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SoluProt: prediction of soluble protein expression in Escherichia coli
MOTIVATION: Poor protein solubility hinders the production of many therapeutic and industrially useful proteins. Experimental efforts to increase solubility are plagued by low success rates and often reduce biological activity. Computational prediction of protein expressibility and solubility in Esc...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034534/ https://www.ncbi.nlm.nih.gov/pubmed/33416864 http://dx.doi.org/10.1093/bioinformatics/btaa1102 |
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author | Hon, Jiri Marusiak, Martin Martinek, Tomas Kunka, Antonin Zendulka, Jaroslav Bednar, David Damborsky, Jiri |
author_facet | Hon, Jiri Marusiak, Martin Martinek, Tomas Kunka, Antonin Zendulka, Jaroslav Bednar, David Damborsky, Jiri |
author_sort | Hon, Jiri |
collection | PubMed |
description | MOTIVATION: Poor protein solubility hinders the production of many therapeutic and industrially useful proteins. Experimental efforts to increase solubility are plagued by low success rates and often reduce biological activity. Computational prediction of protein expressibility and solubility in Escherichia coli using only sequence information could reduce the cost of experimental studies by enabling prioritization of highly soluble proteins. RESULTS: A new tool for sequence-based prediction of soluble protein expression in E.coli, SoluProt, was created using the gradient boosting machine technique with the TargetTrack database as a training set. When evaluated against a balanced independent test set derived from the NESG database, SoluProt’s accuracy of 58.5% and AUC of 0.62 exceeded those of a suite of alternative solubility prediction tools. There is also evidence that it could significantly increase the success rate of experimental protein studies. SoluProt is freely available as a standalone program and a user-friendly webserver at https://loschmidt.chemi.muni.cz/soluprot/. AVAILABILITY AND IMPLEMENTATION: https://loschmidt.chemi.muni.cz/soluprot/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8034534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-80345342021-04-14 SoluProt: prediction of soluble protein expression in Escherichia coli Hon, Jiri Marusiak, Martin Martinek, Tomas Kunka, Antonin Zendulka, Jaroslav Bednar, David Damborsky, Jiri Bioinformatics Original Papers MOTIVATION: Poor protein solubility hinders the production of many therapeutic and industrially useful proteins. Experimental efforts to increase solubility are plagued by low success rates and often reduce biological activity. Computational prediction of protein expressibility and solubility in Escherichia coli using only sequence information could reduce the cost of experimental studies by enabling prioritization of highly soluble proteins. RESULTS: A new tool for sequence-based prediction of soluble protein expression in E.coli, SoluProt, was created using the gradient boosting machine technique with the TargetTrack database as a training set. When evaluated against a balanced independent test set derived from the NESG database, SoluProt’s accuracy of 58.5% and AUC of 0.62 exceeded those of a suite of alternative solubility prediction tools. There is also evidence that it could significantly increase the success rate of experimental protein studies. SoluProt is freely available as a standalone program and a user-friendly webserver at https://loschmidt.chemi.muni.cz/soluprot/. AVAILABILITY AND IMPLEMENTATION: https://loschmidt.chemi.muni.cz/soluprot/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-01-08 /pmc/articles/PMC8034534/ /pubmed/33416864 http://dx.doi.org/10.1093/bioinformatics/btaa1102 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Hon, Jiri Marusiak, Martin Martinek, Tomas Kunka, Antonin Zendulka, Jaroslav Bednar, David Damborsky, Jiri SoluProt: prediction of soluble protein expression in Escherichia coli |
title | SoluProt: prediction of soluble protein expression in Escherichia coli |
title_full | SoluProt: prediction of soluble protein expression in Escherichia coli |
title_fullStr | SoluProt: prediction of soluble protein expression in Escherichia coli |
title_full_unstemmed | SoluProt: prediction of soluble protein expression in Escherichia coli |
title_short | SoluProt: prediction of soluble protein expression in Escherichia coli |
title_sort | soluprot: prediction of soluble protein expression in escherichia coli |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034534/ https://www.ncbi.nlm.nih.gov/pubmed/33416864 http://dx.doi.org/10.1093/bioinformatics/btaa1102 |
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