生长抑素受体3D结构的同源模建及其配体固相合成研究
|
摘要
生长抑素受体(SOMATOSTATIN RECEPTOR，SSTR)是细胞膜上的一类7螺旋跨膜结构的蛋白质。种系发生上属于G-蛋白偶联受体(G-PROTEIN COUPLED RECEPTOR，GPCR)家族。GPCR家族的蛋白均为跨膜结构蛋白，由于膜蛋白分离与纯化在目前情况下很困难，因此，现在PDB数据库中已知的晶体结构并不多。SSTR目前在PDB中没有结构的录入。由于GPCR结构的规则性及跨膜区的序列保守性较强，这就为利用GPCR家族蛋白分子的之空间的三维结构的比较分子模拟，(comparative molecular modelling)或称同源模建，(HOMOLOGY MODELING)提供了很好的基础，目前，这是同源模建应用得最为成功的领域之一。本文的目的之一即是通过同源模建的方法，模拟SSTR的三维结构，为研究生长抑素与其受体作用方式提供基础。同时也为以SSTR作为靶标的药物设计提供一个结构基础。本文的基本操作过程是：分别先以五种SSTR的氨基酸序列作为搜寻提问，以Blast2软件和BLOSUM62矩阵作为打分方式，搜寻PDB中满足同源模建条件的已有晶体结构作为模板。然后使用整合在SWISSPROT-MODEL中的PROMODⅡ程序，以所选定的晶体结构为模板进行结构模拟，能量优化采用VAN GUNSTERN等开发的GROMOS96程序，选取的参数为IFP43B1，拓朴文件为MTB4381，采用200个循环的最陡下降法(Steepest descent)和300个循环的共轭梯度法(Conjugate gradient)两种手法，得到能量最小的构象。最后使用RAMACHANDRAN PLOT，氨基酸残基与侧链、主链碰撞等情况来检验模型的质量。结果，得到SSTR受体的全部5种亚型的结构模型。计算模型的最终能量，RAMACHANDRAN PLOT的二面角值，检查氨基酸残基碰撞情况，结果表明，除SSTR2的情况较差外，其余4种模型的可信度都很高。可以认为，以同源模建方法模拟SSTR结构是可行，有效的。
本文的另一个目的是以分子对接的方法研究SSTR与其配体相互作用的方式。分子对接(Molecular Docking)是指两个或多个分子之间按照一定的规则相互识别，并以非共价方式结合的过程，通常在计算机辅助药物设计中所说的分子对接，是指以计算机系统，根据几何匹配和能量匹配的原则，来计算模拟两个分子结合的过程。本文使用了一套蛋白质-蛋白质对接软件包GRAMM，对接的方法为最大化的对两个蛋白质的分子进行几何形状及能量匹配，以预测复合物的结构。对接后的复合物模型，以同样的方式进行能量优化，得到最终与结合位点的结构图。结果表明，可能的活性位点由第二胞外环区Phe116第三胞外环区Cys182，IleI184，Phe197，Thr201及第四胞外环区的Val288，构成了一个疏水性的口袋，另外，第二胞外环区的Asn114和第三胞外环区Thr201参与了与OCTREOTIDE的静电作用形成，OCTREOTIDE上的Trp4的芳环，与Phe197的苯环平行，也产生了一个较弱的π-π键。
最后，本文以固相合成的方式，合成了生长抑素-14及一种经过序列改造的新的类似物(序列为：ala-[cys-lys-trp-lys-phe-thr-ser-cys])。α-氨基选择以Fmoc方式保护；固相载体为WANG树脂；缩合剂选择BOP族的HBTU。肽链从树脂上的裂解选择TFA。以DMSO氧化将链中的两个CYS形成一个二硫键桥。最后以质谱，氨基酸分析等手段进行了结构确认。结果表明，所合成的两条多肽链的分子量及氨基酸组成成分都是正确的。
Somatostatin Receptor (SSTR) is 7 trans membrane helices structure. SST is its endogenetic ligand. SSTR with five subtypes belongs to G-protein coupled receptor (GPCR) family, which structures are trans membrane helices. Because membrane protein is hard to be separated and purified so far, there are not so many crystal structures of GPCR protein in PDB. GPCRs have conservative and inerratic trans membrane helices region that could build their models by comparative molecular modeling, or called homology modeling. Homology modeling has most successful examples in GPCR family.
To build a high quality 3D structure of SSTR, which could be a target for drug design, Bioinformatics and Molecular Dynamics Methods are used. 10 crystal structures of G-Protein coupled receptor (GPCR) in PDB were used as homological models to construct the 3D structures of Homo sapiens somatostatin receptor. Blast 2 software was used to align the sequence homology and similarity between the targets and the models. The conformation of the 3D structures refined with free energy minimized by GROMOS force field. To study the interaction between the receptor and the ligand, GRAMM program for protein-protein molecular docking was used to dock the modeled receptor's 3D structure and one of the ligands—octreotide. This article has built 5 subtype 3D structures of SSTR by homology modeling, and molecular docking between the hSSTR2 model and one of its ligand, octreotide was processed for analyzing the interaction between them. The active site in the receptor probably composed by phe 116 in 2nd extracell loop, cys 182,Ile184, phe 197, thr201 in 3rd extracell loop, and val288 in 4th extracell loop, which formed a hydrophobic pocket, embedding octreotide molecule. Also, Asn114 in 2nd loop, thr201 in 3rd loop contribute electrostatic interaction to the ligand. Benzene ring of phe197 is parallel to the benzazole ring of the ligand in Trp4 approximately, which produces aπ-πbond.
To synthesize SST-14 and a new SST analogue (sequence is ala-[cys-lys-trp-lys-phe-thr-ser-cys]), solid phase method is used. Wang resin was used as loader; coupler was HBTU and cleaver was TFA. 2 SH- were oxidized to form a S-S bind. Mass spectrum and amino acid analysis methods were used to verify the structures, and the results show the synthesized peptides are correct.
