基于天然底物和抑制剂的CD38非共价抑制剂的虚拟筛选及比较

doi:10.5246/jcps.2015.09.073

中国药学(英文版) ›› 2015, Vol. 24 ›› Issue (9): 572-580.DOI: 10.5246/jcps.2015.09.073

基于天然底物和抑制剂的CD38非共价抑制剂的虚拟筛选及比较

薛喜文¹, 朱文杰², 张亮仁¹, 赵永娟², 刘振明^1*

1. 北京大学医学部天然药物及仿生药物国家重点实验室, 北京 100191
2. 北京大学深圳研究生院, 广东深圳 518055

收稿日期:2015-05-18 修回日期:2015-06-10 出版日期:2015-09-18 发布日期:2015-06-18
通讯作者: Tel.: 86-10-82805514, Fax: 86-10-82802724, E-mail: zmliu@bjmu.edu.cn
基金资助:
National Natural Science Foundation of China (Grant No. 21272017 and 81172917).

Comparison and discovery of potential non-covalent CD38 inhibitors by virtual screening strategy based on natural substrates and known inhibitors

Xiwen Xue¹, Wenjie Zhu², Liangren Zhang¹, Yongjuan Zhao², Zhenming Liu^1*

1. State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
2. Shenzhen Graduate School, Peking University, Shenzhen, Guangdong 518055, China

Received:2015-05-18 Revised:2015-06-10 Online:2015-09-18 Published:2015-06-18
Contact: Tel.: 86-10-82805514, Fax: 86-10-82802724, E-mail: zmliu@bjmu.edu.cn
Supported by:
National Natural Science Foundation of China (Grant No. 21272017 and 81172917).

摘要/Abstract

摘要：

CD38是一类ADPR环化酶家族的II型或III型跨膜糖蛋白。作为一种多功能信号酶, 它广泛表达于多种组织和细胞中。CD38在体内能够催化NAD⁺(烟酰胺腺嘌呤二核苷酸)和NADP⁺(烟酰胺腺嘌呤二核苷酸磷酸)生成具有钙动员活性的第二信使核苷酸小分子: cADPR(环腺苷二磷酸核糖)和NAADP(烟酸腺嘌呤二核苷酸磷酸)等。通过作用于钙信号通路, 这些Ca²⁺信使小分子可以在生理条件下调控细胞内钙库钙离子的释放和外钙的内流, 进而调节细胞的功能与生命活动。本论文中, 采用基于配体和基于受体的虚拟筛选策略来比较野生型底物和已知抑制剂作为虚拟筛选第一步问询式的优劣性, 并得到了结构新颖的抑制剂分子。采用了OpenEye公司的ROCS与EON组件对SPECS库的共216 000个化合物以两类问询式进行相似性搜索, 一类是天然底物包括NAADP及NAD⁺, 一类是抑制剂分子H2。相似性搜索得到化合物后, 分别对每个化合物进行了结合模式分析及ADME预测等, 最终购买由天然底物出发得到的17个化合物及由已有抑制剂出发得到的10个化合物进行测活。根据对筛选得到的分子的分子量比较、分子活性比较、结合模式比较, 由抑制剂H2作为问询式出发更有可能得到结构新颖且活性更好的抑制剂。

关键词: CD38, 虚拟筛选, 天然底物, 非共价抑制剂

Abstract:

As a type II or III transmembrane glycoprotein, human CD38 is ubiquitously expressed in all mammalian tissues. CD38 is a multi-functional enzyme and a member of the ADP-ribosyl cyclase family, and it catalyzes nicotinamide adenine dinucleotide (NAD⁺) and nicotinamide adenine dinucleotide phosphate (NADP⁺) to two distinct Ca²⁺messengers as follows: cyclic ADP-ribose (cADPR) and nicotinic acid adenine dinucleotide phosphate (NAADP), respectively. Moreover, both cADPR and NAADP mediate mobilization of intracellular Ca²⁺targeting endoplasmic stores and the lysosomes, respectively. In this study, we combined ligand-based and structure-based virtual screening strategies to compare the inhibitor discovery efficacy based on natural substrates and the known inhibitors. The similarity queries towards SPECS database were carried out using ROCS and EON modules of OpenEye software. The hits were further docked to CD38 using AutoDock 4.05 program. In addition, ADME studies were also processed considering solubility in water and membrane permeability. Finally, we identified 17 compounds-based on natural substrates and 10 compounds based on known inhibitor models. The results showed that the known inhibitor H2-based model was more efficient in virtual screening of CD38 non-covalent inhibitors.

Key words: CD38, Virtual screening, Natural substrate, Non-covalent inhibitor

中图分类号:

R916

Supporting:

薛喜文, 朱文杰, 张亮仁, 赵永娟, 刘振明. 基于天然底物和抑制剂的CD38非共价抑制剂的虚拟筛选及比较[J]. 中国药学(英文版), 2015, 24(9): 572-580.

