反向对接的选择性与非选择性抑制剂找靶评价: Glide个案研究

doi:10.5246/jcps.2020.10.063

中国药学(英文版) ›› 2020, Vol. 29 ›› Issue (10): 679-688.DOI: 10.5246/jcps.2020.10.063

• 【研究论文】 • 下一篇

反向对接的选择性与非选择性抑制剂找靶评价: Glide个案研究

李明娜¹, 吴兴², 张亮仁^1*, 刘振明^1*

1. 北京大学医学部药学院天然药物及仿生药物国家重点实验室, 北京 100191
2. 横店集团控股有限公司, 浙江杭州 310007

收稿日期:2020-04-16 修回日期:2020-07-15 出版日期:2020-10-31 发布日期:2020-08-20
通讯作者: Tel.: +86-10-82805281, E-mail: zmliu@bjmu.edu.cn
基金资助:
National Key Research and Development Project (Grant No. 2019YFC1708900), the National Natural Science Foundation of China (Grant No. 81872730, 81673279, 21772005), National Major Scientific and Technological Special Project for Significant New Drugs Development (Grant No. 2018ZX09735001-003, 2019ZX09201005-001, 2019ZX09204-001) and Beijing Natural Science Foundation (Grant No. 7202088, 7172118).

Evaluating reverse docking on general and selective inhibitors: a case study about glide

Mingna Li¹, Xing Wu², Liangren Zhang^1*, 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. Hengdian Group Holdings Limited, Hangzhou 310007, China

Received:2020-04-16 Revised:2020-07-15 Online:2020-10-31 Published:2020-08-20
Contact: Tel.: +86-10-82805281, E-mail: zmliu@bjmu.edu.cn
Supported by:
National Key Research and Development Project (Grant No. 2019YFC1708900), the National Natural Science Foundation of China (Grant No. 81872730, 81673279, 21772005), National Major Scientific and Technological Special Project for Significant New Drugs Development (Grant No. 2018ZX09735001-003, 2019ZX09201005-001, 2019ZX09204-001) and Beijing Natural Science Foundation (Grant No. 7202088, 7172118).

摘要/Abstract

摘要：

反向对接作为一种靶标预测的有效工具, 有许多方面仍待探究。对反向对接软件的客观评价可以帮助我们更好地了解这些工具的长处与短处, 并在靶标预测的过程中起到指导作用。本研究中, 我们评估了Glide (SP)针对选择性抑制剂与非选择性抑制剂的靶标预测能力。结果说明针对不同配体, 对接打分的倾向可能存在差异, 因此总体打分抽样对帮助我们更好地理解某对配体受体间的对接打分具有重要的意义。另外, 对接时结合口袋的输入构象对对接结果存在一定的影响。Glide (SP)显示出较好的对非选择性抑制剂的靶标预测能力。然而, 其对于选择性抑制剂的靶标预测准确度相对较低, 说明该软件不适用于这方面的工作。针对COVID-19的案例研究表面凝血因子Xa可能是氯喹的潜在靶点。因此,我们认为对反向对接软件的进一步开发与靶点间打分差异的修正十分必要。

关键词: 反向对接, 靶标预测, 软件评估

Abstract:

As a powerful tool for target prediction, reverse docking remains largely unexplored. The objective evaluation of reversedocking software can help us know better about the strength and weakness of these tools, hence guiding us in target prediction. In the present study, we evaluated the target prediction power of Glide (SP) against general inhibitors and selective inhibitors. The results showed that the scoring tendency could be different for each ligand, and overall scoring sampling was necessary for a better understanding of the docking score for a certain protein-ligand pair. Besides, the input conformation of the binding pocket could affect the docking result. Glide (SP) showed a preferable performance on the target prediction of the general inhibitors. However, the accuracy of the target prediction of the selective inhibitors was relatively low, indicating that Glide (SP) might not be capable for this task. The case study about COVID-19 proved that coagulation factor Xa might be a potential target of chloroquine. Therefore, we recommend the further development of reverse docking tools and rectification of inter-target scoring bias.