本文的另一个目的是以分子对接的方法研究SSTR与其配体相互作用的方式。分子对接(Molecular Docking)是指两个或多个分子之间按照一定的规则相互识别，并以非共价方式结合的过程，通常在计算机辅助药物设计中所说的分子对接，是指以计算机系统，根据几何匹配和能量匹配的原则，来计算模拟两个分子结合的过程。本文使用了一套蛋白质-蛋白质对接软件包GRAMM，对接的方法为最大化的对两个蛋白质的分子进行几何形状及能量匹配，以预测复合物的结构。对接后的复合物模型，以同样的方式进行能量优化，得到最终与结合位点的结构图。结果表明，可能的活性位点由第二胞外环区Phe116第三胞外环区Cys182，IleI184，Phe197，Thr201及第四胞外环区的Val288，构成了一个疏水性的口袋，另外，第二胞外环区的Asn114和第三胞外环区Thr201参与了与OCTREOTIDE的静电作用形成，OCTREOTIDE上的Trp4的芳环，与Phe197的苯环平行，也产生了一个较弱的π-π键。
最后，本文以固相合成的方式，合成了生长抑素-14及一种经过序列改造的新的类似物(序列为：ala-[cys-lys-trp-lys-phe-thr-ser-cys])。α-氨基选择以Fmoc方式保护；固相载体为WANG树脂；缩合剂选择BOP族的HBTU。肽链从树脂上的裂解选择TFA。以DMSO氧化将链中的两个CYS形成一个二硫键桥。最后以质谱，氨基酸分析等手段进行了结构确认。结果表明，所合成的两条多肽链的分子量及氨基酸组成成分都是正确的。
Somatostatin Receptor (SSTR) is 7 trans membrane helices structure. SST is its endogenetic ligand. SSTR with five subtypes belongs to G-protein coupled receptor (GPCR) family, which structures are trans membrane helices. Because membrane protein is hard to be separated and purified so far, there are not so many crystal structures of GPCR protein in PDB. GPCRs have conservative and inerratic trans membrane helices region that could build their models by comparative molecular modeling, or called homology modeling. Homology modeling has most successful examples in GPCR family.
To build a high quality 3D structure of SSTR, which could be a target for drug design, Bioinformatics and Molecular Dynamics Methods are used. 10 crystal structures of G-Protein coupled receptor (GPCR) in PDB were used as homological models to construct the 3D structures of Homo sapiens somatostatin receptor. Blast 2 software was used to align the sequence homology and similarity between the targets and the models. The conformation of the 3D structures refined with free energy minimized by GROMOS force field. To study the interaction between the receptor and the ligand, GRAMM program for protein-protein molecular docking was used to dock the modeled receptor's 3D structure and one of the ligands—octreotide. This article has built 5 subtype 3D structures of SSTR by homology modeling, and molecular docking between the hSSTR2 model and one of its ligand, octreotide was processed for analyzing the interaction between them. The active site in the receptor probably composed by phe 116 in 2nd extracell loop, cys 182,Ile184, phe 197, thr201 in 3rd extracell loop, and val288 in 4th extracell loop, which formed a hydrophobic pocket, embedding octreotide molecule. Also, Asn114 in 2nd loop, thr201 in 3rd loop contribute electrostatic interaction to the ligand. Benzene ring of phe197 is parallel to the benzazole ring of the ligand in Trp4 approximately, which produces aπ-πbond.
To synthesize SST-14 and a new SST analogue (sequence is ala-[cys-lys-trp-lys-phe-thr-ser-cys]), solid phase method is used. Wang resin was used as loader; coupler was HBTU and cleaver was TFA. 2 SH- were oxidized to form a S-S bind. Mass spectrum and amino acid analysis methods were used to verify the structures, and the results show the synthesized peptides are correct.
引文
1. Krulich L, Dhariwal AP, McCann SM. Stimulatory and inhibitory effects of purified hypothalamic extracts on growth hormone release from rat pituitary in vitro. Endocrinology 1968; 83:783-790
2. Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science 1973; 179:77-79
3. Patel PC. General aspects of biology and function of somatostatin. In: Weil C, Muller EE, Thorner MO, eds. Somatostatin. BERLIN: Springer Sandoz, 1992:1-16
4. Yamada Y, Post SR, Wang K, Tager HS, Bell GI, Seino S. Cloning and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Ptoc Natl Acad Sci USA 1992; 89:251-255
5. Davies N, Yates J, Kynaston H, Taylor BA, Jenkins SA. Effects of octreotide on liver regeneration and tumour growth in the regenerating liver. J Gastroenterol Hepatol 1997;12:47-53
6. Scherubl H, Bader M, Fett U, Hamm B, Schmidt-Gayk H, Koppenhagen K, Dop FJ, Riecken EO, Wiedenmann B. Somatostatin-receptor imaging of neuroendocrine gastroenteropancr eatic tumors. Gastroenterol 1993; 105:1705-1709
7. Lucarelli, P.; Mantuano, E.; Schiattarella, E.; Palmarino, R. :Evidence for linkage equilibrium between two RFLPs associated with the human SST locus. Hum. Genet. 78: 291-292,1988.
8. Lalley, P. A.; Sakaguchi, A. Y; Eddy, R. L.; Honey, N. H.; Bell, G. I.; Shen, L.-P.; Rutter, W. J.; Jacobs, J. W.; Heinrich, G.; Chin, W. W.; Naylor, S. L. : Mapping polypeptide hormone genes in the mouse: somatostatin, glucagon, caleitonin, and parathyroid hormone. Cytogenet. Cell Genet. 44: 92-97, 1987.
9. Naylor, S. L.; Sakaguchi, A. Y.; Shen, L.P.; Bell, G I.; Rutter, W. J.; Shows, T. B. : Polymorphic human somatostatin gene is located on chromosome 3. Proc. Nat. Acad. Sci. 80: 2686-2689, 1983.
10. Shen, L.-P.; Rutter, W. J. :Sequence of the human somatostatin Ⅰ gene. Science 224: 168-171, 1984.
11. Yacubova, E.; Komuro, H. :Stage-specific control of neuronal migration by somatostatin. Nature 4i5: 77-81, 2002.
12. Zabel, B. U.; Naylor, S. L.; Sakaguchi, A. Y.; Bell, G. I.; Shows, T. B. : High-resolution chromosomal localization of human genes for amylase, proopiomelanoeortin, somatostatin, and a DNA fragment (D3S1) by in situ hybridization. Proc. Nat. Acad Sci. 80: 6932-6936, 1983.
13. Yamada, Y.; Post, S. R.; Wang, K.; Tager, H. S.; Bell, G. I.; Seino, S. : Cloning and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Proc. Nat. Acad Sci. 89: 251-255, 1992.
14. Bruno, J. F.; Xu, Y.; Song, J.; Berelowitz, M. : Molecular cloning and functional expression of a brain-specific somatostatin receptor. Proc. Nat. Acad Sci. 89: 11151-11155, 1992.
15. Brinkmeier, M. L.; Camper, S. A. : Localization of somatostatin receptor genes on mouse chromosomes 2, 11, 12, 15, and 17: correlation with growth QTLs. Genomics 43: 9-14, 1997.
16. Kubota, A.; Yamada, Y.; Kagimoto, S.; Shimatsu, A.; Imamura, M.; Tsuda, K.; Imura, H.; Seino, S.; Seino, Y. : Identification of somatostatin receptor subtypes and an implication for the efficacy of somatostatin analogue. SMS 201-995 in treatment of human endocrine tumors. J.. CIin. Invest. 93: 1321-1325, 1994.
