Based On Bioinformatics Of Sars Coronavirus Main Protease Inhibitor Design

Life science is the leading branch in the 21^th century. The development in structural and functional genomics drives the Human Genome Project into the post-genome era. At the same time, new disciplines, such as proteomics and bioinformatics, are developing at high speed. A lot success from genic analysis to the prediction of 3D protein structure and in drug design using the biomolecules as the target has been achieved with the bioinformatics knowledge.The prime object of bioinformatics research is the sequence data of nucleic acids and amino acids in DNA and proteins. The sequence data in molecular database had come into being great contrast with the structure data on account of rapid development of sequencing technology and the comparatively lag of protein structure prediction technology. So it is important to predict protein structure in theory. We developed the predicted method using the correlation relationships among amino acid residues. This method is a branch of Chou and Fasman that was based on the compositions of amino acids in proteins. The amino acid correlation analysis (AACA) method was used in the predictions of α, β, α / β, and α + β protein classes, in total 204 proteins. The prediction accuracy are 94% (α-proteins), 89% (β-proteins), 79% (α/β-proteins) and 89% (α+β-proteins), much higher than the results of the simple distance method and the Euclidean distance method.Bioinformatics is a powerful tool for finding novel drug against SARS. In my thesis research the softwares, ZCURVE_CoV 1.0 and ZCURVE_CoV 2.0 (http://tubic.tju.edu.cn/sars/), developed recently for gene-annotation of SARS-coronavirus, are used to analyze the 36 complete SARS-Coronavirus RNA sequences in the gene bank NCBI (http://www.ncbi.nlm.nih.gov/) from different sources for protein coding genes, and to search for the cleavage sites of SARS-CoV M^pro in polyproteins pp1a and pp1ab. Total of 396 cleavage points are found in the 36 SARS-Coronavirus and 11 cleavable octapeptides are abstracted from the 396 cleavage sites. The statistical distributions of amino acids for the cleavable octapeptides at subsites are calculated. The cleavage specific positions are on R4, R3, R2, R1 and R1, and the positions R3 and R4 are featured by some certain specificity for SARS-CoV M^pro, too. The structural characters of amino acid residues around the cleavage-specific positions are...