利用序列保留性預測磷酸化的位置

Applying Sequence Conservation Strategy to Predict Protein Phosphorylation Sites

謝昆璋(kun- kun-zhang Xie phosphorylation)

指導教授 ： 朱彥煒

亞洲大學/資訊學院/生物資訊學系碩士班/碩士(2008年)

摘要

磷酸化是蛋白質中最重要的後轉譯修飾之一，它參與各種不同的生物訊號傳遞的路徑。在傳遞路徑中，蛋白質的磷酸化與去磷酸化反應為真核細胞提供了調控機制，控制了許多酵素和受體的活化與抑制。因此，若能預測磷酸化作用的位置，將對相關的研究有很大的助益。
本論文提出了一個新的序列保留性計算法則，建立起一個模型，它是利用已知磷酸化的片段當作預測的模板，並利用其與非磷酸化的片段比對，求出最大相似度，並依此建立預測磷酸化的門檻值，最後將未知待預測序列的片段送入本預測模型。實驗結果並與Netphos、Disphos和GPS三個網站比較，針對五個性質來做探討:靈敏度（Sn）、特異性（Sp）、準確度（Acc）、精準度（Precision）和馬修斯相關係數（MCC）。實驗預測的結果顯示，本方法在馬修斯相關係數及預測準確度都有相當不錯的表現。

關鍵字

磷酸化 ； HASH(0x8bb252c) ； HASH(0x8bb25a4)

並列摘要

Phosphorylation, one of the most important post-translational modifications in proteins, is involved in biological signal transduction in various processes. During signal transduction, proteins’ phosphorylation and dephosphorylation provides a control mechanism for eukaryotes to activate or inhibit a number of enzymes and receptors. Therefore, if we can predict where phosphorylation is taking place, it will benefit relevant research significantly. In this study, a new sequence conservation method is proposed to create a model. Using known phosphorylated segments as a template for prediction and matching them with non-phosphorylated segments, we attempted to find their maximum similarity. Based on this, a threshold value for prediction was then for each template. Finally, unknown sequence segments to be predicted were substituted into the prediction model. The results were then compared with the 3 websites Netphos, Disphos and GPS, and a discussion on the following 5 kinds of estimation was conducted accordingly: Sensitivity (Sn), Specificity (Sp), Accuracy (Acc), Precision, and Mattews correlation coefficient (MCC).
The results show that this method had relatively good performance in MCC and Acc prediction.

並列關鍵字

Phosphorylation

參考文獻

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