為了獲得the S protein of SARS_CoV and CD4之間的ligand-receptor binding的資料,確定兩者之間可能作用的胺基酸的範圍,和binding sites的有關資料,並希望這些資料能對製造 抗SARS 的要或者疫苗有所幫助。 本預測用各種生物資訊的工具,如找出consensus domain,homology search以及用AutoDocking sofewar來預測CD4 和S protein of SARS_CoV的interacting domains 和binding sites 又用各種生物資訊的工具預測出SARS_CoV S protein t對CD4可能的binding部分為 SARS_CoV S 蛋白質的 T1059—C1064結合到 CD4 的A126-F203 domain,對於這一結果,我們也以生物資訊的工具將它製圖出來。 CD4可能結合SARS_CoV S的蛋白質,這可能也和SARS的感染有關,這份報告可能供給我們一些設計醫療SARS的藥或疫苗有所幫助。
To obtain the information of ligand-receptor binding between the S protein of SARS_CoV and CD4, identify the possible interacting domains or motifies related to binding sites, and provide clues for studying the functions of SARS proteins and designing anti-SARS drugs and vaccines. We used the homology search, and multi-sequence alignment were used to predict CD4 related interacting domains and binding sites in the S protein of SARS_CoV. Molecular modeling and using AutoDock methods were employed to address the interaction feature between CD4 and S protein of SARS_CoV in validating the bioinformatics predictions. Possible binding sites in the SARS_CoV S protein to CD4 have been Mapped out by using bioinformatics analysis tools. The binding for one protein-protein interaction pair (T1059—C1064 motif of the SARS_CoV S protein to A126-F203 domain of CD4) has been simulated by molecular modeling and AutoDock software. CD4 may be a possible receptor of the SARS_CoV S protein, which may be associated with the SARS infection.This result may give us some methods to design anti-SARS drugs and vaccines.