17．陈凯先等，计算机辅助药物设计：原理，方法及应用上海科学技术出版社，2000．1
18. 18. Baldwin, J. M. 1997. An alpha-carbon template for the transmembrane helices in the rhodopsin family of G-protein-coupled receptos. J. Mol. Biol. 272:144-164
19. Dhawan, B. N., F. Cesselin, R. Raghubir, T. Reisine, P. B. Bradley, P. S. Portoghese, and M. Hamon. 1996! Intemational Union of Pharmacology. Ⅻ. Classification of opioid receptors. Pharmacol. Rev. 48:567-596
20. Grigorieff, N., T. A. Ceska, K. H. Downing, J. M. Baldwin, and R. Henderson. 1996. Electron-crystallographic refinement of the structure of bacteriorhodopsin. J. Mol. Biol. 259:393-421
21. McDonald, I. K., and J. M. Thornton. 1994. Satisfying hydrogen bonding potential in proteins. J. Mol. Biol. 238:777-793
22. Lomize, A. L., I. D. Pogozheva, and H. I. Mosberg. 1996. Development of a model for the opioid receptor .pharmacophore. 3. Comparison of the cyclic tetrapeptide, Tyr-c [D-Cys-Phe-D-Phe] OH with other conformationally constrained δ-receptor selective ligands. Biopolymers. 38:221-234
23. Lomize, A. L., I. D. Pogozheva, and H. I. Mosberg. 1996. Development of a model for the opioid receptor pharmacophore. 3. Comparison of the cyclic tetrapeptide, Tyr-c[D-Cys-Phe-D-Phe]OH with other conformationally constrained &receptor selective ligands. Biopolymers, 38:221-234[Medline].
24. Lomize, A.L., I.D. Pogozheva, and H.I. Mosberg. 1998. Structural organization of G-protein-coupled receptors. Perspect. Drug Discovery Design. (in press).
25. Louie, G. V., and G. D. Brayer. 1989. A polypeptide chain-refolding event occurs in the Gly82 variant of yeast iso-l-cytochrome c. J. Mol. Biol. 209:313-322.
26. Walter R. P. Scott, Philippe H. Hulnenberger, Ilario G. Tironi, Alan E. Mark, Salomon R. Billeter, Jens Fennen, Andrew E. Torda, Thomas Huber, Peter Krulger, and Wilfred F. van Gunsteren The GROMOS Biomolecular Simulation Program Package J. Phys. Chem. A 1999, 103, 3596-3607
27. van Gunsteren, W. F.; Billeter, S. R.; Eising, A. A.; Hu"nenberger,P. H.; Kru"ger, P.; Mark, A. E.; Scott, W. R. P.; Tironi, I. G. Biomolecular Simulation: The GROMOS96 Manual and User Guide. VdF: Hochschulverl.ag AG an der ETH Zu"rich and BIOMOS b.v, Zu"rich, Groningen, 1996; ISBN 3 7281 2422 2.
28. van Gunsteren, W. F.; Billeter, S. R.; Eising, A. A.; Hu"nenberger, P. H.; Kru"ger, P.; Mark, A. E.; Scott, W. R. P.; Tironi, I. G. Biomolecular Simulation: The GR OMOS96 Manual and User Guide. VdF: Hochschulverlag AG an der ETH Zu"rich and BIOMOS b.v, Zu"rich, Groningen, 1996;ISBN 3 7281 2422 2.
29. Bemstein, F. C.; Koetzle, T. F.; Williams, G. J. B.; Meyer, E. F.; Brice, M. D.; Rodgers, J. R.; Ken_nard, O.; Shimanouchi, T.; Tasumi, M. J.Mol. Biol. 1977, 112, 535-542.
30. Havel, T.; Wu"thrich, K. Bull. Math. Biol. 1984, 46, 673-698.
31. Braun, W.; Go, N. J. Mol. Biol. 1985, 186, 611-626.
32. Gu"ntert, P.; Braun, W.; Wu"thrich, K. J. MoL Biol. 1991, 217, 517-530.
33. Ryekaert, J.-P.; Ciccotti, G.; Berendsen, H. J. C. J. Comput. Phys. 1977, 23, 327-341.
34. van Gunsteren, W. F.; Berendsen, H. J. C. Mol. Phys. 1977, 34, 1311-1327.
35. Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; DiNola, A.; Haak, J. R. J. Chem. Phys. 1984, 81, 3684-3690.
36. van Gunsteren, W. F.; Berendsen, H. J. C. Mol. SimuL 1988, 1, 173-185.
37. Yun-yu, S.; Lu, W.; van Gunsteren, W. F. Mol. SimuL 1988, 1,369-383.
38. Zwanzig, R. W. J. Chem. Phys. 1954, 22, 1420-1426.
39. Qi, w; He, Z M,. J. Computers andApplied Chemistry. 2006, 09.
40. Sehwede T, Kopp J, Guex N, and Peitsch MC (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Research 31: 3381-3385.
41. Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modelling. Electrophoresis 18:2714-2723.
1. Krulich L, Dhariwal AP, McCann SM. Stimulatory and inhibitory effects of purified hypothalamic extracts on growth hormone release from rat pituitary in vitro. Endocrinology 1968; 83:783-790
2. Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science 1973;179:77-79
3. Patel PC. General aspects of biology and function of somatostatin. In: Weil C, Muller EE, Thorner MO, eds. Somatostatin. BERLIN: Springer Sandoz, 1992:1-16
4. Yamada Y, Post SR, Wang K, Tager HS, Bell GI, Seino S. Cloning and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Ptoc Natl Acad Sci USA 1992; 89:251-255
5. Davies N, Yates J, Kynaston H, Taylor BA, Jenkins SA. Effects of octreotide on liver regeneration and tumour growth in the regenerating liver. J Gastroenterol Hepatol 1997; 12:47-53
6. Scherubl H, Bader M, Fett U, Hamm B, Schmidt-Gayk H, Koppenhagen K, Dop FJ, Riecken EO, Wiedenmann B. Somatostatin-receptor imaging of neuroendocrine gastroenteropancr eatic tumors. Gastroenterol 1993;105:1705-1709
7. Veber DF, Holly FW, Nutt RF, Bergstrand SJ, Brady SF, Hirschmann R, Glitzer MS, Saperstein R. Highly active cyclic and bicyclic somatostatin analogues of reduced ring size. Nature 1979;280:512-514
8. Schally AV. Oncological applications of somatostatin analogues. Cancer Res 1988;48:6977-6985
9. Keri GY, Erchegyi J, Horvath A, Mezo I, Idei M, Vantus T, Balogh A, Vadasz Z, Bokonyi G, Seprodi J, Teplan I, Csuka O, Tejeda M, Gaal D, Szegedi Z, Szende B, Roze C, Kalthoff H, Ullrich A. A tumor-selective somatostatin analogue (TT-232) with strong in vitro and in vivo antitumor activity. Ptoc NatlAcad Sci USA 1996;93:12513-12518
10. Falb E, Salitra Y, Yechezkel T, Bracha M, Litman P, Olender R, Rosenfeld R, Senderowitz H, Jiang S, Goodman M. A bicyclic and hsst2 selective somatostatin analogue: design, synthesis, conformational analysis and binding. Bioorg Med Chem 2001; 9:3255-3264
11. Bauer W, Briner U, Doepfner W, Hailer R, Huguenin R, Marbach P, Petcher TJ, Pless. SMS 201-995: a very potent and selective octapeptide analogue of somatostatin with prolonged action. Life Sci 1982; 1:1133-1140
12．陈凯先等，计算机辅助药物设计：原理，方法及应用上海科学技术出版社，2000．1
13. Altschul S.F., Madden T.L., Schaffer A.A., Zhang J., Zhang Z., Miller W.,Lipman D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389-3402 1997).
