以計算方法探討與分析核醣核酸的序列與二級結構的關係研究

Abstract

蛋白質參與或催化體內各種生理、合成與代謝等生化反應，也輔助體內相當多的生理功能。在研究蛋白質功能上，經常利用異體表達純化蛋白質及了解其酵素功能、特性與機制，以探討疾病發生的原因，或甚至研發治療疾病的方法。在實驗研究上經常選擇容易培養、生長快速且產量高的異體表達(Heterologous Expression)系統當做異體表達的宿主，使蛋白質可以藉由異體宿主大量表現，再經純化獲得蛋白質。然而，外來基因於異體表現時經常出現一些蛋白質表現與摺疊的問題；其中包括核酸的二級結構對蛋白質轉譯的影響。因此，本論文嘗試提出能量計算的方法，藉以評估序列在轉譯過程中能量的變化，進而提出改良基因的對策。其目的之一是為了解決基因於異體表達的問題。 目前相關的研究指出，異體表達在轉譯的過程中，可能會因為遇到穩定的核酸二級結構而造成轉譯無法啟動或甚至中斷。因此，本研究利用人工設計並驗證其可行性後，企圖開發可用的計算方法或程式，邁向自動化，而在不將胺基酸突變的前提下，將預表達的序列調整至適合於異體表達的型式，並利用降低核酸二級結構的穩定度，使核醣體可以順利轉譯以產生正確的目標蛋白。本研究的立意與成果對改善蛋白質在異體表達的結果、了解轉譯機制、核酸二級結構及蛋白質可溶性之間的關聯性，甚至對於製作抗體疫苗、蛋白質藥物、胜肽生物材料、或基因的功能性鑑定上，將有莫大的幫助與突破。

Proteins play important roles in physiological reactions, biochemical syntheses and metabolism. For that, scientists often need to isolate the proteins for functional studies or therapeutic applications. However, preparations of a specific protein are often difficult to achieve from natural host cells. Therefore, it is usually necessary to utilize heterologous hosts to facilitate protein expression because of relative simplicity, low cost and fast high-density cultivation. Still, persistent challenges to the use of the heterologous host involve low level of expression for some proteins and then formation of inactive insoluble aggregates. In many cases, these problems can arise due to mRNA instability. This study has proposed methods utilizing thermodynamic parameters to analyze free energy variation in translational process. The aim of this work is to also solve the problem of gene expression in the heterologous host. Previous study revealed that ribosomal pausing could be engineered by alternative of RNA secondary structures. In this study, we have designed artificial RNA sequences and afterward verified its feasibility. We have also proposed a method for manipulating RNA sequences by computational methods that can be suitable for heterologous expression, in order to get target proteins successfully. This study has raised idea and practical methods to improve the heterologous expression of proteins, which may help the understanding of translation mechanism as well as understanding of the correlation between RNA secondary structure and protein folding. It can be further applied in the study of antibody, protein drugs, biomaterials and their corresponding applications.