In Silico comparison of Several Prokaryotic and Eukaryotic Signal Peptides for Secretory Production of Recombinant Human Endostatin in E. coli

Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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IBIS07_035

تاریخ نمایه سازی: 29 فروردین 1397

Abstract:

Endostatin is a valuable protein according to its angiogenesis inhibitory and antitumor activity. Recombinant Endostatin has been approved by Food and Drug Administration in china for treating non–small cell lung cancer (NSCLC) patients. It is generally accepted that secretory or extracellular production of recombinant proteins in bacterial hosts can increase the yield, facilitate downstream processing and reduce costs. Use of appropriate signal peptide is a main influential factor on the efficiency of the secretion.In this study, in order to select a suitable signal peptide for extracellular production of Endostatin in E. coli, ten different prokaryotic and eukaryotic signal peptides were added to the N-terminal part of Endostatin and evaluated in silico to estimate the efficacy of signal peptide in protein secretion and the accuracy of cleavage site. The prokaryotic signal peptides includes pectate lyase B , alkaline phosphatase A, outer membrane protein A, outer membrane protein F, outer membrane protein C, fimbrial chaperone SfmC and eukaryotic signal peptides including Cystatin-C, Lactotransferrin, Collagen alpha-1(XVIII) and erythropoietin. SignalP version 4.1 was applied for signal peptide prediction. The location of cleavage site was determined by both SignalP 4.1 and PrediSi servers. The physicochemical properties of the signal peptides were detected by ProtParam server. According to the results, signal peptides of the outer membrane protein F, the outer membrane protein C and the Lactotransferrin were the best theoretical candidates for the secretory production of recombinant human Endostatin. However, more experimental evaluations are needed to confirm the efficiency of these signal peptides

Authors

Sara Abdollahi-Kheirabadi

Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran

Amir Rahimi

Bioinformatics and Computational Biology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.