14. Schwede T, Kopp J, Guex N, and Peitsch MC (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Research 31: 3381-3385.
15. Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modelling. Electrophoresis 18:2714-2723.
16. Peitsch, M. C. (1995) Protein modeling by E-mail Bio/Technology 13,658-660.
17. P.E. Smith and W.F. van Gunsteren Methods for the evaluation of long-range electrostatic forces in computer simulations of molecular systems In: "Computer Simulation of Biomolecular Systems, Theoretical and Experimental Applications", Vol. 2,
18. W.F. van Gunsteren, P.K. Weiner, A.J. Wilkinson eds., Escom Science Publishers, Leiden, The Netherlands, (1993), pp. 182-212
19. W.F. van Gunsteren, P.M. King and A.E. Mark Fundamentals of drug design from a biophysical viewpoint Quart. Rev. Biophysics 27 (1994) 435-481
20. W.F. van Gunsteren, T. Huber and A.E. Torda Biomolecular Modelling: Overview of Types of Methods to Search and Sample Conformational Space in: Proceedings of the 1st European Conference on Computational Chemistry, American Institute of Physics Conf. Proc, 330 (1995) pp. 253-268
21. W.F. van Gunsteren, P.H. Hunenberger, A.E. Mark, P.E. Smith and I.G. Tironi Computer simulation of protein motion Computer Phys. Communications 91 (1995) 305-319
22. Vakser, I.A., 1995, Protein docking for low-resolution structures, Protein Eng., 8:371- 377. (Low-resolution protein docking).
23. Vakser, I.A., 1996, Long-distance potentials: An approach to the multiple-minima problem in ligand-receptor interaction, Protein Eng., 9:37-41. (Interpretation of low-resolution docking in terms of energy potentials)
24. Vakser, I.A., 1996, Low-resolution docking: Prediction of complexes for underdetermined structures, Biopolymers , 39:455-464. (Validation of low-resolution docking).
25. Vakser, I.A., 1996, Main-chain complementarity in protein-protein recognition, Protein Eng., 9:741-744. (Docking of C-alpha structures).
26. Vakser, I.A., 1997, Evaluation of GRAMM low-resolution docking methodology on the hemagglutinin-antibody complex, Proteins , Suppl. 1:226-230. (GRAMM performance at CASP).
27. Vakser, I.A., Matar, O.G., Lam, C.F., 1999, A systematic study of low-resolution recognition in protein-protein complexes,Proc. Natl. Acad. Sci. USA, 96:8477-8482. (Large scale low-resolution docking).
1. Krulich L, Dhariwal AP, McCann SM. Stimulatory and inhibitory effects of purified hypothalamic extracts on growth hormone release from rat pituitary in vitro. Endocrinology 1968; 83:783-790
2. Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science 1973;179:77-79
3. Patel PC. General aspects of biology and function of somatostatin. In: Weil C, Muller EE, Thomer MO, eds. Somatostatin. BERLIN: Springer Sandoz, 1992:1-16
4. Yamada Y, Post SR, Wang K, Tager HS, Bell GI, Seino S. Cloning.and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Ptoc Natl Acad SciUSA 1992; 89:251-255
5. J.H. Jones,'Amino-acid,Peptide and Protein',Edit by G.T.Young, Vol.1. 174-210,1969,The Chemical Sol ,London
6．陈长庆，黄惟德，多肽合成，科学出版社，1984．
7. Merrifield R B. J. Am. Chem. Soc. 1963,85:2149
8．王德心，化学试剂，2003，26：37
1. Galtia KC, Ronco PM, Verrust PJ, et al three-dimensional structure of an angiotensin 257(5069): 502-507
2. Amit AG, Mariuzza RA, Phillips SE, et al. Three-dimensional structure of an antigen-antibody complex at 2.8 A resolution. Science. 1986; 233(4765): 747-753
3. Sela M. Antigenicity: some molecular aspects. Science-1969; 166(911): 1365-1374
4. Janin J. Surface and inside volumes in globular proteins. Nature, 1979; 277(5696): 491-492
5. Connolly ML. Solvent-accessible surfaces of proteins and nucleic acids. Science, 19.83 ;221(4612): 709-713
6. Hopp TP, Woods KR. Prediction of protein antigenic determinants from amino acid sequences. ProcNatl Acad Sci USA, 1981; 78(6): 3824-3828
7. Hopp TP. Use of hydrophilicity plotting procedures to identify protein antigenic segments and other interaction sites. Methods Enzymol, 1989; 178:571-585
8. Westhof E, Altschuh D, Moras D, et al. Correlation between segmental mobility and the location of antigenic determinants in proteins. Nature, 1984; 311(5982): 123-126
9. Tainer JA, Getzoff ED, Alexander H, et al. The reactivity of anti-peptide antibodies is a function of the atomic mobility of sites in a protein. Nature, 1984; 312(5990): 127-134
10. Jemmerson R, Paterson Y. Mobility and evolutionary variability factors in protein antigenicity. Nature, 1985; 317(6032): 89-90
11. Berzofsky JA. Intrinsic and extrinsic factors in protein antigenic structure. Science, 1985; 229:932-940
12. Thornton JM, Edwards MS, Taylor WR, et al. Location ofcontinuous' antigenic determinants in the protruding regions of proteins. EMBO J, 1986; 5(2): 409-413
13. Welling GW, Weijer WJ, van der Zee R, et al. Prediction of sequential antigenic regions in proteins. FEBS Lett, 1985; 188(2): 215-218
14. Frommel C. Use of the averaged mutation rate in pieces of protein sequences to predict the location of antigenic determinants. JTheorBiol 1988; 132(2):171-177
15. Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett, 1990; 276(1-2): 172-174
16. Barlow DJ, Edwards MS, Thornton JM. Continuous and discontinuous protein anligenic determinants. Nature, 1986; 322(6081): 747-748
17. Alix AJ. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine, 1999; 18(3-4): 311-314
