植物非專一性脂質傳輸蛋白質資料庫之建立與分析

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研究生：	王乃娟 Wang, Nai-Jyuan
論文名稱：	植物非專一性脂質傳輸蛋白質資料庫之建立與分析 Construction and analysis of a plant non-specific lipid transfer protein database (LTPDB)
指導教授：	呂平江 Lyu, Ping-Chiang
口試委員:	黃鎮剛楊立威
學位類別：	碩士 Master
系所名稱：	生命科學暨醫學院 - 生物資訊與結構生物研究所 Institute of Bioinformatics and Structural Biology
論文出版年：	2011
畢業學年度：	99
語文別：	中文
論文頁數：	75
中文關鍵詞：	植物脂質傳輸蛋白
外文關鍵詞：	Lipid transfer protein
相關次數：	點閱：2 下載：0
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植物非專一性脂質運輸蛋白 (nsLTPs) 是以α螺旋為主體結構的小分子量鹼性蛋白。在序列上由八個半胱胺酸組成，而這八個半胱胺酸會形成四對雙硫鍵。在過去的研究中主要是依照分子量將此蛋白分為二大類，nsLTP1是9kDa而nsLTP2則是7kDa。但有越來越多的研究發現既不屬於nsLTP1也不屬於nsLTP2的nsLTPs。在沒有一套完善分類方法的情況下，生物學家很難比較nsLTP之間有哪些差異。為了更加了解nsLTP，我們建立了一套基於序列相似性的分類方法。此外，我們發現在過去的研究中，八個半胱胺酸是目前用來判別植物非專一性脂質運輸蛋白的最佳方法，但目前還無法知道在序列上有哪些重要的結構模組 (motif) 會影響植物非專一性脂質運輸蛋白。目前在生物資訊及計算生物學領域中，多重序列比對 (multiple sequence alignment; MSA) 在發掘基因體或蛋白質序列的生物意義上是很有用的工具，在此論文中，我們運用MSA自 Type I 和 Type II 這二類植物非專一性脂質運輸蛋白中分析出各自的的 Prosite signature。比較此 patterns 與我們實驗室早先的實驗結果，發現利用分子生物學點突變的技術所找到對結構或功能有所影響的突變株，該突變位置的胺基酸在我們的 Prosite signature 中出現機率都高於70%，佐證了此 pattern 對結構與功能的重要性。最後，由於目前尚未有專屬於植物非專一性脂質運輸蛋白的資料庫，我們將所收集到的、已有GI number的植物專一性脂質運輸蛋白的蛋白質序列加以篩選、分析，利用 PHP 程式語言、MYSQL 資料庫系統建立了一個線上資訊服務平台，及一個根據我們的分類法來預測是否為 Type I 和 Type II 的 LTProsite 預測平台，網址：http://140.114.98.10/ltp/

Plant non-specific lipid transfer proteins (nsLTPs) are small and basic proteins. Recently, nsLTPs have been reported involved in many physiological functions such as mediating phospholipid transfer, participating in plant defense activity against bacterial and fungal pathogens, and enhancing cell wall extension in tobacco. However, the lipid transfer mechanism of nsLTPs is still unclear, and comprehensive information of nsLTPs is difficult to obtain. In this study, we identified 595 nsLTPs from 121 different species and constructed an nsLTPs database — LTPDB — which comprises the sequence information, structures, relevant literatures, and biological data of all plant nsLTPs (http://140.114.98.10/ltp). Meanwhile, bioinformatics and statistics methods were implemented to develop a classification method for nsLTPs based on the patterns of the eight highly-conserved cysteine, and to suggest strict Prosite patterns for Type I and Type II nsLTPs. The Prosite pattern of Type I is C X2 V X5-7 C [V , L , I] X Y [L, A, V] X8-13 CC X G X12 D X [Q, K, R] X2 CXC X16-21 P X2 C X13-15C, and that of Type II is C X4 L X2 C X9-11 P [S , T] X2 CC X5 Q X2-4 C[L, F]C X2 [A , L , I] X [D , N] P X10-12 [K , R] X4-5 C X3-4 P X0-2 C. Moreover, we referred the Prosite patterns to the experimental mutagenesis data that previously established by our group, and found that the residues with higher conservation played an important role in the structural stability or lipid binding ability of nsLTPs. Taken together, this research has suggested potential residues that might be essential to modulate the structural and functional properties of plant nsLTPs. Finally, we developed a useful prediction tool for nsLTPs named LTProsite and hereby proposed some biologically important sites of the nsLTPs, which are described by using a new Prosite pattern that we defined.

