Protein motif searching through similar enriched Parikh vector identification

Biological researches have shown that some protein regions sharing similar functions or structures have inversed-ordered or highly dispersed sequence similarities and some intra-sequence similarities such as palindrome repeats also play important roles in protein folding. The current protein analysis tools cannot detect these "nontraditional" similarities. Although some tools can be modified for searching intra-sequence inversed or forward ordered similarities, their maximally optimal path processes will miss many suboptimal biologically meaningful similarities. The similar enriched Parikh vector searching (SRPVS) algorithm searches similarities by separating the subsequence composition and order information. The SRPVS first breaks sequences into groups of predefined-sized subsequences, each represented by an enriched Parikh vector (RPV); then similar RPV pairs (SRPV) are searched in each nonoverlapping RPV pair based on various order restrictions - forward, inversed, or shuffled. In this study, SRPVS has been applied to the protein ligand motif finding and the intra-sequence protein inversed repeats finding.