Ali Forouharmehr, Mohammadreza Nassiri*, Shahrokh Ghovvati and Ali Javadmanesh Pages 24 - 33 ( 10 )
Background: Prokaryotic systems such as E. coli are among the most affordable and simplest hosts which are being employed to express recombinant proteins, nevertheless without appropriate signal peptide these systems cannot be used for secretory proteins. Bovine pancreatic ribonuclease A is a protein with four disulfide bonds which might be used as an immunoenzyme for immunotherapy. Consequently, the production of this recombinant protein, using prokaryotic system, requires a suitable signal peptide to protect disulfide bonds and to prevent misfolding.
Objective: This study was designed to predict the best signal peptides to express bovine pancreatic ribonuclease A protein in E. coli.
Method: In this study, 42 signal sequences were selected from data bases and the most important features of them were evaluated. First, n, h and c regions of signal peptides and their probability were investigated by signalP software’s version 4.1. Then, physico-chemical features of them were evaluated by Portparam and SOLpro. Also, secretion sorting and sub-cellular localization sites were evaluated by PRED-TAT and ProtcompB software programs.
Results: The results showed that among all studied signal peptides only 28 out of 41 remained signal peptides could be considered as appropriate secretory signal peptides.
Conclusion: Finally, Phage shock protein E, ranked as the best signal peptide and after that, pectate lyase B, F41 fimbrial protein and Lipopolysaccharide export system protein lptA considered as the next best signal peptides which were approved by in silico tools as the most appropriate secretory signal peptides in E. coli. However, further experiments are required to validate these in silico results.
Bacterial system, bioinformatics, bovine pancreatic ribonuclease A, E. coli, In silico, signal peptide.
Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Department of Biotechnology, Faculty of Agriculture, University of Guilan, Rasht, Guilan, P.O. Box: 41635-1314, Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad