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Bioinformatics SARS coronavirus main protease inhibitor - based design

Author: WangShuQing
Tutor: DuQiShi
School: Tianjin Normal University
Course: Physical and chemical
Keywords: Bioinformatics SARS coronavirus main protease Drug Design Inhibitors Chemically modified
CLC: TQ464
Type: Master's thesis
Year: 2005
Downloads: 148
Quote: 0
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Abstract


The life sciences have become a 21st century scientific development of cutting-edge field of the human genome project has been to enter the era of the genome, about structural genomics science and functional gene groups learn the research led the development of proteomics and metabolic group learn the birth of the bioinformatics, etc. related disciplines. Using bioinformatic knowledge, it has been possible to determine the protein coding genes in the nucleotide sequence of DNA, and the amino acid sequence of the protein, and thus to predict the three dimensional structure of the protein, and to determine the target of the drug molecules, and performed based on the molecular structure of the direct drug design. In the master's degree studies, I participated in the teacher-led research, learning bioinformatics basic theoretical knowledge, practical application experience. The nucleic acid and protein sequence and protein structure data is the main object of study of bioinformatics. Lagging behind the rapid development of sequencing technology and protein structure determination techniques, makes it the molecular database an amount of sequence data, the amount of data and the determination of the structure form a great contrast. Therefore, the theoretical prediction of protein structure is particularly important. I protein amino acid residues of the correlation analysis (AACA) participate in the Graduate Study. Become the basis of the method to the 20 kinds of amino acid residues in the protein percentage packet to identify a particular class of proteins of 20 amino acids in the correlation between the laws, as indicators of the protein type prediction, prediction of the type of the unknown protein. Research using this method the correlation coefficient of the 204 samples of the four types of protein in amino acid residues to identify related pairs can be used as an amino acid residue of the protein structure type characteristics, and for the type of prediction of the protein structure, for α 204 protein samples, β, α / β and α β protein cross-test, the correct rate of 94%, 89%, 79%, 89%, and an average of 88%, higher than the simple distance method and Euclidean distance method. I participated in a mentor-led anti-atypical pneumonia drug research, bioinformatics for the study of the SARS coronavirus main protease inhibitor drugs. In the coronavirus gene analysis software system ZCURVE-CoV 1.0 ZCURVE-CoV 2.0 (http://tubic.tju.edu.cn/sars/), analyzed the gene pool (NCBI RefSeq project) the 36 different sources of SARS the coronavirus RNA gene sequence to identify the main protease (CoV M pro ) 396 restriction sites in in poly the protein ppla and pplab. On this basis, to find 11 SARS coronavirus main protease can be cut octapeptide, SARS CoV M pro true because these eight peptides containing the cutting point, which is the development of SARS-CoV M pro peptide inhibitor of the appropriate starting point. Calculated octapeptide can be cut at specific sites R4, R3, R2, R1, and R1 'on the amino acid probability distribution, found loci R4 and R3 also have a certain degree of specificity. Analysis of these loci on the structural characteristics of amino acids and to determine the most promising as SARS CoV M pro the peptide inhibitors two octapeptide NH of 2 -ATLQ ↓ AIAS-COOH and NH 2 -ATLQ ↓ AENV-CDOH.

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