使用結構字元集的RNA三級結構比對與其軟體工具的開發

Abstract

近年來的研究顯示RNA 分子在細胞內有多樣且重要的生物功能。以演化的角度而言，RNA分子結構的保留性會比其分子序列訊息來的高而不容易改變，因此偵測RNA分子三維結構的相似度將有助於了解RNA分子本身的功能以及演化關係，而這些關係是無法單靠序列訊息就可以偵測出來的。然而，在目前存入PDB與NDB資料庫中RNA三維結構的數量愈來愈多且大小愈來愈大，這些都將造成人工方式去比較分析這些RNA三維結構的困難度。因此，開發出一個快速且精確的自動化工具程式就變得愈來愈重要。 在本研究中，我們利用向量量子化 (vector quantization) 的分群方法推導出一個含有23個核苷酸結構字元的結構字元集，接著利用此結構字元集將RNA 三維結構轉成一維的結構字元序列，最後再利用傳統的序列比對的方法來比較這些結構字元的一維序列，進而判斷出原RNA 分子三維結構的相似度。除此之外，根據上述的方法，我們也開發出一個稱之為SARSA的工具程式可供使用者作線上的分析。在SARSA中，我們提供了兩個工具：可比對兩個RNA三維結構的PARTS與可比對多個RNA三維結構的MARTS。特別的是在PARTS中，我們針對不同的應用實作出四種比對的方法：(1)用於判斷整個結構相似程度的全域比對；(2)用於偵測結構模組的半全域比對；(3)用在尋找相似子結構的區域比對；(4)可去除區域比對中馬賽克效應的正規化區域比對。PARTS與MARTS接受PDB格式的RNA三維結構作為輸入的資料，同時在輸出結果中，它們都提供圖形的顯示以便使用者可以目視、旋轉、放大與縮小所比對出來的RNA 三維的重疊結構。除此之外，我們的實驗結果也顯示出由PARTS產生的比對結果是可以與DIAL的結果相互比較的，而且PARTS的計算效能也優於DIAL。實際上在一些例子中，PARTS比DIAL更能夠產生出較正確的全域、半全域、與區域的兩兩比對結果。SARSA的工具可連結到以下網址使用http://bioalgorithm.life.nctu.edu.tw/SARSA/

Recently, it has become clear that RNA molecules have a variety of important biological functions in cells. Since structures are typically more evolutionarily conserved than sequences, detecting structural similarities among RNA three-dimensional (3D) structures can bring more significant insights into their functional and even evolutionary relationships that would not be detected by sequence information alone. However, the number and size of RNA 3D structures deposited in the PDB and NDB databases have been substantially and rapidly increasing recently, making it difficult and time-consuming to manually compare and analyze these RNA 3D structures. Therefore, it has become more and more crucial to develop automatic tools that are able to efficiently and accurately perform RNA structural comparison. In this study, we first use the vector quantization approach to derive a structural alphabet (SA) of 23 nucleotide conformations, and then transform RNA 3D structures into 1D sequences of SA letters, and finally utilize classical sequence alignment methods to compare these 1D SA-encoded sequences for determining their structural similarities. In addition, based on such an SA-based approach, we have developed a novel web-based tool, called SARSA, for public online analysis. In SARSA, we provide two RNA structural alignment tools, PARTS for pairwise alignment of RNA 3D structures and MARTS for multiple alignment of RNA 3D structures. Particularly in PARTS, we have implemented four kinds of pairwise alignments for a variety of practical applications: (a) global alignment for comparing whole structural similarity, (b) semiglobal alignment for detecting structural motifs, (c) local alignment for finding locally similar substructures, and (d) normalized local alignment for eliminating the mosaic effect of local alignment. Both tools in SARSA take as input RNA 3D structures in the PDB format and in their outputs provide graphical display that allows the user to visually view, rotate and enlarge the superposition of aligned RNA molecules. In addition, our experiments have shown that the pairwise alignments produced by our PARTS were comparable to those obtained by DIAL and the performance computation of PARTS was generally faster than that of DIAL. In some cases, our PARTS can actually produce more accurate global, semiglobal and local pairwise alignments when compared with DIAL. SARSA is available online at http://bioalgorithm.life.nctu.edu.tw/SARSA/.