血管紧张素转换酶与抑制肽结合模式的分子动力学研究

doi:10.7503/cjcu20170007

高等学校化学学报 ›› 2017, Vol. 38 ›› Issue (7): 1216.doi: 10.7503/cjcu20170007

血管紧张素转换酶与抑制肽结合模式的分子动力学研究

王嵩¹, 管珊珊^1,², 万永凤¹, 单亚明², 张浩¹()

1. 吉林大学理论化学研究所理论化学计算实验室, 长春 130061
2. 吉林大学生命科学学院, 艾滋病疫苗国家工程实验室, 长春 130012

收稿日期:2017-01-05 出版日期:2017-07-10 发布日期:2017-06-20
作者简介:联系人简介: 张浩, 男, 博士, 副教授, 主要从事理论化学计算研究. E-mail: stringbell@jlu.edu.cn
基金资助:
国家自然科学基金(批准号: 21443008)、吉林省教育厅十三五规划项目(批准号: 2016406, 2016408)、徐州市玛泰生物科技有限公司科技攻关项目(批准号: 2016220101000815, 3R2173651449)和吉林大学研究生创新基金(批准号: 2016008)资助

Molecular Dynamics Simulation Study on the Binding Modes of Angiotensin-converting Enzyme with Inhibitory Peptides^†

WANG Song¹, GUAN Shanshan^1,², WAN Yongfeng¹, SHAN Yaming², ZHANG Hao^1,^*()

1. Laboratory of Theoretical and Computational Chemistry, Institute of Theoretical Chemistry,Jilin University, Changchun 130061, China
2. National Engineering Laboratory For AIDS Vaccine, School of Life Science,Jilin University, Changchun 130012, China

Received:2017-01-05 Online:2017-07-10 Published:2017-06-20
Contact: ZHANG Hao E-mail:stringbell@jlu.edu.cn
Supported by:
† Supported by the National Natural Science Foundation of China(No.21443008), the 13th Five-Year Plan of Jilin Provincial Department of Education, China(Nos.2016406, 2016408), the Project of Xuzhou Mapeptide Biotechnology Co, Ltd Science and Technology, China(Nos.2016220101000815, 3R2173651449) and the Project of the Graduate Innovation Fund of Jilin University, China(No.2016008)

摘要/Abstract

摘要：

应用分子模拟方法研究了血管紧张素转换酶(Angiotensin-converting enzyme, ACE)C端结构域(C-domain)与两种抑制肽(RIGLF/AHEPVK)的结合机制, 预测了两个体系的结合模式, 提出在C-domain-RIGLF中His353, Asp377, Asp453, Phe457, His513, Tyr523和Phe527为RIGLF主要结合残基, 而在C-domain-AHEPVK中Gln281, His353, Ser355, Glu384, Lys511, His513和Tyr523等残基起关键作用. 应用结合自由能计算比较了两个体系的结合能力, 结果表明, RIGLF和AHEPVK均与C-domain活性位点残基存在较强作用, 且AHEPVK对C-domain的结合能力较强, 与实验结果一致.

关键词: 血管紧张素转换酶, 抑制肽, 分子对接, 分子动力学模拟, 结合自由能计算

Abstract:

Binding modes of C-domain of Angiotensin-converting enzyme(ACE) and two peptides RIGLF and AHEPVK which had competitive inhibited potency against ACE, C-domain-RIGLF and C-domain-AHEPVK were investigated with molecular docking, molecular dynamics simulation, and binding free energy, calculation. The calculation results indicate that vital binding residues in C-domain-RIGLF are His353, Asp377, Asp453, Phe457, His513, Tyr523 and Phe527, while key residues in C-domain-AHEPVK are Gln281, His353, Ser355, Glu384, Lys511, His513 and Tyr523. The binding ability between C-domain-RIGLF and C-domain-AHEPVK were compared via MM-PBSA calculation. The calculated results indicate that AHEPVK binds C-domain more easily than RIGLF. The result is consistent with experimental data. The results have academic guidance meaning for exploring the mechanism of how foodborne peptide inhibitors bind to ACE and this work provides the clues for novel medicines design which are mainly aimed at ACE.

Key words: Angiotensin-converting enzyme, Inhibitory peptide, Molecular docking, Molecular dynamics simulation, Free energy calculation

中图分类号:

O641

TrendMD:

王嵩, 管珊珊, 万永凤, 单亚明, 张浩. 血管紧张素转换酶与抑制肽结合模式的分子动力学研究. 高等学校化学学报, 2017, 38(7): 1216.