18. Pellequer JL, Westhof E, Van Regenmortel MH. Correlation between the location of antigenic sites and the prediction of turns in proteins. Immunol Lett, 1993; 36(1): 83-99
19. Hofmann HJ, Hadge D, Holtje, et al. M,Protein-water interaction energies as predictor for antigenic determinants. Mol Immunol, 1990; (10): 1057-1060
20. Novotny J. Protein antigenicity: a thermodynamic approach. Mol Immunol, 1991; 28(3):201-207
21. Jameson BA, Wolf H. The antigenic index: a novel algorithm for predicting antigenic determinants. ComputAppl Biosci, 1988; 4(1): 181-186
22. WU YZ, ZHU XH. A new approach for B-cell epitope prediction in viral proteins. ChineseScience Bulletin, 1995; 40 (9): 761-763
23．万涛，孙涛，吴家金．蛋白顺序性抗原决定簇的多参数综合预测．中国免疫学杂志，1997；13(6)：329-333
24．陈兴，王更银，丛爱丽，等人DAO氨基酸序列片段B．细胞表位的多参数预测，免疫学257(5069)：502-507
25. Mit AG, Mariuzza RA, Phillips SE, et al. Three-dimensional structure of an antigen-antibody complex at 2.8 A resolution. Science. 1986; 233(4765): 747-753
26. Sela M. Antigenicity: some molecular aspects. Science 1969; 166(911): 1365-1374
27. Janin J. Surface and inside volumes in globular proteins. Nature, 1979; 277(5696): 491-492
28. Connolly ML. Solvent-accessible surfaces of proteins and nucleic acids. Science, 1983;221(4612): 709-713
29. Hopp TP, Woods KR. Prediction of protein antigenic determinants from amino acid sequences. ProcNatl Acad Sci USA, 1981; 78(6): 3824-3828
30. Hopp TP. Use of hydrophilicity plotting procedures to. identify protein antigenic segments and other interaction sites. Methods Enzymol, 1989; 178:571-585
31. Westhof E, Altschuh D, Moras D, et al. Correlation between segmental mobility and the location of antigenic determinants in proteins. Nature, 1984; 311(5982): 123-126
32. Tainer JA, Getzoff ED, Alexander H, et al. The reactivity of anti-peptide antibodies is a function of the atomic mobility of sites in a protein. Nature, 1984; 312(5990): 127-134
33. Jemmerson R, Paterson Y. Mobility and evolutionary variability factors in protein antigenicity. Nature, 1985; 317(6032): 89-90
34. Berzofsky JA. Intrinsic and extrinsic factors in protein antigenic structure. Science, 1985; 229:932-940
35. Thornton JM, Edwards MS, Taylor WR, et al. Location ofcontinuous' antigenic determinants in the protruding regions of proteins. EMBO J, 1986; 5(2): 409-413
36. Welling GW, Weijer WJ, van der Zee R, et al. Prediction of sequential antigenic regions in proteins. FEBS Lett, 1985; 188(2): 215-218
37. Frommel C. Use of the averaged mutation rate in pieces of protein sequences to predict the location of antigenic determinants. JTheorBiol 1988; 132(2):171-177
38. Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett, 1990; 276(1-2): 172-174
39. Barlow DJ, Edwards MS, Thornton JM. Continuous and discontinuous protein anligenic determinants. Nature, 1986; 322(6081): 747-748
40. Alix AJ. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine, 1999; 18(3-4): 311-314
41. Pellequer JL, Westhof E, Van Regenmortel MH. Correlation between the location of antigenic sites and the prediction of turns in proteins. Immunol Lett, 1993; 36(1): 83-99
42. Hofmann HJ, Hadge D, Holtje, et al. M,Protein-water interaction energies as predictor for antigenic determinants. Mol Immunol, 1990; (10): 1057-1060
43. Novotny J. Protein antigenicity: a thermodynamic approach. Mol Immunol, 1991; 28(3):201-207
44. Jameson BA, Wolf H. The antigenic index: a novel algorithm for predicting antigenic determinants. ComputAppl Biosci, 1988; 4(1): 181-186
45. WU YZ, ZHU XH. A new approach for B-cell epitope prediction in viral proteins. ChineseScience Bulletin, 1995; 40 (9): 761-763
46. Wan J, Liu W, Xu Q, Ren Y, Flower DR, Li T. SVRMHC prediction server for MHC-binding peptides. BMC Bioinformatics. 2006 Oct 23;7:463.
2. Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science 1973; 179:77-79
3. Patel PC. General aspects of biology and function of somatostatin. In: Weil C, Muller EE, Thorner MO, eds. Somatostatin. BERLIN: Springer Sandoz, 1992:1-16
4. Yamada Y, Post SR, Wang K, Tager HS, Bell GI, Seino S. Cloning and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Ptoc Natl Acad Sci USA 1992; 89:251-255
5. Davies N, Yates J, Kynaston H, Taylor BA, Jenkins SA. Effects of octreotide on liver regeneration and tumour growth in the regenerating liver. J Gastroenterol Hepatol 1997;12:47-53
6. Scherubl H, Bader M, Fett U, Hamm B, Schmidt-Gayk H, Koppenhagen K, Dop FJ, Riecken EO, Wiedenmann B. Somatostatin-receptor imaging of neuroendocrine gastroenteropancr eatic tumors. Gastroenterol 1993; 105:1705-1709
7. Lucarelli, P.; Mantuano, E.; Schiattarella, E.; Palmarino, R. :Evidence for linkage equilibrium between two RFLPs associated with the human SST locus. Hum. Genet. 78: 291-292,1988.
8. Lalley, P. A.; Sakaguchi, A. Y; Eddy, R. L.; Honey, N. H.; Bell, G. I.; Shen, L.-P.; Rutter, W. J.; Jacobs, J. W.; Heinrich, G.; Chin, W. W.; Naylor, S. L. : Mapping polypeptide hormone genes in the mouse: somatostatin, glucagon, caleitonin, and parathyroid hormone. Cytogenet. Cell Genet. 44: 92-97, 1987.
9. Naylor, S. L.; Sakaguchi, A. Y.; Shen, L.P.; Bell, G I.; Rutter, W. J.; Shows, T. B. : Polymorphic human somatostatin gene is located on chromosome 3. Proc. Nat. Acad. Sci. 80: 2686-2689, 1983.