Xiwen Xue, Wenjie Zhu, Liangren Zhang, Yongjuan Zhao, Zhenming Liu. Comparison and discovery of potential non-covalent CD38 inhibitors by virtual screening strategy based on natural substrates and known inhibitors[J]. Journal of Chinese Pharmaceutical Sciences, 2015, 24(9): 572-580.

参考文献

[1] Reinherz, E.L.; Kung, P.C.; Goldstein, G.; Levey, R.H.; Schlossman, S.F. Proc. Natl. Acad. Sci. USA. 1980, 77, 1588-1592.

[2] Takasawa, S.; Tohgo, A.; Noguchi, N.; Koguma, T.; Nata, K.; Sugimoto, T.; Yonekura, H.; Okamoto, H. J. Biol. Chem. 1993, 268, 26052–26054.

[3] Tohgo, A.; Takasawa, S.; Noguchi, N.; Koguma, T.; Nata, K.; Sugimoto, T.; Furuya, Y.; Yonekura, H.; Okamoto, H. J. Biol. Chem. 1994, 269, 28555–28557.

[4] Lund, F.E.; Yu, N.; Kim, K.M.; Reth, M.; Howard, M.C. J. Immunol. 1996, 157, 1455–1467.

[5] Howard, M.; Grimaldi, J.; Bazan, J.; Lund, F.E.; Santos-Argumedo, L.; Parkhouse, R.M.; Walseth, T.F.; Lee, H.C. Science. 1993, 262, 1056–1059.

[6] Aarhus, R.; Graeff, R.M.; Dickey, D.M.; Walseth, T.F.; Lee, H.C. J. Biol. Chem. 1995, 270, 30327–30333.

[7] Ausiello, C.M.; la Sala, A.; Ramoni, C.; Urbani, F.; Funaro, A.; Malavasi, F. Cell Immunol. 1996, 173, 192–197.

[8] Ausiello, C.M.; Urbani, F.; la Sala, A.; Funaro, A.; Malavasi, F. Eur. J. Immunol. 1995, 25, 1477–1480

[9] Dianzani, U.; Funaro, A.; DiFranco, D.; Garbarino, G.; Bragardo, M.; Redoglia, V.; Buonfiglio, D.; De Monte, L.B.; Pileri, A.; Malavasi, F. J. Immunol. 1994, 153, 952–959.

[10] Deaglio, S.; Aydin, S.; Vaisitti, T.; Bergui, L.; Malavasi, F. Trends. Mol. Med. 2008, 14, 210–218.

[11] Guse, A.H. FEBS. J. 2005, 272, 4590–4597.

[12] Zhang, H.; Graeff, R.; Lee, H.C.; Hao, Q. Messenger. 2013, 2, 44–53.

[13] Lee, H. Sci. China Life Sci. 2011, 54, 699–711.

[14] Lin, H. Org. Biomol. Chem. 2007, 5, 2541–2554.

[15] Liu, Q.; Kriksunov, I.A.; Jiang, H.; Graeff, R.; Lin, H.; Lee, H.C.; Hao, Q. Chem. Biol. 2008, 15, 1068–1078.

[16] Liu, Q.; Kriksunov, I.A.; Graeff, R.; Munshi, C.; Lee, H.C.; Hao, Q. J. Biol. Chem. 2006, 281, 32861–32869.

[17] Sauve, A.A.; Schramm, V.L. Biochemistry. 2002, 41, 8455–8463.

[18] Muller-Steffner, H.M.; Malver, O.; Hosie, L. J. Biol. Chem. 1992, 267, 9606–9611.

[19] Sauve, A.A.; Deng, H.; Angeletti, R.H. Schramm, V.L. J. Am. Chem. Soc. 2000, 122, 7855–7859.

[20] Chen, Z.; Kwong, A.K.Y.; Yang, Z. Heterocycles. 2011, 83, 2837–2850.

[21] Kwong, A.K.; Chen, Z.; Zhang, H.; Leung, F.P.; Lam, C.M.; Ting, K.Y. ; Zhang, L.; Hao, Q.; Zhang, L.H.; Lee, H.C. Biochemistry. 2012, 51, 555–564.

[22] Wang, S.; Zhu, W.; Wang, X.; Li, J.; Zhang, K.; Zhang, L.; Zhao, Y.J.; Lee, H.C.; Zhang, L. Molecules. 2014, 19, 15754–15767.

[23] Zhou, Y.; Ting, K.Y.; Lam, C.M.C.; Kwong, A.K.; Xia, J.; Jin, H.; Liu, Z.; Zhang, L.; Lee, C.H.; Zhang, L. Chem. Med. Chem. 2012, 7, 223–228.

[24] Escande, C.; Nin, V.; Price, N.L.; Capellini, V.; Gomes, A.P.; Barbosa, M.T.; O'Neil, L.; White, T.A.; Sinclair, D.A.; Chini, E.N. Diabetes. 2013, 62, 1084–1093.

