發(fā)布時間：2018-04-11 04:15

  本文選題：生物信息學(xué) + 泛素連接酶��； 參考：《中國人民解放軍軍事醫(yī)學(xué)科學(xué)院》2017年博士論文

【摘要】：泛素是一種76個氨基酸構(gòu)成的小分子蛋白,能夠通過C端的羧基與賴氨酸殘基上的氨基之間形成肽鍵而共價結(jié)合到特定的蛋白上,該過程被稱作泛素化修飾。泛素化修飾調(diào)控了真核生物細(xì)胞內(nèi)80%蛋白質(zhì)的蛋白酶體降解,同時還調(diào)控炎癥信號通路、DNA損傷修復(fù)等多種進(jìn)程。泛素化修飾與阿爾茲海默綜合癥、帕金森綜合癥以及多種癌癥的發(fā)生發(fā)展密切相關(guān)。研究泛素化對理解遺傳信息的調(diào)控表達(dá)和多種疾病的發(fā)生發(fā)展有重要意義。在泛素化修飾過程中,泛素連接酶E3與底物之間的相互作用決定了底物蛋白的特異性,是理解泛素化系統(tǒng)精確調(diào)控的關(guān)鍵。人們發(fā)展了多種利用高通量蛋白檢測技術(shù)(例如全局蛋白穩(wěn)定性分析、蛋白微陣列、噬菌體展示文庫和質(zhì)譜技術(shù))鑒定泛素連接酶-底物相互作用的方法。然而由于泛素連接酶底物較低的蛋白表達(dá)水平、泛素連接酶與底物較弱的相互作用,高通量實驗方法往往效率較低,且成本較高。因此,盡管目前有近5700個底物蛋白的30000個泛素化修飾位點被鑒定,但是數(shù)據(jù)庫中僅有861對泛素連接酶-底物相互作用關(guān)系,這意味著只有約15%的泛素化修飾蛋白有泛素連接酶信息。因此迫切需要發(fā)展一種有效的在蛋白質(zhì)組水平預(yù)測泛素連接酶-底物相互作用的生物信息學(xué)方法。為解決這一挑戰(zhàn),本文構(gòu)建了人類泛素連接酶-底物相互作用的預(yù)測模型。首先,為了構(gòu)建預(yù)測模型所需的金標(biāo)準(zhǔn)數(shù)據(jù)集,本文發(fā)展了一套從文獻(xiàn)中獲取泛素連接酶-底物相互作用信息的策略。從PubMed和Web of Knowledge數(shù)據(jù)庫獲取可能包含泛素連接酶-底物相互作用信息的文獻(xiàn)摘要,利用文本挖掘工具對文獻(xiàn)摘要進(jìn)行分析,經(jīng)過人工判讀進(jìn)行校驗,最終本文構(gòu)建了一個包含1315對泛素連接酶底物相互作用的數(shù)據(jù)集,這是目前最大的泛素連接酶-底物相互作用數(shù)據(jù)集。利用構(gòu)建的數(shù)據(jù)集,本文進(jìn)一步構(gòu)建了泛素連接酶-底物相互作用網(wǎng)絡(luò),該網(wǎng)絡(luò)具有無尺度性質(zhì)。依據(jù)來源文獻(xiàn)的發(fā)表時間,本文將泛素連接酶-底物相互作用數(shù)據(jù)集劃分為了金標(biāo)準(zhǔn)陽性數(shù)據(jù)集(2010年1月1日之前)和獨立測試陽性數(shù)據(jù)集(2010年1月1日之后)。在金標(biāo)準(zhǔn)陰性數(shù)據(jù)集方面,由于難以找到一個實驗驗證的理想金標(biāo)準(zhǔn)陰性數(shù)據(jù)集,本文從與E3有相互作用的蛋白質(zhì)中隨機(jī)抽取了不被金標(biāo)準(zhǔn)陽性數(shù)據(jù)集和獨立測試陽性數(shù)據(jù)集包含的泛素連接酶-蛋白對作為金標(biāo)準(zhǔn)陰性數(shù)據(jù)集。然后,本文構(gòu)建了可用于泛素連接酶-底物預(yù)測的五大類生物學(xué)特征,包括:同源泛素連接酶-底物相互作用、泛素連接酶-底物富集的結(jié)構(gòu)域?qū)Α⒎核剡B接酶-底物富集的GO功能條目對、蛋白相互作用網(wǎng)絡(luò)環(huán)和潛在的泛素連接酶識別底物序列motif。本文發(fā)現(xiàn)泛素連接酶可能通過特定的結(jié)構(gòu)域和底物相結(jié)合,或者識別底物上特定的序列motif。泛素連接酶和底物在相互作用網(wǎng)絡(luò)中更傾向于形成3元環(huán)和4元環(huán)。本文利用似然比評估發(fā)現(xiàn)這五大類特征都能對泛素連接酶-底物相互作用關(guān)系進(jìn)行有效預(yù)測,并且該體系有助于發(fā)現(xiàn)潛在的泛素連接酶識別底物結(jié)構(gòu)域和motif,例如本文預(yù)測的“TP53 DNA-binding domain”能與泛素連接酶WWP1相互作用(富集比:7.21),以及APC/C復(fù)合體泛素連接酶識別底物的“KEN” motif (motif得分:16.13),都得了文獻(xiàn)的驗證。進(jìn)而,本文利用樸素貝葉斯分類器,整合這五大類特征構(gòu)建了 ESI的預(yù)測模型。五倍交叉驗證發(fā)現(xiàn)整合后的模型ROC曲線下面積高于任何單一特征的預(yù)測模型,其面積為0.827,說明該預(yù)測模型具有理想的預(yù)測效果,同時,獨立測試數(shù)據(jù)集(所有ESI的發(fā)現(xiàn)時間均在2010年1月1日之后)測試下ROC曲線下面積為0. 733,說明模型具有發(fā)現(xiàn)新的ESI的能力。最后,本文利用構(gòu)建的ESI預(yù)測模型對人類蛋白質(zhì)組范圍的ESI進(jìn)行了預(yù)測并構(gòu)建了在線的泛素連接酶-底物相互作用展示平臺UbiBrowser(http://ubibrowser.ncpsb. org)。UbiBrowser 支持多種數(shù)據(jù)提交方式,利用網(wǎng)絡(luò)視圖、列表視圖和序列視圖,展示了預(yù)測的泛素連接酶-底物相互作用、文獻(xiàn)來源的泛素連接酶-底物相互作用以及蛋白的泛素化修飾位點和可能的被識別結(jié)構(gòu)域和motif信息。模型預(yù)測相關(guān)的支持證據(jù)信息也同時向用戶進(jìn)行展示。本文利用UbiBrowser對一些與疾病相關(guān)的泛素連接酶-底物相互作用進(jìn)行了預(yù)測,這些預(yù)測結(jié)果得到了最新發(fā)表文獻(xiàn)的支持。本文進(jìn)而選取了潛在的泛素連接酶底物-相互作用對Smurfl-Smad3進(jìn)行實驗研究,結(jié)果表明在過表達(dá)體系下,Smurfl能夠介導(dǎo)Smad3的泛素化修飾,這進(jìn)一步說明UbiBrowser能夠幫助實驗人員發(fā)現(xiàn)新的泛素連接酶-底物相互作用。總之,為高效的揭示泛素連接酶-底物相互作用關(guān)系,本文完成了從泛素連接酶-底物相互作用的數(shù)據(jù)收集、預(yù)測模型構(gòu)建以及在線瀏覽平臺開發(fā)等一系列工作,最終為用戶提供了首個覆蓋人類所有蛋白的泛素連接酶-底物相互作用瀏覽器。本文工作,有助于研究人員發(fā)現(xiàn)新的泛素連接酶-底物相互作用,同時也有助于更加深入的理解泛素化修飾過程中泛素連接酶-底物間的選擇機(jī)制。