Key words: Reverse docking, Target prediction, Software evaluation

中图分类号:

R916

Supporting:

李明娜, 吴兴, 张亮仁, 刘振明. 反向对接的选择性与非选择性抑制剂找靶评价: Glide个案研究[J]. 中国药学(英文版), 2020, 29(10): 679-688.

Mingna Li, Xing Wu, Liangren Zhang, Zhenming Liu. Evaluating reverse docking on general and selective inhibitors: a case study about glide[J]. Journal of Chinese Pharmaceutical Sciences, 2020, 29(10): 679-688.

参考文献

[1] Sydow, D.; Burggraaff, L.; Szengel, A.; van Vlijmen, H.W.T.; IJzerman, A.P.; van Westen, G.J.P.; Volkamer, A. Advances and challenges in computational target prediction. J. Chem. Inf. Model. 2019, 59, 1728-1742.

[2] da Matta, C.B.B.; de Queiroz, A.C.; Santos, M.S.; Alexandre-Moreira, M.S.; Gonçalves, V.T.; de Nigris del Cistia, C.; Sant’Anna, C.M.R.; DaCosta, J.B.N. Novel dialkylphosphorylhydrazones: Synthesis, leishmanicidal evaluation and theoretical investigation of the proposed mechanism of action. Eur. J. Med. Chem. 2015, 101, 1-12.

[3] Lim, T.G.; Lee, S.Y.; Huang, Z.N.; Lim, D.Y.; Chen, H.Y.; Jung, S.K.; Bode, A.M.; Lee, K.W.; Dong, Z.G. Curcumin suppresses proliferation of colon cancer cells by targeting CDK2. Cancer Prev. Res.( Phila). 2014, 7, 466-474.

[4] Wang, Z.Y.; Luo, S.Q.; Wan, Z.; Chen, C.Y.; Zhang, X.N.; Li, B.B.; Huang, G.L.; Chen, L.Y.; He, Z.W.; Huang, Z.N. Glabridin arrests cell cycle and inhibits proliferation of hepatocellular carcinoma by suppressing braf/MEK signaling pathway. Tumor Biol. 2016, 37, 5837-5846.

[5] Lapillo, M.; Tuccinardi, T.; Martinelli, A.; Macchia, M.; Giordano, A.; Poli, G. Extensive reliability evaluation of docking-based target-fishing strategies. Int. J. Mol. Sci. 2019, 20, 1023.

[6] Friesner, R.A.; Banks, J.L.; Murphy, R.B.; Halgren, T.A.; Klicic, J.J.; Mainz, D.T.; Repasky, M.P.; Knoll, E.H.; Shelley, M.; Perry, J.K.; Shaw, D.E.; Francis, P.; Shenkin, P.S. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem. 2004, 47, 1739-1749.

[7] Halgren, T.A.; Murphy, R.B.; Friesner, R.A.; Beard, H.S.; Frye, L.L.; Pollard, W.T.; Banks, J.L. Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J. Med. Chem. 2004, 47, 1750-1759.

[8] Schomburg, K.T.; Rarey, M. Benchmark data sets for structure-based computational target prediction. J. Chem. Inf. Model. 2014, 54, 2261-2274.

[9] Liu, Z.H.; Li, Y.; Han, L.; Li, J.; Liu, J.; Zhao, Z.X.; Nie, W.; Liu, Y.C.; Wang, R.X. PDB-wide collection of binding data: current status of the PDBbind database. Bioinformatics. 2015, 31, 405-412.

[10] Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The Protein Data Bank. Nucleic Acids Res. 2000, 28, 235-242.

