Publication result detail

SoluProt: prediction of soluble protein expression in Escherichia coli

HON, J.; MARUŠIAK, M.; MARTÍNEK, T.; KUNKA, A.; ZENDULKA, J.; BEDNÁŘ, D.; DAMBORSKÝ, J.

Original Title

SoluProt: prediction of soluble protein expression in Escherichia coli

English Title

SoluProt: prediction of soluble protein expression in Escherichia coli

Type

WoS Article

Original Abstract

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 prioritisation of highly soluble proteins.
Results: A new tool for sequence-based prediction of soluble protein expression in Escherichia 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, SoluProts accuracy of 58.4% and AUC of 0.60 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/.

English abstract

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 prioritisation of highly soluble proteins.
Results: A new tool for sequence-based prediction of soluble protein expression in Escherichia 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, SoluProts accuracy of 58.4% and AUC of 0.60 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/.

Keywords

protein solubility, machine-learning

Key words in English

protein solubility, machine-learning

Authors

HON, J.; MARUŠIAK, M.; MARTÍNEK, T.; KUNKA, A.; ZENDULKA, J.; BEDNÁŘ, D.; DAMBORSKÝ, J.

RIV year

2022

Released

01.01.2021

ISBN

1367-4803

Periodical

BIOINFORMATICS

Volume

37

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

23

Pages to

28

Pages count

6

URL

https://www.fit.vut.cz/research/publication/12368/

BibTex

@article{BUT168540,
  author="Jiří {Hon} and Martin {Marušiak} and Tomáš {Martínek} and Antonín {Kunka} and Jaroslav {Zendulka} and David {Bednář} and Jiří {Damborský}",
  title="SoluProt: prediction of soluble protein expression in Escherichia coli",
  journal="BIOINFORMATICS",
  year="2021",
  volume="37",
  number="1",
  pages="23--28",
  doi="10.1093/bioinformatics/btaa1102",
  issn="1367-4803",
  url="https://www.fit.vut.cz/research/publication/12368/"
}

Documents

SolutProt_Martinek_clanek
SoluProt_Martinek_popis
SoluProt r1
SoluProt SI r1