Peptide Pattern Recognition

The common microbial patterns render recognition by organisms and their self/ nonself recognition is based on innate mechanisms. The common microbial patterns include lipopolysaccharides (LPS), mannose, fucose, technoic acid and /V-formyl peptides. These common microbial patterns are called pattern recognition molecules (PRMs) or pattern recognition receptors (PRRs). 

Over the recent years, proteomic technologies evolved rapidly and now offer new perspectives in discovery of new cancer biomarkers based on the detection of low molecular weight proteins or peptides by MS. Two main peptidomic approaches are currently under investigation. These include pattern recognition and single/oligo biomarker detection. 

Both GTR and RTG are supergraphs. For example, cyclosporin A is a small peptide consisting of 11 residues. From its 2GF-COSY and TOCSY spectra, 11 ISNets have been found. After fuzzy graph pattern recognition, its GTR and RTG are generated as shown in Fig. 14. 

A third approach, pioneered by the group of Liebler [19, 34], involves a pattern recognition software called scoring algorithm for spectral analysis (SALSA) to search specific sequence motifs in the MS-MS data. Potential applications envisaged for SALSA include identification of specific protein modifications, e.g., PTM, identifications of peptides with common sequences, e.g., wild-type and mutant forms, and targeted analysis of isoforms and conformers in complex samples. 

White CR, Smythies LE, Crossman DK, Palgunachari MN, Anantharamaiah GM, Datta G (2012) Regulation of pattern recognition receptors by the apolipoprotein A-I mimetic peptide 4F. Arterioscler Thromb Vase Biol 32 2631-2639... 

PLS was frequently used to connect the variation in chemical stiucture of polypeptides to variation of their biological activities. Chemical stiucture of peptides were characterized by Zi, Z2 and Z3 deseriptors [45, 189, 209, 210] of their amino acid moieties. The PLS approach gave significant cross-vahdated predictions of the activities in most examples [191, 188, 189]. Sjostrom et al. [193] analysed the information content of signal peptide amino acid sequences fromproteins. Other applications are available in the hterature [45,61-64,192,222, 225-228]. The combined use of PLS and pattern recognition methods [229, 230] is reviewed in [183,194]. 

The pattern recognition of peptides and proteins has received increasing attention, due to the potential applications in the fields of proteomic, diagnostic or bioclinical analyses, of paramount importance in biological and medical research [71]. 

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