[Abstract]:Ubiquitin is a small protein of 76 amino acids, and peptide bond covalent binding to specific proteins can form through C terminal carboxyl and lysine residues on the amino group, a process called ubiquitination. Ubiquitination regulates proteasome degradation in eukaryotic cells, 80% egg white quality, but also regulate the inflammatory signaling pathway, DNA damage repair and other processes. The ubiquitination and Alzheimer's syndrome, Parkinson syndrome is closely related to the occurrence and development of many cancers. It has important significance to study the regulation of ubiquitin expression and understanding the genetic information of many diseases. In the ubiquitination process. The interaction between ubiquitin ligase E3 and substrate determines the specific substrate protein, is the key to understand the precise regulation of the ubiquitin system. The development of a variety of people to use high-throughput protein detection Technology (such as global protein stability analysis, protein microarray, phage display library and mass spectrometry) method for identification of ubiquitin ligase substrate interactions. However, due to the lower substrate of the ubiquitin ligase protein interaction with ubiquitin ligase substrate is weak, high-throughput experimental methods are of low efficiency, and high cost. Therefore, although there are 30000 nearly 5700 ubiquitin protein modification sites were identified, but only 861 of the database of ubiquitin ligase substrate interactions, which means that only about 15% of the ubiquitination protein ubiquitin ligase. Therefore there is an urgent need to develop an effective in proteomics bioinformatics prediction of ubiquitin ligase substrate interaction method. To solve this challenge, this paper constructs a prediction of human ubiquitin ligase substrate interactions Model. First, the gold standard in order to build prediction model for data set, this paper developed a ubiquitin ligase - from the literature to obtain substrate interaction information acquisition strategy. May contain ubiquitin ligase substrate interaction information from PubMed and Web of of the Knowledge database, using text mining tools for analysis of literature Abstract after artificial interpretation verification, finally this paper constructs a contains 1315 pairs of ubiquitin ligase substrate interaction data set, which is currently the largest ubiquitin ligase substrate interaction data set. Using the data sets, the paper builds the ubiquitin ligase substrate interaction network, the network has scale-free properties according to published sources. The literature, the ubiquitin ligase substrate interaction data set into positive data set (2010 gold standard The year before January 1st) and the independent test positive data set (after January 1, 2010). The gold standard negative data set, because the ideal gold standard negative data is difficult to find a set of experiments, were randomly selected from the E3 interacting proteins are not gold standard positive data sets and independent test positive data set the ubiquitin ligase protein on the gold standard for negative data set. Then, this paper constructs can be used to predict the ubiquitin ligase substrate five categories of biological characteristics, including: homologous ubiquitin ligase substrate interaction domain, ubiquitin ligase