A Comprehensive Bioinformatic Assessment of Different Signal Peptides for Secretory Expression of Human Growth Hormone in Escherichia Coli: An In Silico Study

Abstract

Background: Nowadays, by genetic engineering and bioinformatics, large scale production of pharmacological recombinant proteins in Escherichia coli (E. coli) bacteria, which has unique expression properties, becomes a routine and economic imperative. In this study, periplasmic production of human growth hormone was investigated using bioinformatics methods. Methods: The aim of this study was bioinformatic evaluation of 48 human signal peptides by reliable servers for expression analysis of human growth hormone in Escherichia coli. Accuracy and precision of 48 signal peptides were evaluated via powerful SignalP server. Physicochemical properties of remaining signal peptides were investigated using Genescript and Protparam servers. Solubility of protein, secretory activity of signal peptides after expression, and transmission mechanism of signal peptides were investigated using Solpro, ProtCompB and PRED-TAT, respectively. Findings: Theoretically, proline rich protein HaeIII subfamily 1 (PRH1), C10orf99, and prolactin-releasing hormone (PRLH) signal peptides were predicted as the most proper signal peptides in fusion of human growth hormone protein, respectively. Conclusion: Secretory expression instead of cytoplasmic expression provides benefits. This study results indicated that by examining different signal peptide sequences in fusion with human growth hormone protein, achieving signal peptides with potential and capability for high expression is possible. The accuracy of these results can be verified in future studies and experiments.

Keywords

• Escherichia coli
• Human growth hormone
• Periplasm
• Bioinformatics