LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries
Enzymes are potent catalysts with high specificity and selectivity. To leverage nature's synthetic potential for industrial applications, various protein engineering techniques have emerged which allow to tailor the catalytic, biophysical, and molecular recognition properties of enzymes. Howeve...
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ftzhawzuerich:oai:digitalcollection.zhaw.ch:11475/29461 2024-09-09T19:36:05+00:00 LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries Patsch, David Eichenberger, Michael Voss, Moritz Bornscheuer, Uwe T. Buller, Rebecca M. 2023 application/pdf https://hdl.handle.net/11475/29461 https://doi.org/10.1016/j.csbj.2023.09.013 https://doi.org/10.21256/zhaw-29461 https://digitalcollection.zhaw.ch/handle/11475/29461 en eng Elsevier https://doi.org/10.1016/j.csbj.2023.09.013 https://doi.org/10.21256/zhaw-29461 doi:10.1016/j.csbj.2023.09.013 doi:10.21256/zhaw-29461 https://hdl.handle.net/11475/29461 https://digitalcollection.zhaw.ch/handle/11475/29461 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ ISSN:2001-0370 Computational and Structural Biotechnology Journal Bioinformatic tool Enzyme engineering Library design Sequence space info:eu-repo/classification/ddc/004 info:eu-repo/classification/ddc/660.6 info:eu-repo/semantics/article Beitrag in wissenschaftlicher Zeitschrift Text 2023 ftzhawzuerich https://doi.org/10.1016/j.csbj.2023.09.01310.21256/zhaw-29461 2024-06-17T23:44:43Z Enzymes are potent catalysts with high specificity and selectivity. To leverage nature's synthetic potential for industrial applications, various protein engineering techniques have emerged which allow to tailor the catalytic, biophysical, and molecular recognition properties of enzymes. However, the many possible ways a protein can be altered forces researchers to carefully balance between the exhaustiveness of an enzyme screening campaign and the required resources. Consequently, the optimal engineering strategy is often defined on a case-by-case basis. Strikingly, while predicting mutations that lead to an improved target function is challenging, here we show that the prediction and exclusion of deleterious mutations is a much more straightforward task as analyzed for an engineered carbonic acid anhydrase, a transaminase, a squalene-hopene cyclase and a Kemp eliminase. Combining such a pre-selection of allowed residues with advanced gene synthesis methods opens a path toward an efficient and generalizable library construction approach for protein engineering. To give researchers easy access to this methodology, we provide the website LibGENiE containing the bioinformatic tools for the library design workflow. Article in Journal/Newspaper Carbonic acid ZHAW digitalcollection (Repository of the Zurich University of Applied Sciences) |
institution |
Open Polar |
collection |
ZHAW digitalcollection (Repository of the Zurich University of Applied Sciences) |
op_collection_id |
ftzhawzuerich |
language |
English |
topic |
Bioinformatic tool Enzyme engineering Library design Sequence space info:eu-repo/classification/ddc/004 info:eu-repo/classification/ddc/660.6 |
spellingShingle |
Bioinformatic tool Enzyme engineering Library design Sequence space info:eu-repo/classification/ddc/004 info:eu-repo/classification/ddc/660.6 Patsch, David Eichenberger, Michael Voss, Moritz Bornscheuer, Uwe T. Buller, Rebecca M. LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
topic_facet |
Bioinformatic tool Enzyme engineering Library design Sequence space info:eu-repo/classification/ddc/004 info:eu-repo/classification/ddc/660.6 |
description |
Enzymes are potent catalysts with high specificity and selectivity. To leverage nature's synthetic potential for industrial applications, various protein engineering techniques have emerged which allow to tailor the catalytic, biophysical, and molecular recognition properties of enzymes. However, the many possible ways a protein can be altered forces researchers to carefully balance between the exhaustiveness of an enzyme screening campaign and the required resources. Consequently, the optimal engineering strategy is often defined on a case-by-case basis. Strikingly, while predicting mutations that lead to an improved target function is challenging, here we show that the prediction and exclusion of deleterious mutations is a much more straightforward task as analyzed for an engineered carbonic acid anhydrase, a transaminase, a squalene-hopene cyclase and a Kemp eliminase. Combining such a pre-selection of allowed residues with advanced gene synthesis methods opens a path toward an efficient and generalizable library construction approach for protein engineering. To give researchers easy access to this methodology, we provide the website LibGENiE containing the bioinformatic tools for the library design workflow. |
format |
Article in Journal/Newspaper |
author |
Patsch, David Eichenberger, Michael Voss, Moritz Bornscheuer, Uwe T. Buller, Rebecca M. |
author_facet |
Patsch, David Eichenberger, Michael Voss, Moritz Bornscheuer, Uwe T. Buller, Rebecca M. |
author_sort |
Patsch, David |
title |
LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
title_short |
LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
title_full |
LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
title_fullStr |
LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
title_full_unstemmed |
LibGENiE : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
title_sort |
libgenie : a bioinformatic pipeline for the design of information-enriched enzyme libraries |
publisher |
Elsevier |
publishDate |
2023 |
url |
https://hdl.handle.net/11475/29461 https://doi.org/10.1016/j.csbj.2023.09.013 https://doi.org/10.21256/zhaw-29461 https://digitalcollection.zhaw.ch/handle/11475/29461 |
genre |
Carbonic acid |
genre_facet |
Carbonic acid |
op_source |
ISSN:2001-0370 Computational and Structural Biotechnology Journal |
op_relation |
https://doi.org/10.1016/j.csbj.2023.09.013 https://doi.org/10.21256/zhaw-29461 doi:10.1016/j.csbj.2023.09.013 doi:10.21256/zhaw-29461 https://hdl.handle.net/11475/29461 https://digitalcollection.zhaw.ch/handle/11475/29461 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1016/j.csbj.2023.09.01310.21256/zhaw-29461 |
_version_ |
1809905354264281088 |