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研究生:莊利偉
研究生(外文):Chuang,Li-Wei
論文名稱:胺基酸與結構字元間殘基接觸數之研究
論文名稱(外文):A Study of Residue Contact Number Among the Amino Acid and Structural Alphabet
指導教授:董其樺
指導教授(外文):Tung,Chi-Hua
學位類別:碩士
校院名稱:中華大學
系所名稱:生物資訊學系碩士班
學門:生命科學學門
學類:生物訊息學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:51
中文關鍵詞:結構字元胺基酸交互作用胺基酸接觸數分數矩陣
外文關鍵詞:Structural AlphabetAmino Acid InteractionAmino Acid contactscoring matrix
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在研究蛋白質結構的生物資訊領域中,胺基酸的特性與立體結構的摺疊形狀有著緊密的關聯性。為了了解在蛋白質結構中各胺基酸之間的相互關係,可透過計算胺基酸中Cα原子彼此的接觸數,再將其轉換為分數,藉此觀察每種胺基酸在蛋白質中,何種胺基酸彼此之間較常發生靠近或疏遠。以往研究僅考慮胺基酸的一級序列與二級結構等資訊,並未包含局部片段的三級結構之資訊,可能無法真實反應出胺基酸在蛋白質中的所扮演的角色。因此,本研究使用結構字元(Structural Alphabet, SA)的定義,把胺基酸替換為結構字元,使其胺基酸一級序列中能同時隱含二級與三級結構的描述,並藉由胺基酸的連結度數量定義其所屬環境,了解胺基酸存在於蛋白質內部或外部後,再觀察局部結構之摺疊型式與胺基酸彼此相互接觸的分佈傾向。
本研究方法產生出三種分數矩陣,分別為23個結構字元的23乘23矩陣、23個結構字元與3種二級結構的69乘69矩陣,以及23個結構字元與5種環境的115乘115矩陣。研究結果顯示,使用結構字元所產生的分數矩陣,相較於其他研究者的分數矩陣,其分布的變異數較大,且具有較明顯的二級結構分群,因此更能將胺基酸排列與結構摺疊形狀的關聯性做詳細的描述。
本研究探討蛋白質中胺基酸原子之間的接觸數量,以新的觀點,例如環境、局部結構、結構字元等構面,統計分析各胺基酸之間在不同條件環境下的接觸偏好。結果所得之接觸偏好矩陣,可顯示出胺基酸存在於蛋白質內部或外部及當時所屬的局部二級結構,彼此之間產生接觸的傾向為何。

In structural biology, there is a strong link between the characteristics of amino acids and the folding of three-dimensional protein structures. In order to understand the relationships between each amino acid within a protein structure, a score is given based the contact numbers of Cα atoms in an amino acid such that the distances of all amino acids of a protein structure can be observed. Past research has only considered the primary sequence and secondary structure of amino acids while overlooking the local tertiary structure; thus, the role amino acids play within a protein may not be completely understood. Therefore, this study used the structural alphabet (SA) in place of amino acids such that the primary sequence simultaneously illustrated the secondary and tertiary structures and defined the environment based on the amino acid contact numbers. Then, after determining whether the amino acid was inside or outside the protein molecule, the folding of the local structure and the distribution of amino acids could be observed.
Three score matrices were generated in this study: a 23x23 matrix of the 23-state SA, a 69x69 matrix of the 23-state SA and three secondary structures, and a 115x115 matrix of the 23-state SA and five environments. The results indicated that compared to the score matrices in past studies, the SA score matrices had larger distribution variances and more prominent secondary structure groups; therefore, they can better describe the relationships between the amino acid sequence and structural folding.
In this study, we uncover the contact numbers of amino acids in proteins based on new ideas, such as the environment, the local structures, and structural alphabets to analyze the contact preference under different conditions between the various amino acids. The results obtained from the scoring matrix of contact preference may exhibit amino acids present in the protein inside or outside with the local secondary structure and demonstrate the tendency to yield contact with other amino acids.

