Publication details

SoluProt: prediction of soluble protein expression in Escherichia coli

Authors

HON Jiří MARUSIAK Martin MARTINEK Tomas KUNKA Antonín ZENDULKA Jaroslav BEDNÁŘ David DAMBORSKÝ Jiří

Year of publication 2021
Type Article in Periodical
Magazine / Source Bioinformatics
MU Faculty or unit

Faculty of Science

Citation
Web https://academic.oup.com/bioinformatics/article/37/1/23/6070085
Doi http://dx.doi.org/10.1093/bioinformatics/btaa1102
Keywords SOLUBILITY; WEBSERVER; TOPOLOGY; ACCURATE
Attached files
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.
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