WANG Song, GUAN Shanshan, WAN Yongfeng, SHAN Yaming, ZHANG Hao. Molecular Dynamics Simulation Study on the Binding Modes of Angiotensin-converting Enzyme with Inhibitory Peptides^†. Chem. J. Chinese Universities, 2017, 38(7): 1216.

图/表 6

Table 1 Simulation information of two complex systems

Simulation system	Simulation time/ns	Number of solvent molecules	Number of counter ions	Number of Cl^-/Zn²⁺
C-domain-RIGLF	100	27191	12 Na⁺	2/1
C-domain-AHEPVK	100	27187	13 Na⁺	2/1

Fig.1 RMSD of backbone Cα atoms of C-domain-RIGLF(a) and N-domain-AHEPVK(b) with respect to their initial structures as function of time during 100 ns

Fig.2 Predicted binding modes and key residues of two systems C-domain-RIGLF(A) and C-domain-AHEPVK(B)

Fig.3 Decomposition of the binding energy on per residue basis on two systems C-domain-RIGLF(A) and C-domain-AHEPVK(B) : the total binding energy contribution form per

Fig.4 Comparative B-factor between C-domain-RIGLF(A) and C-domain-AHEPVK(B)

Table 2 Calculated energy components, binding free energy of C-domain-RIGLF and C-domain-AHEPVK*

Energy component	C-domain-RIGLF	C-domain-AHEPVK
ΔE_vdw/(kJ·mol^-1)	-240.91	-252.80
ΔE_ele/(kJ·mol^-1)	-2371.28	-1906.96
ΔE_MM/(kJ·mol^-1)	-2612.19	-2159.72
ΔG_ele,sol/(kJ·mol^-1)	-41.49	-41.11
ΔG_nonpolar,sol/(kJ·mol^-1)	2419.64	1944.06
ΔG_sol/(kJ·mol^-1)	2378.14	1902.94
(Δ $G ele, sol$ +ΔE_ele)/(kJ·mol^-1)	-2412.77	-1948.08
(Δ $G nonpolar, so l$ +ΔE_vdw)/(kJ·mol^-1)	2178.73	1691.26
ΔG_total/(kJ·mol^-1)	-234.04	-256.82

Table 2 Calculated energy components, binding free energy of C-domain-RIGLF and C-domain-AHEPVK*

Energy component	C-domain-RIGLF	C-domain-AHEPVK
ΔE_vdw/(kJ·mol^-1)	-240.91	-252.80
ΔE_ele/(kJ·mol^-1)	-2371.28	-1906.96
ΔE_MM/(kJ·mol^-1)	-2612.19	-2159.72
ΔG_ele,sol/(kJ·mol^-1)	-41.49	-41.11
ΔG_nonpolar,sol/(kJ·mol^-1)	2419.64	1944.06
ΔG_sol/(kJ·mol^-1)	2378.14	1902.94
(Δ $G ele, sol$ +ΔE_ele)/(kJ·mol^-1)	-2412.77	-1948.08
(Δ $G nonpolar, so l$ +ΔE_vdw)/(kJ·mol^-1)	2178.73	1691.26
ΔG_total/(kJ·mol^-1)	-234.04	-256.82