摘要    1
Chapter 1 － Introduction    4
1.1    Lipid transfer protein — the definition    4
1.2    Plant non-specific lipid transfer proteins (nsLTPs)    4
1.3    The structure of plant non-specific lipid transfer proteins    5
1.4    Biological function of plant non-specific lipid transfer proteins    6
1.5    Identification and classification of plant non-specific lipid transfer proteins    6
1.6    The aims of this work    7
Figure. 1    8
Figure. 1.1 nsLTPs sequence alignment and the disulfide bond patterns    8
Table 1.    9
Table.1. 1 The difference between nsLTP1 and nsLTP2.    9
Table.1. 2 Diversity of the eight cysteine motif in nsLTP types.    10
Table.1. 3 Comparison of classification methods    11
Chapter 2 － Materials and methods    12
2.1 Hardware environment    12
2.2 Software environment    12
2.3 Databases and web-based tools    12
2.3.1 NCBI (http://www.ncbi.nlm.nih.gov/)    12
2.3.2 ExPASY (http://expasy.org/)    13
2.3.3 TARGETP (http:// www.cbs.dtu.dk/services/TargetP)    14
2.3.4 SignalP 3.0 Server (http://www.cbs.dtu.dk/services/SignalP/)    14
2.3.5 PDB database (http://www.pdb.org/)    15
2.3.6 The Prosite database (http://ca.expasy.org/Prosite/)    15
2.4 Data mining and Hidden Markov model    16
2.5 Unsupervised Clustering    17
2.6 Sequence alignment and phylogenetic tree reconstruction    18
2.7 Calculation of the amino acids occurrence    20
2.8 Construction of the LTPDB    20
Figure. 2    21
Figure. 2. 1 Data preprocessing    21
Figure. 2. 2 Tree build pipeline    22
Figure. 2. 3 UPGMA tree build pipeline    23
Figure. 2. 4 Neighbor-joining methods pipeline    24
Figure. 2. 5 The web interface of LTPDB    25
Chapter 3-Results and discussions    26
3.1 Classification based on sequence similarities    26
3.2 Phylogenetic analysis of nsLTPs    27
3.3 Strategies for define new Prosite patterns for nsLTPs    28
3.4 Usage of the web service    31
3.4.1 Home page- nsLTPs story    31
3.4.2 Species Browsing    32
3.4.3 Structure Browsing    33
3.4.4 LTP-related Publications    34
3.4.5 LTP-related Useful Tools    34
3.5 Ongoing projects related to LTPDB and Prosite classification and identification predictor (LTProsite)    35
Figure. 3    36
Figure. 3. 1 Five types distribution in Mw and pI characteristics.    36
Figure. 3. 2 Five types distribution in CXC and the net charge characteristics.    37
Figure. 3. 4 The unrooted phylogenetic trees were created by the neighbor-joining method    39
Figure. 3. 5 The regular expression patterns PLANT_LTP, PS00597 in PROSITE    40
Figure. 3. 6 Type I Prosite pattern    41
Figure. 3. 7 Sequence alignment of plant nsLTP1.    42
Figure. 3. 8 A structure of an Mugbean nsLTP1 myristate complex.    43
Figure. 3. 9 Experimental data    44
Figure. 3. 10 Type II Prosite pattern    45
Figure. 3. 11 Sequence alignment of plant nsLTP2.    46
Figure. 3. 12 Stereo view of nsLTP2/sterol complex.    47
Figure. 3. 13 Experimental data of Type2    48
Figure. 3. 14 90% prosite pattern    49
Figure. 3. 15 Experimental flowchart    50
Figure. 3. 16 Web service of LTPDB homepage.    51
Figure. 3. 18 NsLTPs in specific species    53
Figure. 3. 19 The complete protein information    54
Figure. 3. 20 Structure Browsing    55
Figure. 3.21 Structure information    56
Figure. 3. 22 RMSD differences between the coordinates of equivalent main-chain atoms of all nsLTPs structures, labeled with their PDB code    57
Figure. 3. 23 Type I and Type II RMSD color map.    58
Figure. 3. 24 Reference page    59
Figure. 3. 25 Related useful tools    60
Table 3.    62
Table. 3.1 Diversity of the eight cysteine motifs based on LTPDB.    62
Table. 3.2 Correlation between different nsLTPs structures    63
Chapter 4 – Conclusions    66
Chapter 5 - Future Work    67
Aim 1. Develop an efficient Prosite classification and identification methods based on LTPDB (LTProsite)    67
References    68

                                

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