Tumor Homing Peptides Repository Figure 2. Screenshot of major fields page of TumorHoPe. doi:10.1371/journal.pone.0035187.g002 peptide sequences in FASTA format for performing BLAST search against tumor homing peptides. Smith-Waterman Algorithm. In order to handle similarity search effectively in case of small peptides, we have integrated Smith-Waterman algorithm [20]. This option allows users to search tumor homing peptides in the database that are similar to their peptides. User can submit multiple peptide sequences in FASTA format. Identical Residues. In addition to BLAST and Smith- Waterman algorithm, a simple algorithm has been integrated called Identical Residues. It takes user defined peptide sequence and aligns it with each tumor homing peptide using overlapping approach (alignment without gap). It displays query and target sequence with a number of identical residues in two peptides. Peptide Mapping. It allows users to map tumor homing peptides on their peptide sequence. User may submit protein or polypeptide sequence on this page to identify segments that are identical to peptides in TumorHoPe. Results TumorHoPe contains 744 peptides in which 359 peptides have been collected from research publications and 253 peptides have been collected from patents. The rest 132 peptides have been collected from both research publications and patents. As shown in Figure 2, peptides target more than 20 types of tumors. For example, 282 peptides target breast tumor, 75 peptides target melanomas, and 60 peptides target prostate tumor. In this study, we have covered more than 70 types of cancer cell lines. A few cell lines are found to be targeted by a large number of homing peptides. For example, 151 peptides target MDA-MB cell line, 75 peptides target MCF cell line, and 49 peptides target SK-BR-3 cell line (column 2 of Figure 2). We have computed average amino acid composition of these peptides and observed that certain types of residues (Cys, Arg, Gly, Leu and Ser) are more abundant in tumor homing peptides (Figure 3A). We have also computed and plotted the average amino acid composition of equal number of proteins (744) extracted from SwissProt. As shown in Figure 3A, tumor homing peptides have relatively higher average composition of Arg, Cys and Trp compared to SwissProt sequences, while residues Gly and Leu are abundant in both the cases. As shown in Figure 3A, Cys residue has the highest average composition. This is unusual as composition of Cys residues is very low in natural proteins and peptides. We have further examined the homing peptides and found that a wide range of peptides are cyclic where start and end residues are cysteine. In order to avoid biasness in our analysis, we computed average amino acid composition of non-cyclic tumor homing peptides (cyclic peptides were removed). As shown in Figure 3A, the composition of Cys of non-cyclic peptides is lower than the composition of Cys in all tumor homing peptides, but still it is significantly higher than the composition of Cys in normal proteins (SwissProt proteins). In addition, composition of Arg is also found to be very high. This is in agreement with various studies, which showed that positively charged residues are usually preferred in homing peptides. We have also calculated the frequency of poly-Arg (RR, RRR and RRRR) in tumor homing peptides (data not shown). Only 30 peptides contain RR motif, while no peptide has RRR motif. Therefore, high average composition of Arg in tumor homing peptides is not due to the presence of poly-Arg peptides/motifs and it may be due to the presence of some common motifs like RGD, NGR, etc. which contain Arg. It is also observed that most of the peptides have 7, 9, 10 and 12 residues (Figure 3B). This could be due to the more frequent use of phage display libraries consisting of 7 mer/9 mer peptides. PLoS ONE | www.plosone.org 4 April 2012 | Volume 7 | Issue 4 | e35187