参考文献 32

[1]	Tanzadehpanah H., Asoodeh A., Saberi M. R., Chamani J., Innov. Food Sci. Emerg., 2013, 18, 212—219
[2]	Pihlanto A., Virtanen T., Korhonen H., Int. Dairy. J., 2010, 20(1), 3—10
[3]	Masuyer G., Akif M., Czarny B., Beau F., Schwager S. L., Sturrock E. D., Isaac R. E., Dive V., Acharya K. R., FEBS J., 2014, 281(3), 943—956
[4]	Hu J., Igarashi A., Kamata M., Nakagawa H., J. Biol. Chem., 2001, 276(51), 47863—47868
[5]	Geng X. R., Tian G. T., Zhang W. W., Zhao Y. C., Zhao L. Y., Wang H. X., Ng T. B., Scientific Reports,2016, 6, 24130
[6]	Iwaniak A., Minkiewicz P., Darewicz M., Compr. Rev. Food Sci. F., 2014, 13(2), 114—134
[7]	Conrad N., Schwager S. L. U., Carmona A. K., Sturrock E. D., Biochemical and Biophysical Research Communications,2016, 481, 111—116
[8]	Feng S. M., Limwachiranon J., Luo Z. S., Shi X. D., Ru Q. M., International Journal of Food Science and Technology,2016, 51, 1610—1617
[9]	Orona-Tamayo D., Valverde M. E., Nieto-Rendon B., Paredes-López O., LWT-Food Science and Technology,2015, 64(1), 236—242
[10]	Forghani B., Zarei M., Ebrahimpour A., Philip R., Bakar J., Hamid A. A., Saari N., Journal of Functional Foods,2016, 20, 276—290
[11]	Norris R., O'Keeffe M. B., Poyarkov A., FitzGerald R. J., Food Chemistry,2015, 188, 210—217
[12]	Gangopadhyay N., Wynne K., O'Connor P., Gallagher E., Brunton N. P., Rai D. K., Hayes M., Food Chemistry,2016, 203, 367—374
[13]	Lau C. C., Abdullah N., Shuib A. S., Aminudin N., Food Chem., 2014, 148, 396—401
[14]	Morris G. M., Huey R., Lindstrom W., Sanner M. F., Belew R. K., Goodsell D. S., Olson A. J., J. Comput. Chem., 2009, 30(16), 2785—2791
[15]	Qian M.D., Shan Y. M., Guan S. S., Zhang H., Wang S., Han W. W., Journal of Chemical Information and Modeling, 2016, 56,2024—2034
[16]	Hou X., Du J., Zhang J., Du L., Fang H., Li M., Journal of Chemical Information and Modeling,2013, 53(1), 188—200
[17]	Masuyer G., Schwager S. L., Sturrock E. D., Isaac R. E., Acharya K. R., Scientific Reports,2012, 2, 717
[18]	Guan S. S., Han W. W., Zhang H., Wang S., Shan Y. M., Journal of Biomolecular Structure and Dynamics,2016, 34(1), 15—28
[19]	Discovery Studio 2.5, Accelrys Inc.: San Diego, CA., 2009
[20]	Wang X., Wu S., Xu D., Xie D., Guo H., Journal of Chemical Information and Modeling,2011, 51(5), 1074—1082
[21]	Hess B., Kutzner C., van Der Spoel D., Lindahl E., J. Chem. Theory Comput., 2008, 4(3), 435—447
[22]	Hornak V., Abel R., Okur A., Strockbine B., Roitberg A., Simmerling C.,Proteins,2006, 65(3), 712—725
[23]	Hess B., van der Vegt N. F. A.,J. Phys. Chem.B,2006, 110(35), 17616—17626
[24]	Berendsen H. J. C., Postma J. P. M., van Gunsteren W. F., DiNola A., Haak J. R., J. Chem. Phys., 1984, 81(8), 3684—3690
[25]	Darden T., York D., Pedersen L., J. Chem. Phys., 1993, 98(12), 10089—10092
[26]	Chen X. G., Zhao X. J., Wang S., Wang L. P., Li W., Sun C. C., Acta Chim. Sinica,2013, 71(02), 199—204
	(陈晓光, 赵晓杰, 王嵩, 王丽萍, 李惟, 孙家锺.化学学报, 2013, 71(02), 199—204)
[27]	Wang S., Zhao X., Zheng Q. C., Huang X. R., Sun C. C., Chem. J. Chinese Universities,2009, 30(8), 1641—1644
	(王嵩, 赵熹, 郑清川, 黄旭日, 孙家锺.高等学校化学学报, 2009, 30(8), 1641—1644)
[28]	Case D. A., Cheatham Ⅲ T. E., Darden T., Gohlke H., Luo R., Merz K. M. Jr., Onufriev A., Simmerling C., Wang B., Woods R. J., J. Comput. Chem., 2005, 26(16), 1668—1688
[29]	Case D.A., Darden T., Cheatham Ⅲ T. E., Simmerling C., Wang J. M., Duke R. E., Luo R., Crowley M., Walker R., Zhang W., Merz K. M. Jr., Wang B., Hayik S., Roitberg A., Seabra G., Kolossváry I., Wong K. F., Paesani F., Vanicek J., Wu X. W., Brozell S. R., Steinbrecher T., Gohlke H., Yang L. J., Tan C. H., Mongan J., Hornak V., Cui G. L., Mathews D. H., Seetin M. G., Sagui C., Babin V., Kollman P. A., AMBER 10, University of California,San Francisco, 2008
[30]	Pearlman D. A., Case D. A., Caldwell J. W., Ross W. S., Cheatham Ⅲ T. E., DeBol S., Ferguson D., Seibel G., Kollman P., Comp. Phys. Commun., 1995, 91, 1—41
[31]	Weik M., Ravelli R. B. G., Kryger G., McSweeney S., Raves M. L., Harel M., Gros P., Silman I., Kroon J., Sussman J. L., P. Natl. Acad. Sci. USA,2000, 97(2), 623—628
[32]	Obradovic Z., Peng K., Vucetic S., Radivojac P., Dunker A. K., Proteins,2005, 61(S7), 176—182