substrate concentration of GO, the function of entry of ubiquitin ligase substrate concentration protein interaction network, ring and potential ubiquitin ligase substrate recognition sequence of motif. we found that through ubiquitin ligase domain and substrate specific combination, or Identification of substrate specific sequences of motif. ubiquitin ligase and substrate interaction in the network tend to form 3 membered ring and 4 membered ring. The likelihood these five kinds of features can effectively predict the ubiquitin ligase substrate interaction relationship evaluation, and the system can help to find potential ubiquitin ligase substrate recognition domain and motif, such as the "TP53 DNA-binding domain" prediction can interact with ubiquitin ligase WWP1 (enrichment ratio: 7.21), and the APC/C ubiquitin ligase complex substrate recognition of the "KEN motif" (motif score: 16.13), verification documents. Then got, using the Naive Bayesian classifier. The integration of the five kinds of feature prediction model is built. ESI prediction model ROC curve area model of five fold cross validation found after the integration of the next higher than any single feature, its area is 0. 827, the prediction effect, the prediction model is ideal at the same time, the independent test data set (all ESI found time in January 1, 2010 after the area under the ROC curve test) was 0.733, shows that the model is capable of discovering new ESI. Finally, the ESI prediction model based on the human proteome wide ESI the prediction and the construction of the online ubiquitin ligase substrate interaction platform UbiBrowser (http://ubibrowser.ncpsb. ORG.UbiBrowser) to support multiple data submission, using the network view, list view and sequence view, show the prediction of ubiquitin ligase substrate interactions, the literature source of ubiquitin ligase substrate interactions and protein ubiquitination site and may be recognition domain and motif information. At the same time supporting evidence information related to the user model Show. UbiBrowser to predict some disease associated ubiquitin ligase substrate interactions by using these results obtained with the newly published literature support. This paper then select a potential substrate ubiquitin ligase interaction experiment on Smurfl-Smad3, the results show that the over expression system, Smurfl ubiquitination mediated by Smad3, it proves that UbiBrowser can help researchers find new ubiquitin ligase substrate interactions. In short, efficient reveal ubiquitin ligase substrate interaction relationship, this paper completed the ubiquitin ligase substrate interaction data collection, forecasting models and online through a series of work platform development. The end provides the first cover all human ubiquitin ligase substrate interaction browser for users. The work of this paper, It is helpful for researchers to discover new ubiquitin ligase substrate interaction, and help further understand the ubiquitin ligase substrate selection mechanism in ubiquitination.

【學(xué)位授予單位】：中國人民解放軍軍事醫(yī)學(xué)科學(xué)院
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：R3416
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本文編號：1734384