在人類基因定序計劃完成之後，已定序的蛋白質序列數目也在逐漸地增加.。因此，在這後基因體時代，了解蛋白質的功能、結構、如何運作，似乎也更加地重要且迫切。目前有很多現有的工具被用來分析蛋白質的功能與結構，例如：X-ray晶體繞射、核磁共振等，藉由蛋白質的結構，我們可以推測它們的功能與運作；但是這是相當沒有效率的，因為X-ray晶體繞射、核磁共振是相當耗時且昂貴的.
藉由適當的計算工具，我們可以獲得很多關於蛋白質結構、功能的資訊：一般而言，多條序列比對是最常被使用的方法之一；然而，這個方法並不是所有的蛋白質均適用，它的準確性受限於受試蛋白質之間的親疏遠近：演化距離愈小的蛋白質愈準確。因此本篇提出一個較不受限於蛋白質演化親疏的方法。這個演算法可以預測有功能的胺基酸候選者：給定一個目標蛋白質，將與該目標蛋白質有關的蛋白質(通常是同一個family或superfamily的蛋白質)，經過適當的分類，再利用最佳的3條序列比對，然後以Blosum62計分矩陣對每個目標蛋白質上的胺基酸交叉投票，最後票數愈高的胺基酸愈有可能是有功能的候選者。
最後，將這個方法應用到醯亞胺水解酵素與核醣核酸水解酵素家族上。 對於醯亞胺水解酵素，本篇提出的方法從519個胺基酸中，預測出10個可能的候選者；在這其中，有5個胺基酸與反應區中金屬的結合有關。另一方面，對於核醣核酸水解酵素家族裡的RNase3，我們也找出一個可能的候選者，並經由實驗證實該胺基酸確實與RNase3的毒性有關。利用這個方法，我們可以只藉由序列的資訊來預測與功能相關的胺基酸候選者，這樣可以幫助生物學家們更有效率且深入地研究他們所感興趣的蛋白質。

A lot of biological information bury in one protein, such as functions and active sites, could be available if the protein structure was known. However, it is inefficient and expensive for obtaining protein structures. Therefore, several methods, such as multiple sequence alignment (MSA), have been developed to detect important properties of proteins without structure information, but these do not always work. In this study, a simple method was designed to identify potentially critical residues for mammalian imidase and eosinophil cationic protein (ECP or RNase3) by sequence information alone. For rat imidase, 10 residues were identified by this method and were corresponded to a bacterial imidase crystal structure (1GKQ). Five residues, one lysine (Lys159), three histidines (His67, His69, His248) and one aspartate (Asp326) involved in metal coordinate in active site were identified. The other amino acid residues that might be important for the function or structure of mammalian imidase were also identified. On the other hand, for ECP, Pro3 was also identified to be critical for ECP’s toxicity, and it was also verified by the experimental result (unpublished data).

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