The use of targeted therapy nowadays has become to an interesting method of research in the field of cancer treatment.¹⁸ TRAIL ligand is an important factor in this field due to its exclusive impact in inducing apoptosis of cancer cells, and many studies are performing in this regard.¹⁹ Although E. coli is the best host for production of this protein due to its relatively simple structure, its production within the cell results in an insoluble form and in order to have biological effects, it requires different refolding steps.²⁰ Transfer of the protein into the periplasmic space is an important way to reduce this problem. However, secretion of a protein into the periplasmic space is a highly coordinated process among different cell components. Selection of an appropriate signal peptide is one of the important factors in this regard. Since random selection of a signal peptide is time-consuming and costly, it seems reasonable to use appropriate methods for prediction of the process in order to save time and money. The use of bioinformatics powerful tools to predict a physiological phenomenon has become a widely used method in different fields of biology²¹. Accordingly, different servers were used in this study to evaluate the physicochemical properties of 26 common signal peptides and their impact on the secretion of TRAIL in E. coli.

The signal peptides were evaluated based on characteristics such as net positive charge, theoretical pI, molecular weight, hydrophobicity, as well as its stability in connection with TRAIL.  Prediction of the exact site of cleavage by signal peptidase enzyme is important for evaluation of secretive structure. Using SignalP server, it was found that Bla, gIII, LPP, npr, OmpT, TolB, and TorA signal peptides bound to TRAIL sequence are not cut properly and thus they were excluded from the study. The structure of signal peptides has an enormous effect on their efficiency.²² Positively charged amino acids are important elements in n-region of signal peptides, so that replacing these amino acids with negatively charged or uncharged amino acids decreases sharply the performance of signal peptides in secretion of the desired protein. It seems that these amino acids are necessary for interaction of the signal peptide with negatively charged phospholipids of the cell membrane. Most signal peptides in the present study had two positive charges in n-region. Hydrophobicity of signal peptides is another important factor in their performance. The higher the hydrophobicity and the longer the length of h-region, the greater will be the efficiency of signal peptide. These hydrophobic amino acids are required for interaction of signal peptides with the hydrophobic area of the membrane. The hydrophobicity of signal peptides was evaluated by aliphatic index and GRAVY, and according to Table 3, the highest hydrophobicity was seen in SfmC, OmpC, and DsbA signal peptides. Proper and high secretion of a protein greatly depends on efficiency of cleavage of signal peptide by signal peptidase. Presence of AXA motif in c-region immediately upstream of signal peptide cleavage site is crucial for cutting of signal peptides. In this motif, there are small and neutral amino acids such as alanine, glycine, and serine in positions 1 and 3, but position 2 includes bulky amino acids. As in Table 2, this motif is seen in all signal peptides. However, among various physicochemical factors associated with signal peptides, positive charge in n-region and length and amount of hydrophobicity of c-region are the most important factors.²² The positive charge was +2 among most of signal peptides and D-score had no significant difference between them. Therefore, length and hydrophobicity of h-region is the basis of selection of a suitable signal peptide. Accordingly, SfmC, OmpC, DsbA, and PhoA signal peptides had the highest impact and Endoxylanase, LivK, L-Asparaginase, and Pac signal peptides had the lowest effect on the secretion of TRAIL. Since, as far as we know, there were no studies to evaluate TRAIL secretion with signal peptides such as SfmC, OmpC, and DsbA, these signal peptides can be good candidates for such studies. The results of this study are consistent with in silico studies regarding secretion of growth hormone in E. coli.²³ Although the use of signal peptide PhoA proposed in this study is consistent with the performed empirical test,²⁴ other tests with OmpA signal peptide, which was not a candidate in this study, had also good results.²⁵ Thus, despite the advantages of bioinformatics tools for selecting a signal peptide, practical evaluation of the selected signal peptides is also required.