[11] Wishart, D.S.; Feunang, Y.D.; Guo, A.C.; Lo, E.J.; Marcu, A.; Grant, J.R.; Sajed, T.; Johnson, D.; Li, C.; Sayeeda, Z.; Assempour, N.; Iynkkaran, I.; Liu, Y.F.; Maciejewski, A.; Gale, N.; Wilson, A.; Chin, L.; Cummings, R.; Le, D.; Pon, A.; Knox, C.; Wilson, M. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2018, 46, D1074-D1082.

[12] Kim, S.; Chen, J.; Cheng, T.J.; Gindulyte, A.; He, J.; He, S.Q.; Li, Q.L.; Shoemaker, B.A.; Thiessen, P.A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E.E. PubChem 2019 update: improved access to chemical data. Nucleic Acids Res. 2019, 47, D1102-D1109.

[13] Madhavi Sastry, G.; Adzhigirey, M.; Day, T.; Annabhimoju, R.; Sherman, W. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J. Comput. Aided Mol. Des. 2013, 27, 221-234.

[14] Harder, E.; Damm, W.; Maple, J.; Wu, C.J.; Reboul, M.; Xiang, J.Y.; Wang, L.L.; Lupyan, D.; Dahlgren, M.K.; Knight, J.L.; Kaus, J.W.; Cerutti, D.S.; Krilov, G.; Jorgensen, W.L.; Abel, R.; Friesner, R.A. OPLS3: a force field providing broad coverage of drug-like small molecules and proteins. J. Chem. Theory Comput. 2016, 12, 281-296.

[15] Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001, 46, 3-26.

[16] Wang, W.; Zhou, X.; He, W.L.; Fan, Y.; Chen, Y.Z.; Chen, X. The interprotein scoring noises in glide docking scores. Proteins: Struct. Funct. Bioinform. 2012, 80, 169-183

[17] Luo, Q.Y.; Zhao, L.; Hu, J.X.; Jin, H.W.; Liu, Z.M.; Zhang, L.R. The scoring bias in reverse docking and the score normalization strategy to improve success rate of target fishing. PLoS One. 2017, 12, e0171433.

[18] Kakodkar, P.; Kaka, N.; Baig, M.N. A comprehensive literature review on the clinical presentation, and management of the pandemic coronavirus disease 2019 (COVID-19). Cureus. 2020, 12, e7560.

[19] Ewing, W.R.; Becker, M.R.; Manetta, V.E.; Davis, R.S.; Pauls, H.W.; Mason, H.; Choi-Sledeski, Y.M.; Green, D.; Cha, D.; Spada, A.P.; Cheney, D.L.; Mason, J.S.; Maignan, S.; Guilloteau, J.P.; Brown, K.; Colussi, D.; Bentley, R.; Bostwick, J.; Kasiewski, C.J.; Morgan, S.R.; Leadley, R.J.; Dunwiddie, C.T.; Perrone, M.H.; Chu, V. Design and structure-activity relationships of potent and selective inhibitors of blood coagulation factor Xa. J. Med. Chem. 1999, 42, 3557-3571.

[20] Li, H.C.; Ma, J.; Zhang, H.; Cheng, Y.; Wang, X.; Hu, Z.W.; Li, N.; Deng, X.R.; Zhang, Y.; Zheng, X.Z.; Yang, F.; Weng, H.Y.; Dong, J.P.; Liu, J.W.; Wang, Y.Y.; Liu, X.M. Thoughts and practice on the treatment of severe and critical new coronavirus pneumonia. Chin. J.Tuberculosis Res. Dis. 2020, 43, E038.

