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研究生:林叔儀
研究生(外文):Shu-I Lin
論文名稱:感光蛋白組建
論文名稱(外文):Light Detector under Construction
指導教授:費伍岡
指導教授(外文):Wolfgang B. Fischer
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:生醫光電研究所
學門:工程學門
學類:生醫工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:62
中文關鍵詞:視紫紅質分子動力學模擬感光蛋白
外文關鍵詞:RhodopsinMolecular dynamic simulationLight detector
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膜蛋白的純化和萃取,是一項仍需要克服的挑戰。人體細胞中,約40%的蛋白質為膜蛋白,但現今已知的蛋白質結構數據庫中,膜蛋白只占約1%。為了拉近兩者之間的差距,引入電腦計算技術是重要的方法之一。良好的結構預測技術,能提供重要的資訊,並可用於研究領域之參考,此外,還能幫助我們了解膜蛋白的功能。在膜蛋白的生物性生成過程中,蛋白質引導通道複合物(protein conducing channel)扮演著重要角色。新生成的胜肽鏈被插入蛋白質引導通道中間,通過側向通道離開,並釋放到膜中。然而,由胜肽鏈組成的穿膜螺旋(transmembrane helix),是否在離開蛋白質引導通道後,便能夠直接組成天然結構而不需要額外的組裝機制(例如:穿膜螺旋的旋轉與傾斜);或是當單螺旋從蛋白質引導通道釋放後,再與接續之穿膜螺旋依序進行組裝,此機制尚未清楚。在本論文中,將著重在跨膜螺旋與其他跨膜螺旋組裝成對(pair)的狀況下(例如:螺旋1 +螺旋2、螺旋2 +螺旋3以及螺旋3 +螺旋4),藉由蛋白對接組裝(docking)程式以及分子動力學模擬,開發出一套可以用於預測未知膜蛋白結構之方法。
在此研究中,以電腦輔助分析的方法重建視紫紅質(rhodopsin;PDB id:4ZWJ)之結構。視紫紅質屬G蛋白偶和受體家族(G protein couple receptor family;GPCRs)之感光膜蛋白。而GPCRs為最大的膜蛋白家族,同時也是重要的小分子標靶藥物之目標蛋白。GPCRs家族皆由7個α螺旋結構組成穿膜區間,但其穿膜螺旋之間的距離、角度、傾斜度和接觸殘基皆不盡相同。在本實驗中,利用本實驗室所設計的蛋白對接組裝程式,調整兩穿膜螺旋之間的距離、旋轉角度和傾斜度,能夠產出高達一百萬個結構(無時間依賴性)。所得結構根據AMBER 94力場計算其相互作用之位能,並依照位能高低,將結構進行排序,而後選擇最低位能之結構,執行200奈秒分子動力學模擬(有時間依賴性)。研究結果發現:最低能量結構的構型並不全然與天然結構的構象互相匹配。而部分蛋白的環路(loop)在折疊途徑和決定蛋白質的穩定性方面,具有重要之作用。然而,視紫紅質的環路並不全具有這方面的功能,部分環路只作為連接體,連接兩個穿膜螺旋。在本實驗中,依順序執行穿膜螺旋的對接、插入環路並進行MD模擬,有部分成對螺旋與天然螺旋的結構相似性獲得改善。
結論:雖然部分成對穿膜螺旋與天然結構之相似性可藉由連接環路獲得改善,然而改善幅度小,同時與天然結構相異性仍大。因此,我們傾向改善對接程式,將更多因子納入考量使對接程式更加完善。由於現行對接程式僅利用位能作為最佳結構判斷依據,並未考量蛋白質引導通道,也未顯示接觸殘基相似度、集群分析(cluster analysis)等參數,可能是造成最低位能結構與天然結構不相符的原因。結構之間的位能在選擇結構時是一個很重要的特徵,然而比起最低位能的結構,有時位能較高的結構也是值得考慮的。未來會嘗試將上述參數納入最佳結構判斷標準,以期能夠更精準的預測蛋白質結構。
The purification and extraction of membrane protein for structural analysis is a challenge which needs to be met. It is estimated that 40% of the proteins in the human cell are membrane proteins. In the Protein Data Bank (PDB), around 1 % of the structures are those from membrane proteins. Therefore, the introduction of computational methods is necessary to offset the tremendous disparity. A great computational prediction not only provides a bridge to the experimental data but also guide us to the decipher the functional state of membrane proteins.
The biosynthesis of integral membrane protein is achieved by a protein conduct channel (PCC) complex including the so-called translocon. The nascent protein will be inserted into the translocon and released into the membrane via a lateral gate of the translocon. Are the trans membrane domains (TMDs) properly located at the site of the translocon? Or will the individual helix assembly with another helix when released from the translocon? The mechanism is unclear. In this thesis, the focus is on the situation of transmembrane helix assembly with the other transmembrane helices in a pairwise fashion (helix1+helix2, helix2+helix3, helix3+helix4… etc.), An in-house docking program is used as well as molecular dynamic (MD) simulations.