血管紧张素转换酶与抑制肽结合模式的分子动力学研究

Molecular Dynamics Simulation Study on the Binding Modes of Angiotensin-converting Enzyme with Inhibitory Peptides^†

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 6

参考文献 32

相关文章 15

编辑推荐

Metrics

本文评价

[1]	高志伟, 李军委, 史赛, 付强, 贾钧儒, 安海龙. 基于分子动力学模拟的TRPM8通道门控特性分析[J]. 高等学校化学学报, 2022, 43(6): 20220080.
[2]	胡波, 朱昊辰. 双层氧化石墨烯纳米体系中受限水的介电常数[J]. 高等学校化学学报, 2022, 43(2): 20210614.
[3]	雷晓彤, 金怡卿, 孟烜宇. 基于分子模拟方法预测PIP₂在双孔钾通道TREK-1上结合位点的研究[J]. 高等学校化学学报, 2021, 42(8): 2550.
[4]	李聪聪, 刘明皓, 韩佳睿, 朱镜璇, 韩葳葳, 李婉南. 基于分子动力学模拟的VmoLac非特异性底物催化活性的理论研究[J]. 高等学校化学学报, 2021, 42(8): 2518.
[5]	曾永辉, 言天英. 质子水合结构的振动态密度分析[J]. 高等学校化学学报, 2021, 42(6): 1855.
[6]	齐人睿, 李明昊, 常浩, 付学奇, 高波, 韩葳葳, 韩璐, 李婉南. 基于拉伸分子动力学模拟的黄嘌呤氧化酶抑制剂解离途径的理论研究[J]. 高等学校化学学报, 2021, 42(3): 758.
[7]	刘爱清, 徐文生, 徐晓雷, 陈继忠, 安立佳. 高分子/棒状纳米粒子复合物的分子动力学模拟[J]. 高等学校化学学报, 2021, 42(3): 875.
[8]	帅蝶, 赵美娟, 陈丙年, 王力. 4种Keggin型磷钼酸盐对蘑菇酪氨酸酶活性和黑色素生成的抑制及抗氧化作用[J]. 高等学校化学学报, 2021, 42(12): 3579.
[9]	杨举, 苏丽娇, 李灿花, 鲁佳佳, 杨俊丽, 古捷, 杨丽, 杨丽娟. 甘松新酮/磷酸盐柱[6]芳烃主客体络合行为[J]. 高等学校化学学报, 2021, 42(10): 3099.
[10]	张爱芹, 王嫚, 申刚义, 金军. 多溴联苯醚与人血清白蛋白相互作用的表面等离子体共振及分子对接[J]. 高等学校化学学报, 2020, 41(9): 2054.
[11]	王莲萍,李庆杰,刘晓艳,任跃英,杨秀伟. 基于UFLC-MS/分子模拟计算的吴茱萸醇提取物中胆碱酯酶抑制剂筛选[J]. 高等学校化学学报, 2020, 41(1): 111.
[12]	瞿思颖, 徐沁. 凝血因子Xa的S4口袋部分关键残基对利伐沙班结合的不同作用机制[J]. 高等学校化学学报, 2019, 40(9): 1918.
[13]	王晓霞, 马力通, 聂智华, 王正德, 崔金龙, 赵文渊, 赛华征. 多光谱法和分子对接模拟法研究黄腐酸与胃蛋白酶的相互作用[J]. 高等学校化学学报, 2019, 40(9): 1840.
[14]	马玉聪, 樊保民, 王满曼, 杨彪, 郝华, 孙辉, 张慧娟. 曲唑酮的两步法制备及对碳钢的缓蚀机理[J]. 高等学校化学学报, 2019, 40(8): 1706.
[15]	孙浩帆, 张凌怡, PATRICKNorman, 张维冰. 二芳基乙烯衍生物与DNA结合的分子动力学研究[J]. 高等学校化学学报, 2019, 40(6): 1229.

血管紧张素转换酶与抑制肽结合模式的分子动力学研究

Molecular Dynamics Simulation Study on the Binding Modes of Angiotensin-converting Enzyme with Inhibitory Peptides†

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 6

参考文献 32

相关文章 15

编辑推荐

Metrics

本文评价

Molecular Dynamics Simulation Study on the Binding Modes of Angiotensin-converting Enzyme with Inhibitory Peptides^†