data gathering, multi-step analysis, sequence prioritization and selection from days to hours. The successful use case for the haloalkane dehalogenase family is described in a comprehensive tutorial available on the EnzymeMiner web page. EnzymeMiner is a universal tool applicable to any enzyme family that provides an interactive and easy-to-use web interface freely available at https://loschmidt.chemi.muni.cz/enzymeminer/. |
format | Online Article Text |
id | pubmed-7319543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73195432020-07-01 EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities Hon, Jiri Borko, Simeon Stourac, Jan Prokop, Zbynek Zendulka, Jaroslav Bednar, David Martinek, Tomas Damborsky, Jiri Nucleic Acids Res Web Server Issue Millions of protein sequences are being discovered at an incredible pace, representing an inexhaustible source of biocatalysts. Despite genomic databases growing exponentially, classical biochemical characterization techniques are time-demanding, cost-ineffective and low-throughput. Therefore, computational methods are being developed to explore the unmapped sequence space efficiently. Selection of putative enzymes for biochemical characterization based on rational and robust analysis of all available sequences remains an unsolved problem. To address this challenge, we have developed EnzymeMiner—a web server for automated screening and annotation of diverse family members that enables selection of hits for wet-lab experiments. EnzymeMiner prioritizes sequences that are more likely to preserve the catalytic activity and are heterologously expressible in a soluble form in Escherichia coli. The solubility prediction employs the in-house SoluProt predictor developed using machine learning. EnzymeMiner reduces the time devoted to data gathering, multi-step analysis, sequence prioritization and selection from days to hours. The successful use case for the haloalkane dehalogenase family is described in a comprehensive tutorial available on the EnzymeMiner web page. EnzymeMiner is a universal tool applicable to any enzyme family that provides an interactive and easy-to-use web interface freely available at https://loschmidt.chemi.muni.cz/enzymeminer/. Oxford University Press 2020-07-02 2020-05-11 /pmc/articles/PMC7319543/ /pubmed/32392342 http://dx.doi.org/10.1093/nar/gkaa372 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Hon, Jiri Borko, Simeon Stourac, Jan Prokop, Zbynek Zendulka, Jaroslav Bednar, David Martinek, Tomas Damborsky, Jiri EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
title | EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
title_full | EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
title_fullStr | EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
title_full_unstemmed | EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
title_short | EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
title_sort | enzymeminer: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7319543/ https://www.ncbi.nlm.nih.gov/pubmed/32392342 http://dx.doi.org/10.1093/nar/gkaa372 |
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