Rhodopsin (PDB id: 4ZWJ) is used for studying its reconstruction. Rhodopsin, is a light detecting membrane protein which belongs to the G-protein-couple receptors (GPCRs) family. GPCRs are the largest group of membrane proteins, and also represent the most important drug target. The members of GPCRs share a 7 α-helical structure, however, their positioning differs in respect of inter-helix distances, angles, tilts, and contact residues.
To investigate how helices assemble as membrane proteins, the distance, rotational angles, and tilt are screened. The docking delivers up to one million structures. The structures are ranked according to the interaction energies which are calculated based on the AMBER 94 force field. The lowest energy structure is chosen to execute 200 ns MD simulation (time-dependent).
In this study, it has been found that first, the lowest energy conformation does not always match to the conformation of native structure. Second, even though some loops play important role in folding pathways and determinants the stability of the protein, it seems that the loops only be the connectors between helices in the structure of rhodopsin. Third, the protocol, sequentially performing docking, insertion of the loop, followed by a MD simulation, works partially improve the generation of the dimmer.
In conclusion, the potential energy is important feature for choosing the structure, however, sometimes the higher energy structures need to be taken account.
中文摘要 i
Abstract iii
Content v
List of Figures vi
List of Tables viii
1. Introduction 1
1.1 Protein-conducting channel (PCC) 1
1.2 Rhodopsin 3
1.3 Loop prediction 4
1.4 Rationale and objective 5
2. Materials and Methods 6
2.1 Rhodopsin 6
2.2 Lipid membrane 8
2.3 Molecular Operating Environment (MOE) 9
2.4 AMBER 94 force field 11
2.5 Program Loopy 12
2.6 Molecular Dynamic simulations 13
2.7 Root mean square deviations (RMSD) 16
2.8 Root mean square fluctuation (RMSF) 16
2.9 Dictionary secondary structure of protein (DSSP) 17
3. Result 18
4. Discussion 36
5. Conclusion 38
6. References 39
7. Appendix 44
List of Figures
Figure 1. The flow chart of computational approach. 5
Figure 2. The structure of rhodopsin. 6
Figure 3. The TMDs of rhodopsin 7
Figure 4. The lipid patch. 8
Figure 5. The degree of freedoms (DOFs) in docking approach. 10
Figure 6. The equation of AMBER 94 to calculate the potential energy. 11
Figure 7. The flow chart of MD simulations. 15
Figure 8. The assembled model based on homo oligomer docking approach. 18
Figure 9. The sequential assembly results. 19
Figure 10. The assembled model based on docking approach. 21
Figure 11. All the settings generated by docking approach. 23
Figure 12. The structures after 200 ns MD simulation. 25
Figure 13. DSSP of structure with loops (left side) and without loops (right side). 27
Figure 14. The contact residues between helices 5/6. 30
Figure 15. The contact residues between helices 6/7. 32
Figure 16. The structure of docking crystal helices 3/4 in ranking NO.2 and contact residues 35
Figure 17. 2D energy plots for the assembled ideal helices 2/3 and contact residues. 44
Figure 18. 2D energy plots for the assembled ideal helices 3/4 and contact residues. 45
Figure 19. 2D energy plots for the assembled ideal helices 4/5 and contact residues. 46
Figure 20. 2D energy plots for the assembled ideal helices 5/6 and contact residues. 47
Figure 21. 2D energy plots for the assembled ideal helices 6/7 and contact residues. 48
Figure 22. 2D energy plots for the assembled crystal helices 1/2. 49
Figure 23. 2D energy plots for the assembled crystal helices 2/3 and contact residues. 50
Figure 24. 2D energy plots for the assembled crystal helices 3/4 and contact residues. 51
Figure 25. 2D energy plots for the assembled crystal helices 4/5 and contact residues. 52
Figure 26. 2D energy plots for the assembled crystal helices 5/6 and contact residues. 53
Figure 27. 2D energy plots for the assembled crystal helices 6/7 and contact residues. 54
List of Tables
Table 1. The average RMSD values of model structures in first 5 ns and last 5 ns with loops (right side) and without loops (left side). 28
Table 2. The RMSD values and identical contact residues. 33
Table 3. The top ten structure of helices 3/4 generated according to docking approach and the comparisons of RMSD values. 34
Table 4. The average RMSD of combination of helices 1/2 with and without loop. 55
Table 5. The average RMSD of combination of helices 2/3 with and without loop. 56
Table 6. The average RMSD of combination of helices 3/4 with and without loop. 57
Table 7. The average RMSD of combination of helices 4/5 with and without loop. 58
Table 8. The average RMSD of combination of helices 5/6 with and without loop. 59
Table 9. The average RMSD of combination of helices 6/7 with and without loop. 60
Table 10. The RMSD values of first ten crystal structures and their potential energy. 61
Table 11. The RMSD of first ten ideal structures and their potential energy. 62
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