Unique Peptide Identification of Rnasea Superfamily Sequences Based on Reinforced Merging Algorithms

نویسندگان

  • Tun-Wen Pai
  • Bo-Han Su
  • Pei-Chih Wu
  • Margaret Dah-Tsyr Chang
  • Hao-Teng Chang
  • Tan-Chi Fan
  • Shi-Hwei Liu
چکیده

Human ribonuclease A (RNaseA) superfamily consists of eight RNases with high similarity in which RNase2 and RNase3 share 76.7% identity. The evolutionary variation of RNases results in differential structures and functions of the enzymes. To distinguish the characteristics of each RNase, we developed reinforced merging algorithms (RMA) to rapidly identify the unique peptide motifs for each member of the highly conserved human RNaseA superfamily. Many motifs in RNase3 identified by RMA correlated well with the antigenic regions predicted by DNAStar. Two unique peptide motifs were experimentally confirmed to contain epitopes for monoclonal antibodies (mAbs) specifically against RNase3. Further analysis of homologous RNases in different species revealed that the unique peptide motifs were located at the correspondent positions, and one of these motifs indeed matched the epitope for a specific anti-bovine pancreatic RNaseA (bpRNaseA) antibody. Our method provides a useful tool for identification of unique peptide motifs for further experimental design. The RMA system is available and free for academic use at http://bioinfo.life.nthu.edu.tw/rma/ and http://spider.cs.ntou.edu.tw/bioinformatics/RMA.html.

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Unique peptide prediction of RNase family sequences based on reinforced merging algorithms

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عنوان ژورنال:
  • Journal of bioinformatics and computational biology

دوره 4 1  شماره 

صفحات  -

تاریخ انتشار 2006