Abstract:
Biological databases in the past decade have tremendously grown in size. However, effective retrieval of these data is still a great challenge. In particular, we need a high-quality tool to measure similarity among protein sequences within the database. Current techniques in protein homology testing involve a 1-dimensional alignment of Nucleotide or Amino acid sequencing. Due to its various constraints and low sequence identity values, Hydrophobic Cluster Alignment has increasingly been used to predict the structure and functionality of protein. However, this Hydrophobic Cluster Alignment still needs to be done manually and solely depends on experience and expertise of a researcher. In this work, I implement a 2-D visualization tool for amino acid and 2-D Automatic hydrophobic cluster alignment tool. I propose a new protein representation that could be used effectively in our 2-D automatic Hydrophobic Cluster Alignment software. The 2-D alignment was performed on the amino acid sequences from the PIR database, the SISYPHUS Database, and HOMSTRAD Database. The results have demonstrated that the 2-D automatic hydrophobic cluster alignment is more accurate than the existing 1-D sequence alignment is.