10. Shen, L.-P.; Rutter, W. J. :Sequence of the human somatostatin Ⅰ gene. Science 224: 168-171, 1984.
11. Yacubova, E.; Komuro, H. :Stage-specific control of neuronal migration by somatostatin. Nature 4i5: 77-81, 2002.
12. Zabel, B. U.; Naylor, S. L.; Sakaguchi, A. Y.; Bell, G. I.; Shows, T. B. : High-resolution chromosomal localization of human genes for amylase, proopiomelanoeortin, somatostatin, and a DNA fragment (D3S1) by in situ hybridization. Proc. Nat. Acad Sci. 80: 6932-6936, 1983.
13. Yamada, Y.; Post, S. R.; Wang, K.; Tager, H. S.; Bell, G. I.; Seino, S. : Cloning and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Proc. Nat. Acad Sci. 89: 251-255, 1992.
14. Bruno, J. F.; Xu, Y.; Song, J.; Berelowitz, M. : Molecular cloning and functional expression of a brain-specific somatostatin receptor. Proc. Nat. Acad Sci. 89: 11151-11155, 1992.
15. Brinkmeier, M. L.; Camper, S. A. : Localization of somatostatin receptor genes on mouse chromosomes 2, 11, 12, 15, and 17: correlation with growth QTLs. Genomics 43: 9-14, 1997.
16. Kubota, A.; Yamada, Y.; Kagimoto, S.; Shimatsu, A.; Imamura, M.; Tsuda, K.; Imura, H.; Seino, S.; Seino, Y. : Identification of somatostatin receptor subtypes and an implication for the efficacy of somatostatin analogue. SMS 201-995 in treatment of human endocrine tumors. J.. CIin. Invest. 93: 1321-1325, 1994.
17．陈凯先等，计算机辅助药物设计：原理，方法及应用上海科学技术出版社，2000．1
18. 18. Baldwin, J. M. 1997. An alpha-carbon template for the transmembrane helices in the rhodopsin family of G-protein-coupled receptos. J. Mol. Biol. 272:144-164
19. Dhawan, B. N., F. Cesselin, R. Raghubir, T. Reisine, P. B. Bradley, P. S. Portoghese, and M. Hamon. 1996! Intemational Union of Pharmacology. Ⅻ. Classification of opioid receptors. Pharmacol. Rev. 48:567-596
20. Grigorieff, N., T. A. Ceska, K. H. Downing, J. M. Baldwin, and R. Henderson. 1996. Electron-crystallographic refinement of the structure of bacteriorhodopsin. J. Mol. Biol. 259:393-421
21. McDonald, I. K., and J. M. Thornton. 1994. Satisfying hydrogen bonding potential in proteins. J. Mol. Biol. 238:777-793
22. Lomize, A. L., I. D. Pogozheva, and H. I. Mosberg. 1996. Development of a model for the opioid receptor .pharmacophore. 3. Comparison of the cyclic tetrapeptide, Tyr-c [D-Cys-Phe-D-Phe] OH with other conformationally constrained δ-receptor selective ligands. Biopolymers. 38:221-234
23. Lomize, A. L., I. D. Pogozheva, and H. I. Mosberg. 1996. Development of a model for the opioid receptor pharmacophore. 3. Comparison of the cyclic tetrapeptide, Tyr-c[D-Cys-Phe-D-Phe]OH with other conformationally constrained &receptor selective ligands. Biopolymers, 38:221-234[Medline].
24. Lomize, A.L., I.D. Pogozheva, and H.I. Mosberg. 1998. Structural organization of G-protein-coupled receptors. Perspect. Drug Discovery Design. (in press).
25. Louie, G. V., and G. D. Brayer. 1989. A polypeptide chain-refolding event occurs in the Gly82 variant of yeast iso-l-cytochrome c. J. Mol. Biol. 209:313-322.
26. Walter R. P. Scott, Philippe H. Hulnenberger, Ilario G. Tironi, Alan E. Mark, Salomon R. Billeter, Jens Fennen, Andrew E. Torda, Thomas Huber, Peter Krulger, and Wilfred F. van Gunsteren The GROMOS Biomolecular Simulation Program Package J. Phys. Chem. A 1999, 103, 3596-3607
27. van Gunsteren, W. F.; Billeter, S. R.; Eising, A. A.; Hu"nenberger,P. H.; Kru"ger, P.; Mark, A. E.; Scott, W. R. P.; Tironi, I. G. Biomolecular Simulation: The GROMOS96 Manual and User Guide. VdF: Hochschulverl.ag AG an der ETH Zu"rich and BIOMOS b.v, Zu"rich, Groningen, 1996; ISBN 3 7281 2422 2.
28. van Gunsteren, W. F.; Billeter, S. R.; Eising, A. A.; Hu"nenberger, P. H.; Kru"ger, P.; Mark, A. E.; Scott, W. R. P.; Tironi, I. G. Biomolecular Simulation: The GR OMOS96 Manual and User Guide. VdF: Hochschulverlag AG an der ETH Zu"rich and BIOMOS b.v, Zu"rich, Groningen, 1996;ISBN 3 7281 2422 2.
29. Bemstein, F. C.; Koetzle, T. F.; Williams, G. J. B.; Meyer, E. F.; Brice, M. D.; Rodgers, J. R.; Ken_nard, O.; Shimanouchi, T.; Tasumi, M. J.Mol. Biol. 1977, 112, 535-542.
30. Havel, T.; Wu"thrich, K. Bull. Math. Biol. 1984, 46, 673-698.
31. Braun, W.; Go, N. J. Mol. Biol. 1985, 186, 611-626.
32. Gu"ntert, P.; Braun, W.; Wu"thrich, K. J. MoL Biol. 1991, 217, 517-530.
33. Ryekaert, J.-P.; Ciccotti, G.; Berendsen, H. J. C. J. Comput. Phys. 1977, 23, 327-341.
34. van Gunsteren, W. F.; Berendsen, H. J. C. Mol. Phys. 1977, 34, 1311-1327.
35. Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; DiNola, A.; Haak, J. R. J. Chem. Phys. 1984, 81, 3684-3690.
36. van Gunsteren, W. F.; Berendsen, H. J. C. Mol. SimuL 1988, 1, 173-185.
37. Yun-yu, S.; Lu, W.; van Gunsteren, W. F. Mol. SimuL 1988, 1,369-383.
38. Zwanzig, R. W. J. Chem. Phys. 1954, 22, 1420-1426.
39. Qi, w; He, Z M,. J. Computers andApplied Chemistry. 2006, 09.
40. Sehwede T, Kopp J, Guex N, and Peitsch MC (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Research 31: 3381-3385.
41. Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modelling. Electrophoresis 18:2714-2723.