[25] Kellenberger, E.; Kuhn, I.; Schuber, F.; Muller-Steffner, H. Bioorg. Med. Chem. Lett. 2011, 21, 3939–3942.

[26] Zhang, S.; Xue, X.; Zhang, L.; Zhang, L; Liu, Z. Chem. Biol. Drug Des. 2015, [Epub ahead of print]. This article can be found online at http://onlinelibrary.wiley.com/doi/10.1111/cbdd.12606/pdf

[27] Gao, T.; Niu, Y.; Wang, D.; Lei, X.P.; Hu, Y.H. J. Chin. Pharm. Sci. 2008, 17, 75–78.

[28] Kruger, D.M.; Evers, A. Chem. Med. Chem. 2010, 5, 148–158.

[29] Rush, T.S.III; Grant, J.A.; Mosyak, L.; Nicholls, A. J. Med. Chem. 2005, 48, 1489–1495.

[30] Nicholls, A.; MacCuish, N.E.; MacCuish, J.D. J. Comput. Aided. Mol. Des. 2004, 18, 451–474.

[31] Liu, Q.; Kriksunov, I.A.; Graeff, R.; Munshi, C.; Lee, H.C.; Hao, Q. J. Biol. Chem. 2006, 281, 32861–32869.

[32] GOLD Evaluation Version 3.0.1. Cambridge Crystallographic Data Centre: Cambridge, UK. 2006.

[33] Morris, G.M.; Goodsell, D.S.; Halliday, R.S.; Huey, R.; Hart, W.E.; Belew, R.K.; Olson, A.J. Comput. Chem. 1998, 19, 1639–1662.

[34] Maynard, A.L.; Kulkarni, A.; Goupil-Lamy, A. Discovery Studio 2.5, Release 2.5, San Diego: Accelrys Software Inc.: 2009.

[35] Schweitzer, K.; Mayr, G.W.; Guse, A.H. Anal. Biochem. 2001, 299, 218–226.

[36] Egan, W.J.; Merz, K.M.Jr.; Baldwin, J.J. J. Med. Chem. 2000, 43, 3867–3877.

[37] Pollastri, M.P. Curr. Protoc. Pharmacol. 2010, Chapter 9, Unit 9, 12.

[38] Ghose, A.K.; Crippen, G.M. J. Chem. Inf. Comput. Sci. 1987, 27, 21–35.

[39] Pade, V.; Stavchansky, S. J. Pharm. Sci. 1998, 87, 1604–1607.

基于天然底物和抑制剂的CD38非共价抑制剂的虚拟筛选及比较

Comparison and discovery of potential non-covalent CD38 inhibitors by virtual screening strategy based on natural substrates and known inhibitors

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

编辑推荐

Metrics

本文评价

[1]	迟骁玮, 黎奇, 钟毅, 龚桐, 衣楚潇, 张亮仁, 刘振明. 基于虚拟筛选发现潜在的黄嘌呤氧化酶抑制剂[J]. 中国药学(英文版), 2023, 32(8): 626-635.
[2]	刘琛楠, 王倩, 韩江雪, 刘思含, 肖春玲, 关艳, 李兴华, 王颖, 王潇, 蒙建州, 甘茂罗, 刘忆霜. 金属-β-内酰胺酶L1抑制剂的虚拟筛选和高通量实验测试[J]. 中国药学(英文版), 2021, 30(10): 806-812.
[3]	邓华, 高超, 位灯国, 刘思思. 基于端粒G-四链体结构的三阴性乳腺癌细胞抑制剂的虚拟筛选[J]. 中国药学(英文版), 2020, 29(6): 383-389.
[4]	李亦博, 周鑫, 刘振明, 张亮仁. 基于深度分子生成模型的类天然产物虚拟筛选库设计[J]. 中国药学(英文版), 2018, 27(7): 451-459.
[5]	李建国, 裴芬, 朱文杰, 金宏威, 赵永娟, 张亮仁, 李汉璋, 张礼和. NMN类似物2'位取代基对其CD38酶抑制活性的影响[J]. 中国药学(英文版), 2015, 24(8): 514-523.
[6]	杨冠宇, 孙琦, 王超, 梁磊, 许凤荣, 牛彦, 徐萍. 磺胺类黄酮衍生物20S蛋白酶体抑制剂的设计、合成与活性评价[J]. 中国药学(英文版), 2014, 23(9): 626-630.
[7]	杨志瑜, 吕炜, 田然, 金宏威, 曾慧慧^*. 5-羟色胺1A受体配体发现新思路: 基于受体的药效团[J]. , 2009, 18(2): 151-155.
[8]	高广涛, 牛彦, 王栋, 雷小平^, 胡应和^*. 药效团模型法寻找M₁受体激动剂[J]. , 2008, 17(1): 75-78.