反向对接的选择性与非选择性抑制剂找靶评价: Glide个案研究

Evaluating reverse docking on general and selective inhibitors: a case study about glide

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 15

编辑推荐

Metrics

本文评价

[1]	焦佩丽, 李奕言, 吴兴, 王昱曦, 毛蓓蓓, 金宏威, 张礼和, 张亮仁, 刘振明. 基于结构设计的新型mTOR抑制剂的抗宫颈癌活性研究[J]. 中国药学(英文版), 2020, 29(9): 603-616.
[2]	刘慧, 梁磊, 袁兰, 许凤荣, 牛彦, 王超, 徐萍. 氮杂芳香环并哒嗪酮类荧光探针的设计、合成和生物成像的应用[J]. 中国药学(英文版), 2019, 28(5): 298-315.
[3]	周北斗, 王欣, 翁智敏, 黄堡城, 马泽通, 于博, 阮丽琴, 胡栋宝. 氧杂蒽酮的合成和抗肿瘤、抑制酪氨酸酶和抑制血小板聚集活性研究[J]. 中国药学(英文版), 2019, 28(4): 247-256.
[4]	王新童, 邹文星, 肖浩然, 谢文军, 李鑫, 卞希玲, 孙崎, 王克威. 呋喃并[3,2-b]吡啶类化合物对α7尼古丁乙酰胆碱受体负向变构调节作用的电生理学评价[J]. 中国药学(英文版), 2019, 28(3): 160-166.
[5]	贺明, 谢宝花, 贺培, 周海兵, 黄胜堂, 董春娥. 喹啉-苯并吡喃类新型乙酰胆碱酯酶抑制剂的微波一锅法的设计合成以及生物活性研究[J]. 中国药学(英文版), 2018, 27(11): 735-752.
[6]	Olatunde S. Oladeji, Monisola I. Ikhile, Carine M. D. Fotsing, Messai Mamo, Patrick G. Ndungu, Derek T. Ndinteh. Synthesis of 4-aminoantipyrine Schiff bases and their antimicrobial activities[J]. 中国药学(英文版), 2018, 27(11): 753-766.
[7]	李灿, 李宏月, 孙静, 席丹丹, 王超, 梁磊, 许凤荣, 牛彦, 徐萍. 5-苄基-2-苯基嘧啶-4(3H)-酮类新型MEK抑制剂基于结构的设计与合成[J]. 中国药学(英文版), 2018, 27(10): 686-695.
[8]	Dini Kesuma, Siswandono, Bambang Tri Purwanto, Marcellino Rudyanto. Synthesis of N-(phenylcarbamothioyl)-benzamide derivatives and their cytotoxic activity against MCF-7 cells[J]. 中国药学(英文版), 2018, 27(10): 696-702.
[9]	马玉翠, 徐靓, 吴翠, 巢志茂. 反式-3-苯基-2-丙烯酸的晶体结构[J]. 中国药学(英文版), 2018, 27(9): 644-648.
[10]	黄宗泽, 王新童, 孟盈, 李鑫, 肖浩然, 卞希玲, 王克威, 孙崎. 3H-喹唑啉-4-酮衍生物的设计、合成及其α7尼古丁乙酰胆碱受体正向变构调节作用评价[J]. 中国药学(英文版), 2018, 27(8): 540-552.
[11]	黄慧霞, 刘会雪, 马孝杰, 管辉, 杨晓改. 氯化镧和柠檬酸镧在胃肠道以磷酸镧微粒为转化物种且主要通过M细胞进行转运吸收[J]. 中国药学(英文版), 2018, 27(8): 553-564.
[12]	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.
[13]	孟盈, 邹文星, 黄宗泽, 王新童, 焦文宣, 谢文军, 卞希玲, 王克威, 孙崎. 无配体钯催化的Suzuki羰基化反应研究及其在α7 nAChR 正向变构调节剂改造中的应用[J]. 中国药学(英文版), 2018, 27(7): 460-468.
[14]	刘芸奇, 李茜茜, 豆晓东, 田超, 张志丽, 刘俊义, 王孝伟. 相似的吡啶酮类化合物具有显著不同的抗HIV-1 逆转录酶活性[J]. 中国药学(英文版), 2018, 27(7): 469-477.
[15]	孔秋云, 杭楠, 张超, 李树春, 李中军, 孙洋, 孟祥豹. 作用于炎症小体的α,β-不饱和酮类化合物的合成及活性评价[J]. 中国药学(英文版), 2018, 27(5): 295-306.