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Title
Optimized Signal Peptide for Secretory Expression of Human Recombinant Somatropin in E. coli
Type of Research Article
Keywords
Human Somatropin, Signal peptide, E. coli, Secretary Expression
Abstract
The human somatropin is a single-chain polypeptide with a pivotal role in various biological processes. Although E. coli is considered as a preferred host for the production of human somatropin, the high expression of this protein in E. coli results in the accumulation of protein as inclusion bodies. Periplasmic expression using signal peptides could be used to overcome the formation of inclusion bodies; still, the efficiency of each of the signal peptides in periplasmic transportation is varied and often is protein specific. The present study aimed to use In-silico analysis to identify an appropriate signal peptide for the periplasmic expression of human somatropin in E. coli. Methods: A library containing 90 prokaryotic and eukaryotic signal peptides were collected from the signal peptide database, and each signal's characteristics and efficiency in connection with the target protein were analyzed by different software. The prediction of the secretory pathway and the cleavage position was determined by the signalP5 server. Physicochemical properties, including molecular weight, instability index, gravity, and aliphatic index, were investigated by protparam software. Results: The results of the present study showed that among all the signal peptides studied, five signal peptides ynfB, sfaS, lolA, glnH, and malE displayed high scores for periplasmic expression of human somatropin in E. coli, respectively. Conclusion: In conclusion, the results indicated that in-silico analysis could be used for the identification of suitable signal peptides for the periplasmic expression of proteins. Further laboratory studies can evaluate the accuracy of the results of insilico analysis.
Researchers (First Researcher)، safar farajnia (Second Researcher)، Davoud Farajzadeh (Third Researcher)، nasser pouladi (Fourth Researcher)، Neda Pourvatan (Fifth Researcher)، Mohammad Karbalaeimahdi (Not In First Six Researchers)، Fahime Shayegh (Not In First Six Researchers)، Maryam Arya (Not In First Six Researchers)