利用RNA二級與三級結構資訊識別RNA結構模體

Abstract

近年來，ncRNA這種不會轉譯成蛋白質的RNA分子在生物領域越來越受重視。他們在細胞內扮演許多重要的角色，包括基因調控、RNA的修改與參與染色體的複製等等。生物學家在PDB資料庫的RNA結構中發現有許多反覆出現的相似子結構，這些相似的子結構就被稱為RNA結構模體。許多研究也已經證明了這些RNA結構模體通常具有特定的功能。然而，把結構模體從PDB資料庫中的RNA結構準確地辨識出來仍是一件具有挑戰性的工作。RNAMotifScan這個工具是利用一維序列與二級結構資訊進行序列比對以找出在一個給定的RNA結構中的一個特定RNA結構模體。但是，RNA的一維序列在演化上比RNA二級與三級結構較不具有保守性，這意味著一維序列在辨識RNA結構模體的用處比不上二級與三級結構。在本論文中，我們使用先前所發展的結構字元將RNA三級結構編碼成一維結構序列，並且進一步修改RNAMotifScan程式使得修改後的RNAMotifScan能以RNA的鹼基對（即二級結構資訊）與一維結構序列（即三級結構資訊）來辨識RNA結構模體。最後，我們的實驗結果顯示上述的方法確實能夠進一步地改善原本的RNAMotifScan在辨識RNA結構模體的執行效能。

In recent years, the non-coding RNAs (ncRNAs) whose transcripts are not translated into proteins are becoming more and more important in the biology. They play essential roles in many cellular processes, such as gene regulation, RNA modification and chromosome replication. Biologists found that there were many recurrent conserved substructures, called RNA structural motifs, in the RNA structures currently deposited in the PDB database. Many studies have also shown that the RNA structural motifs usually have specific functions. However, it remains a challenging task to accurately identify them from the RNA structures in the PDB database. RNAMotifScan is an alignment-based tool for identifying a specified RNA structural motif from a given RNA structure by considering both the primary sequence (1D) and base pairs (2D) of the RNA structure. However, the 1D sequences of RNAs are less evolutionarily conserved than their 2D and 3D structures, suggesting that the 1D sequences are less useful than 2D and 3D structures when identifying the RNA structural motifs. In this thesis, we utilize the structure alphabet that was previously developed by our lab to transform RNA 3D structures into 1D structural sequences and further modify the program of RNAMotifScan such that it can identify the RNA structural motifs based on the base pairs of the given RNAs (i.e., 2D information) and their structural sequences (i.e., 3D information). Finally, our experimental results have shown that the above method indeed have further improved the performance of RNAMotifScan for identifying the RNA structural motifs.