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• W2015185330 abstract "Recombinant protein technology is essential for conducting protein science and using proteins as materials in pharmaceutical or industrial applications. Although obtaining soluble proteins is still a major experimental obstacle, knowledge about protein expression/solubility under standard conditions may increase the efficiency and reduce the cost of proteomics studies. In this study, we present a computational approach to estimate the probability of protein expression and solubility for two different protein expression systems: in vivo Escherichia coli and wheat germ cell-free, from only the sequence information. It implements two kinds of methods: a sequence/predicted structural property-based method that uses both the sequence and predicted structural features, and a sequence pattern-based method that utilizes the occurrence frequencies of sequence patterns. In the benchmark test, the proposed methods obtained F-scores of around 70%, and outperformed publicly available servers. Applying the proposed methods to genomic data revealed that proteins associated with translation or transcription have a strong tendency to be expressed as soluble proteins by the in vivo E. coli expression system. The sequence pattern-based method also has the potential to indicate a candidate region for modification, to increase protein solubility. All methods are available for free at the ESPRESSO server (http://mbs.cbrc.jp/ESPRESSO)." @default.
• W2015185330 created "2016-06-24" @default.
• W2015185330 creator A5039198984 @default.
• W2015185330 creator A5082723449 @default.
• W2015185330 date "2013-04-18" @default.
• W2015185330 modified "2023-09-27" @default.
• W2015185330 title "ESPRESSO: A system for estimating protein expression and solubility in protein expression systems" @default.
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• W2015185330 doi "https://doi.org/10.1002/pmic.201200175" @default.
• W2015185330 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23436767" @default.
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