Abstract
Members of protein families often have highly conserved sequences; most of these sequences carry identical biological functions and possess similar three-dimensional structures. However, enzymes with high sequence identity may acquire differential functions other than the common catalytic ability. It is conceivable that each of their variable regions consists of a unique peptide motif (UPM), which selectively interacts with other cellular proteins, rendering additional biological activities. The ability to identify and localize such UPMs is paramount in recognizing the characteristic role of each member of a protein family. In this study, we have developed a reinforced merging algorithm (RMA) with which non-gapped UPMs were identified in a variety of query protein sequences including members of human ribonuclease A (RNaseA), epidermal growth factor receptor (EGFR), matrix metalloproteinase (MMP), Sma-and-Mad related protein (Smad), downstream of tyrosine kinase (DOK) and carboxypeptidase (CP) protein families. Cross species comparison of two homologous protein sets, RNaseAs and MsbAs, were also investigated. The UPMs identified by RMA generally occupy specific positions in the resolved three-dimensional structures, especially the loop regions on the structural surfaces. These motifs coincide with the recognition sites for antibodies, as the epitopes of five monoclonal antibodies, □RNase2, mAb 3C1, □MMP1, □MMP3 and □CPE, and three polyclonal antibodies, D112-P123 Ab, □ErbB2 N-term and □DOK2 were shown to overlap with the UPMs so mapped. Most of the UPMs were found to correlate well with the potential antigenic regions predicted by PROTEAN. Furthermore, via large scale analysis of an antibody database, an accuracy of 70% can be achieved in terms of mapping a UPM to an epitope. In addition, UPMs are found to correlate well with the regions for protein-protein, protein-cell, enzyme-substrate, and receptor-ligand interactions. Taken together, we have developed a novel, rapid and efficient methodology for identification of peptide fragments possessing uniqueness from members of protein families employing bioinformatics and molecular biological approaches. The correlation of UPMs with three-dimensional protein structures and functions is excellent such that potential epitopes and interacting motifs that distinguish different members of a protein family can be located.