1. Krulich L, Dhariwal AP, McCann SM. Stimulatory and inhibitory effects of purified hypothalamic extracts on growth hormone release from rat pituitary in vitro. Endocrinology 1968; 83:783-790
2. Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science 1973;179:77-79
3. Patel PC. General aspects of biology and function of somatostatin. In: Weil C, Muller EE, Thorner MO, eds. Somatostatin. BERLIN: Springer Sandoz, 1992:1-16
4. Yamada Y, Post SR, Wang K, Tager HS, Bell GI, Seino S. Cloning and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Ptoc Natl Acad Sci USA 1992; 89:251-255
5. Davies N, Yates J, Kynaston H, Taylor BA, Jenkins SA. Effects of octreotide on liver regeneration and tumour growth in the regenerating liver. J Gastroenterol Hepatol 1997; 12:47-53
6. Scherubl H, Bader M, Fett U, Hamm B, Schmidt-Gayk H, Koppenhagen K, Dop FJ, Riecken EO, Wiedenmann B. Somatostatin-receptor imaging of neuroendocrine gastroenteropancr eatic tumors. Gastroenterol 1993;105:1705-1709
7. Veber DF, Holly FW, Nutt RF, Bergstrand SJ, Brady SF, Hirschmann R, Glitzer MS, Saperstein R. Highly active cyclic and bicyclic somatostatin analogues of reduced ring size. Nature 1979;280:512-514
8. Schally AV. Oncological applications of somatostatin analogues. Cancer Res 1988;48:6977-6985
9. Keri GY, Erchegyi J, Horvath A, Mezo I, Idei M, Vantus T, Balogh A, Vadasz Z, Bokonyi G, Seprodi J, Teplan I, Csuka O, Tejeda M, Gaal D, Szegedi Z, Szende B, Roze C, Kalthoff H, Ullrich A. A tumor-selective somatostatin analogue (TT-232) with strong in vitro and in vivo antitumor activity. Ptoc NatlAcad Sci USA 1996;93:12513-12518
10. Falb E, Salitra Y, Yechezkel T, Bracha M, Litman P, Olender R, Rosenfeld R, Senderowitz H, Jiang S, Goodman M. A bicyclic and hsst2 selective somatostatin analogue: design, synthesis, conformational analysis and binding. Bioorg Med Chem 2001; 9:3255-3264
11. Bauer W, Briner U, Doepfner W, Hailer R, Huguenin R, Marbach P, Petcher TJ, Pless. SMS 201-995: a very potent and selective octapeptide analogue of somatostatin with prolonged action. Life Sci 1982; 1:1133-1140
12．陈凯先等，计算机辅助药物设计：原理，方法及应用上海科学技术出版社，2000．1
13. Altschul S.F., Madden T.L., Schaffer A.A., Zhang J., Zhang Z., Miller W.,Lipman D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389-3402 1997).
14. Schwede T, Kopp J, Guex N, and Peitsch MC (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Research 31: 3381-3385.
15. Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modelling. Electrophoresis 18:2714-2723.
16. Peitsch, M. C. (1995) Protein modeling by E-mail Bio/Technology 13,658-660.
17. P.E. Smith and W.F. van Gunsteren Methods for the evaluation of long-range electrostatic forces in computer simulations of molecular systems In: "Computer Simulation of Biomolecular Systems, Theoretical and Experimental Applications", Vol. 2,
18. W.F. van Gunsteren, P.K. Weiner, A.J. Wilkinson eds., Escom Science Publishers, Leiden, The Netherlands, (1993), pp. 182-212
19. W.F. van Gunsteren, P.M. King and A.E. Mark Fundamentals of drug design from a biophysical viewpoint Quart. Rev. Biophysics 27 (1994) 435-481
20. W.F. van Gunsteren, T. Huber and A.E. Torda Biomolecular Modelling: Overview of Types of Methods to Search and Sample Conformational Space in: Proceedings of the 1st European Conference on Computational Chemistry, American Institute of Physics Conf. Proc, 330 (1995) pp. 253-268
21. W.F. van Gunsteren, P.H. Hunenberger, A.E. Mark, P.E. Smith and I.G. Tironi Computer simulation of protein motion Computer Phys. Communications 91 (1995) 305-319
22. Vakser, I.A., 1995, Protein docking for low-resolution structures, Protein Eng., 8:371- 377. (Low-resolution protein docking).
23. Vakser, I.A., 1996, Long-distance potentials: An approach to the multiple-minima problem in ligand-receptor interaction, Protein Eng., 9:37-41. (Interpretation of low-resolution docking in terms of energy potentials)
24. Vakser, I.A., 1996, Low-resolution docking: Prediction of complexes for underdetermined structures, Biopolymers , 39:455-464. (Validation of low-resolution docking).
25. Vakser, I.A., 1996, Main-chain complementarity in protein-protein recognition, Protein Eng., 9:741-744. (Docking of C-alpha structures).
26. Vakser, I.A., 1997, Evaluation of GRAMM low-resolution docking methodology on the hemagglutinin-antibody complex, Proteins , Suppl. 1:226-230. (GRAMM performance at CASP).
27. Vakser, I.A., Matar, O.G., Lam, C.F., 1999, A systematic study of low-resolution recognition in protein-protein complexes,Proc. Natl. Acad. Sci. USA, 96:8477-8482. (Large scale low-resolution docking).