中文摘要 i
Abstract ii
致謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章、緒論 1
1.1研究動機 1
1.2研究目的 2
第二章、相關文獻探討 4
2.1蛋白質的胺基酸交互作用偏好 4
2.2準化學方法(quasi-chemical method)探討胺基酸之交互作用 5
2.3結構字元之定義與二級結構之關聯 7
2.4特定種類胺基酸序列-蛋白質局部結構關係:結構字元的分析 7
第三章、研究方法 9
3.1測試資料之準備 9
3.2將PDB轉成DSSP 10
3.3計算胺基酸Cα與Cα之間的距離 11
3.4分鏈計算 12
3.5胺基酸環境定義 13
3.6根據接觸數所產生的分數矩陣 15
3.7 20乘20的分數矩陣 18
3.8 60乘60的分數矩陣 19
3.9 100乘100的分數矩陣 20
3.10將胺基酸替換成結構字元(SA) 21
3.11 23乘23的分數矩陣 22
3.12 69乘69的分數矩陣 22
3.13 115乘115的分數矩陣 23
第四章、研究結果與討論 24
4.1 胺基酸接觸總數 24
4.2 胺基酸在環境中的胺基酸交互作用分數 27
4.3 結構字元之間的分數矩陣 29
4.4 結構字元與二級結構之間的分數矩陣 30
4.5 結構字元與環境之間的分數矩陣 32
4.6 結構字元在各環境中的接觸總數 34
第五章、結論與未來展望 36
參考文獻 38
附錄 40

1. de Brevern, A.G. and A.P. Joseph, Species specific amino acid sequence-protein local structure relationships: An analysis in the light of a structural alphabet. J Theor Biol, 2011. 276(1): p. 209-17.
2. Kauzmann, W., Some factors in the interpretation of protein denaturation. Adv Protein Chem, 1959. 14: p. 1-63.
3. Kellis, J.T., Jr., et al., Contribution of hydrophobic interactions to protein stability. Nature, 1988. 333(6175): p. 784-6.
4. Nozaki, Y. and C. Tanford, The solubility of amino acids and two glycine peptides in aqueous ethanol and dioxane solutions. Establishment of a hydrophobicity scale. J Biol Chem, 1971. 246(7): p. 2211-7.
5. Jha, A.N., S. Vishveshwara, and J.R. Banavar, Amino acid interaction preferences in proteins. Protein Sci, 2010. 19(3): p. 603-26.
6. Tanaka, S. and H.A. Scheraga, Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins. Macromolecules, 1976. 9(6): p. 945-50.
7. Robson, B. and D.J. Osguthorpe, Refined models for computer simulation of protein folding. Applications to the study of conserved secondary structure and flexible hinge points during the folding of pancreatic trypsin inhibitor. J Mol Biol, 1979. 132(1): p. 19-51.
8. Maiorov, V.N. and G.M. Crippen, Contact potential that recognizes the correct folding of globular proteins. J Mol Biol, 1992. 227(3): p. 876-88.
9. Bryant, S.H. and C.E. Lawrence, An empirical energy function for threading protein sequence through the folding motif. Proteins, 1993. 16(1): p. 92-112.
10. Bolser, D.M., et al., Residue contact-count potentials are as effective as residue-residue contact-type potentials for ranking protein decoys. BMC Struct Biol, 2008. 8: p. 53.
11. Zhang, C. and S.H. Kim, Environment-dependent residue contact energies for proteins. Proc Natl Acad Sci U S A, 2000. 97(6): p. 2550-5.
12. Yang, J.M. and C.H. Tung, Protein structure database search and evolutionary classification. Nucleic Acids Res, 2006. 34(13): p. 3646-59.
13. Tung, C.H., J.W. Huang, and J.M. Yang, Kappa-alpha plot derived structural alphabet and BLOSUM-like substitution matrix for rapid search of protein structure database. Genome Biol, 2007. 8(3): p. R31.

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