Abdorrasoul Malekpour1, Saeid Gholamzadeh1, Saeideh Zahedi1, Mohammad Zarenezhad1, Mojtaba Mortazavi2. 1Legal Medicine Research Center, Legal Medicine Organization of Iran, Tehran, Iran, 2Institute of Science and High Technology and Environmental Science, Graduate University of Advanced Technology, Kerman, Iran
Background and objectives: Hepatitis B as an infectious disease has eight main genotypes (A–H). The aim of this study is to identify rare codon clusters (RCC) in proteins structure of HBV.
Materials and Methods: For detection of Protein Family Accession Numbers (Pfam) of HBV proteins; UniProt database and Pfam search tool were used. Obtained Pfam IDs were analyzed in Sherlocc program and RCCs in HBV proteins were detected. Furthermore, the structures of TrEMBL entries proteins were studied in PDB database and 3D structures of the HBV proteins and locations of RCCs were visualized and studied using Swiss PDB Viewer software®.
Results: Pfam search tool have found nine significant hits and 0 insignificant hits in 3 frames. Results of Pfams studied in the Sherlocc program show this program not identified RCCs in the external core antigen (PF08290) and truncated HBeAg protein (PF08290). By contrast the RCCs were identified in hepatitis core antigen (PF00906), large envelope protein S (PF00695), X protein (PF00739), DNA polymerase (viral) N-terminal domain (PF00242) and protein P (Pf00336). In HBV genome, seven RCCs were identified in hepatitis core antigen, large envelope protein S and DNA polymerase proteins as well as protein structures of TrEMBL entries sequences found in Sherlocc program outputs are not complete.
Conclusion: Based on situation of RCCs detected in the structure of HBV proteins, it was found that mentioned RCCs are critical in HBV life cycle and can be considered as drug targets. The results of this study provide new and deep perspectives about structure of HBV proteins for further researches and designing new drugs for treatment of HBV.
Keywords: Codon, Hepatitis B virus, Computational Biology
Presented at the SAGES 2017 Annual Meeting in Houston, TX.
Abstract ID: 79282
Program Number: P442
Presentation Session: Poster (Non CME)
Presentation Type: Poster
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