1. Krulich L, Dhariwal AP, McCann SM. Stimulatory and inhibitory effects of purified hypothalamic extracts on growth hormone release from rat pituitary in vitro. Endocrinology 1968; 83:783-790
2. Brazeau P, Vale W, Burgus R, Ling N, Butcher M, Rivier J, Guillemin R. Hypothalamic polypeptide that inhibits the secretion of immunoreactive pituitary growth hormone. Science 1973;179:77-79
3. Patel PC. General aspects of biology and function of somatostatin. In: Weil C, Muller EE, Thomer MO, eds. Somatostatin. BERLIN: Springer Sandoz, 1992:1-16
4. Yamada Y, Post SR, Wang K, Tager HS, Bell GI, Seino S. Cloning.and functional characterization of a family of human and mouse somatostatin receptors expressed in brain, gastrointestinal tract, and kidney. Ptoc Natl Acad SciUSA 1992; 89:251-255
5. J.H. Jones,'Amino-acid,Peptide and Protein',Edit by G.T.Young, Vol.1. 174-210,1969,The Chemical Sol ,London
6．陈长庆，黄惟德，多肽合成，科学出版社，1984．
7. Merrifield R B. J. Am. Chem. Soc. 1963,85:2149
8．王德心，化学试剂，2003，26：37
1. Galtia KC, Ronco PM, Verrust PJ, et al three-dimensional structure of an angiotensin 257(5069): 502-507
2. Amit AG, Mariuzza RA, Phillips SE, et al. Three-dimensional structure of an antigen-antibody complex at 2.8 A resolution. Science. 1986; 233(4765): 747-753
3. Sela M. Antigenicity: some molecular aspects. Science-1969; 166(911): 1365-1374
4. Janin J. Surface and inside volumes in globular proteins. Nature, 1979; 277(5696): 491-492
5. Connolly ML. Solvent-accessible surfaces of proteins and nucleic acids. Science, 19.83 ;221(4612): 709-713
6. Hopp TP, Woods KR. Prediction of protein antigenic determinants from amino acid sequences. ProcNatl Acad Sci USA, 1981; 78(6): 3824-3828
7. Hopp TP. Use of hydrophilicity plotting procedures to identify protein antigenic segments and other interaction sites. Methods Enzymol, 1989; 178:571-585
8. Westhof E, Altschuh D, Moras D, et al. Correlation between segmental mobility and the location of antigenic determinants in proteins. Nature, 1984; 311(5982): 123-126
9. Tainer JA, Getzoff ED, Alexander H, et al. The reactivity of anti-peptide antibodies is a function of the atomic mobility of sites in a protein. Nature, 1984; 312(5990): 127-134
10. Jemmerson R, Paterson Y. Mobility and evolutionary variability factors in protein antigenicity. Nature, 1985; 317(6032): 89-90
11. Berzofsky JA. Intrinsic and extrinsic factors in protein antigenic structure. Science, 1985; 229:932-940
12. Thornton JM, Edwards MS, Taylor WR, et al. Location ofcontinuous' antigenic determinants in the protruding regions of proteins. EMBO J, 1986; 5(2): 409-413
13. Welling GW, Weijer WJ, van der Zee R, et al. Prediction of sequential antigenic regions in proteins. FEBS Lett, 1985; 188(2): 215-218
14. Frommel C. Use of the averaged mutation rate in pieces of protein sequences to predict the location of antigenic determinants. JTheorBiol 1988; 132(2):171-177
15. Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett, 1990; 276(1-2): 172-174
16. Barlow DJ, Edwards MS, Thornton JM. Continuous and discontinuous protein anligenic determinants. Nature, 1986; 322(6081): 747-748
17. Alix AJ. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine, 1999; 18(3-4): 311-314
18. Pellequer JL, Westhof E, Van Regenmortel MH. Correlation between the location of antigenic sites and the prediction of turns in proteins. Immunol Lett, 1993; 36(1): 83-99
19. Hofmann HJ, Hadge D, Holtje, et al. M,Protein-water interaction energies as predictor for antigenic determinants. Mol Immunol, 1990; (10): 1057-1060
20. Novotny J. Protein antigenicity: a thermodynamic approach. Mol Immunol, 1991; 28(3):201-207
21. Jameson BA, Wolf H. The antigenic index: a novel algorithm for predicting antigenic determinants. ComputAppl Biosci, 1988; 4(1): 181-186
22. WU YZ, ZHU XH. A new approach for B-cell epitope prediction in viral proteins. ChineseScience Bulletin, 1995; 40 (9): 761-763
23．万涛，孙涛，吴家金．蛋白顺序性抗原决定簇的多参数综合预测．中国免疫学杂志，1997；13(6)：329-333
24．陈兴，王更银，丛爱丽，等人DAO氨基酸序列片段B．细胞表位的多参数预测，免疫学257(5069)：502-507
25. Mit AG, Mariuzza RA, Phillips SE, et al. Three-dimensional structure of an antigen-antibody complex at 2.8 A resolution. Science. 1986; 233(4765): 747-753
26. Sela M. Antigenicity: some molecular aspects. Science 1969; 166(911): 1365-1374
27. Janin J. Surface and inside volumes in globular proteins. Nature, 1979; 277(5696): 491-492
28. Connolly ML. Solvent-accessible surfaces of proteins and nucleic acids. Science, 1983;221(4612): 709-713
29. Hopp TP, Woods KR. Prediction of protein antigenic determinants from amino acid sequences. ProcNatl Acad Sci USA, 1981; 78(6): 3824-3828
30. Hopp TP. Use of hydrophilicity plotting procedures to. identify protein antigenic segments and other interaction sites. Methods Enzymol, 1989; 178:571-585
31. Westhof E, Altschuh D, Moras D, et al. Correlation between segmental mobility and the location of antigenic determinants in proteins. Nature, 1984; 311(5982): 123-126
32. Tainer JA, Getzoff ED, Alexander H, et al. The reactivity of anti-peptide antibodies is a function of the atomic mobility of sites in a protein. Nature, 1984; 312(5990): 127-134
33. Jemmerson R, Paterson Y. Mobility and evolutionary variability factors in protein antigenicity. Nature, 1985; 317(6032): 89-90
34. Berzofsky JA. Intrinsic and extrinsic factors in protein antigenic structure. Science, 1985; 229:932-940
35. Thornton JM, Edwards MS, Taylor WR, et al. Location ofcontinuous' antigenic determinants in the protruding regions of proteins. EMBO J, 1986; 5(2): 409-413
36. Welling GW, Weijer WJ, van der Zee R, et al. Prediction of sequential antigenic regions in proteins. FEBS Lett, 1985; 188(2): 215-218
37. Frommel C. Use of the averaged mutation rate in pieces of protein sequences to predict the location of antigenic determinants. JTheorBiol 1988; 132(2):171-177
38. Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett, 1990; 276(1-2): 172-174
39. Barlow DJ, Edwards MS, Thornton JM. Continuous and discontinuous protein anligenic determinants. Nature, 1986; 322(6081): 747-748
40. Alix AJ. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine, 1999; 18(3-4): 311-314
41. Pellequer JL, Westhof E, Van Regenmortel MH. Correlation between the location of antigenic sites and the prediction of turns in proteins. Immunol Lett, 1993; 36(1): 83-99
42. Hofmann HJ, Hadge D, Holtje, et al. M,Protein-water interaction energies as predictor for antigenic determinants. Mol Immunol, 1990; (10): 1057-1060
43. Novotny J. Protein antigenicity: a thermodynamic approach. Mol Immunol, 1991; 28(3):201-207
44. Jameson BA, Wolf H. The antigenic index: a novel algorithm for predicting antigenic determinants. ComputAppl Biosci, 1988; 4(1): 181-186
45. WU YZ, ZHU XH. A new approach for B-cell epitope prediction in viral proteins. ChineseScience Bulletin, 1995; 40 (9): 761-763
46. Wan J, Liu W, Xu Q, Ren Y, Flower DR, Li T. SVRMHC prediction server for MHC-binding peptides. BMC Bioinformatics. 2006 Oct 23;7:463.