Literature DB >> 29796003

Correlation Between Protein Primary Structure and Soluble Expression Level of HSA dAb in Escherichia coli.

Yankun Yang1,2, Guoqiang Liu1,2, Meng Liu2, Zhonghu Bai2,3, Xiuxia Liu2,3, Xiaofeng Dai2,3, Wenwen Guo3,4.   

Abstract

It is widely accepted that features such as pI, length, molecular mass and amino acid (AA) sequence have a significant influence on protein solubility. Here, we mainly focused on AA composition and explored those that most affected the soluble expression level of human serum albumin (HSA) domain antibody (dAb). The soluble expression and sequence of 65 dAb variants were analysed using clustering and linear modelling. Certain AAs significantly affected the soluble expression level of dAb, with the specific AA combinations being (S, R, N, D, Q), (G, R, C, N, S) and (R, S, G); these combinations respectively affected the dAb expression level in the broth supernatant, the level in the pellet lysate and total soluble dAb. Among the 20 AAs, R displayed a negative influence on the soluble expression level, whereas G and S showed positive effects. A linear model was built to predict the soluble expression level from the sequence; this model had a prediction accuracy of 80%. In summary, increasing the content of polar AAs, especially G and S, and decreasing the content of R, was helpful to improve the soluble expression level of HSA dAb.

Entities:  

Keywords:  Escherichia coli; domain antibody (dAb); heterologous protein soluble expression; linear modelling; primary structure

Year:  2018        PMID: 29796003      PMCID: PMC5956261          DOI: 10.17113/ftb.56.01.18.5445

Source DB:  PubMed          Journal:  Food Technol Biotechnol        ISSN: 1330-9862            Impact factor:   3.918


  25 in total

Review 1.  Domain antibodies: proteins for therapy.

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4.  Hydrophobicity of amino acid subgroups in proteins.

Authors:  G J Lesser; G D Rose
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Review 5.  Applications of single-chain variable fragment antibodies in therapeutics and diagnostics.

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6.  SOLpro: accurate sequence-based prediction of protein solubility.

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7.  Understanding the relationship between the primary structure of proteins and its propensity to be soluble on overexpression in Escherichia coli.

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8.  Protein production by auto-induction in high density shaking cultures.

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9.  High-throughput expression of C. elegans proteins.

Authors:  Chi-Hao Luan; Shihong Qiu; James B Finley; Mike Carson; Rita J Gray; Wenying Huang; David Johnson; Jun Tsao; Jérôme Reboul; Philippe Vaglio; David E Hill; Marc Vidal; Lawrence J Delucas; Ming Luo
Journal:  Genome Res       Date:  2004-10       Impact factor: 9.043

10.  Scoring function to predict solubility mutagenesis.

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