舞毒蛾谷胱甘肽S-转移酶的结构预测及其与杨树次生物质的分子对接分析

doi:10.12302/j.issn.1000-2006.202212012

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南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (5): 211-220.doi: 10.12302/j.issn.1000-2006.202212012

舞毒蛾谷胱甘肽S-转移酶的结构预测及其与杨树次生物质的分子对接分析

谢佳铭¹(), 曹传旺¹^,^*(), 孙丽丽¹, 李明俊², 张瑞琼¹

1.东北林业大学林学院,森林生态系统可持续经营教育部重点实验室,黑龙江哈尔滨 150040
2.内蒙古宁城县坤头河林场,内蒙古宁城 024228

收稿日期:2022-12-10 修回日期:2024-03-22 出版日期:2024-09-30 发布日期:2024-10-03
通讯作者: * 曹传旺(chuanwangcao@nefu.edu.cn),教授。
作者简介:
谢佳铭(1095334984@qq.com)。
基金资助:
国家自然科学基金项目(32071772);国家重点研发计划(2018YFC1200400)

Structural prediction of glutathione S-transferase (GST) in Lymantria dispar and its molecular docking analysis with poplar secondary metabolites

XIE Jiaming¹(), CAO Chuanwang¹^,^*(), SUN Lili¹, LI Mingjun², ZHANG Ruiqiong¹

1. Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin 150040, China
2. Ningcheng County Kuntouhe Forest Farm of Inner Mongolia, Ningcheng 024228, China

Received:2022-12-10 Revised:2024-03-22 Online:2024-09-30 Published:2024-10-03

摘要/Abstract

摘要：

【目的】明确舞毒蛾(Lymantria dispar)谷胱甘肽S-转移酶(glutathione S-transferase, GST)与杨树主要次生物质的结合能力和结合方式,为解析GST介导的舞毒蛾对杨树次生物质适应性机制提供理论基础,并通过GST分子模拟筛选结合能力强的次生物质,为舞毒蛾的科学防治提供新的策略。【方法】基于Swiss-model算法,经序列多重比对后,以氨基酸序列一致性大于30%的GST蛋白作为建模模板,对10条舞毒蛾GST蛋白进行同源建模,成功构建其三维结构。随后,利用SAVES软件对已构建的GST蛋白三维结构进行评估。从Pubchem网站获得6种杨树次生物质的3D结构并运用Discovery Studio 2019软件对10种GST模型和6种杨树次生物质进行分子对接,通过结合能和可视化分析其对接情况。【结果】10种舞毒蛾GST蛋白同源建模所得模型均满足拉氏构象图中氨基酸位于最佳合理区和允许区域的数量大于90%的条件;三维结构与一级结构的兼容性评分大于0.2的氨基酸数量大于80%;所得ERRAT值为91.73%~97.82%,可知10种GST模型评估合格。分子对接结果表明,GST与杨树次生物质分子间均含有氢键及共价键。其中:与水杨苷结合最优蛋白为LdGSTs2,结合能为-45.70 kJ/mol;与咖啡酸结合最优蛋白为LdGSTz2,结合能为-43.96 kJ/mol;与邻苯二酚和芦丁结合最优蛋白为LdGSTz1,结合能分别为-25.86和-95.46 kJ/mol;与黄酮结合最优蛋白为LdGSTe2,结合能为-32.49 kJ/mol;与槲皮素结合最优蛋白为LdGSTo2,结合能为-62.09 kJ/mol。【结论】舞毒蛾GST与杨树次生物质结合能均≤-5 kJ/mol均含有氢键和共价键,同种杨树次生物质与不同GSTs的结合能相似,表明舞毒蛾GST与杨树次生物质之间具有较好的亲和力并且分子间结合稳定;GST对次生物质特异性不高,但同种GST与不同的杨树次生物质的亲和力强弱存在差异。研究结果可为添加次生物质以降低杀虫剂抗药性提供理论依据。

关键词: 舞毒蛾, 谷胱甘肽S-转移酶, 杨树次生物质, 同源建模, 分子对接, 结合能

Abstract:

【Objective】This study aims to determine the binding ability and mode of glutathione S-transferase (GST) in Lymantria dispar to key poplar secondary metabolites, provide a foundational theory for the adaptation mechanism of LdGST to these metabolites. Additionally, The GST molecular simulation was used to identify the best binding secondary metabolites, offering a novel strategy for controlling Lymantria dispar.【Method】Homology modeling, multiple sequence alignment, and three-dimensional structure determination of 10 GSTs were performed using templates with over 30% similarity via the Swiss-model website. The 10 GST models were evaluated using SAVES software. The 3D structures of six poplar secondary metabolites were obtained from the PubChem website. Molecular docking of the 10 GST models with the six poplar secondary metabolites was conducted using Discovery Studio 2019 Client software, and docking results analyzed through combined energy and visualization.【Result】 The models obtained through homology modeling of the 10 GSTs met the criteria, with more than 90% of amino acids in the Ramachandran Plot’s most favored and additional allowed regions. The percentage of amino acids with a compatibility score above 0.2 between the three-dimensional and primary structures was over 80%, and the ERRAT value ranged from 91.73% to 97.82%, indicating the models were qualified. Molecular docking revealed that the binding of GST to poplar secondary metabolites involved hydrogen and covalent bonds. The optimal protein bindings were as follows: Salicin, LdGSTs2 with a binding energy of -45.70 kJ/mol. Caffeic acid, LdGSTz2 with a binding energy of -43.96 kJ/mol. Catechol and rutin, LdGSTz1 with binding energies of -25.86 and -95.46 kJ/mol, respectively. Flavonoids, LdGSTe2 with a binding energy of -32.49 kJ/mol. Quercetin, LdGSTo2 with a binding energy of -62.09 kJ/mol.【Conclusion】The binding energy of LdGSTs to poplar secondary metabolites are all below -5 kJ/mol, involving hydrogen and covalent bonds. The similar binding energy of the same poplar secondary metabolites to different GSTs suggests good affinity and stable intermolecular binding, with low specificity of GST for secondary metabolites. However, the affinity of the same GST to different poplar secondary metabolites varied. These results provide a theoretical basis for reducing insecticide resistance by incorporating secondary metabolites.

Key words: Lymantria dispar, glutathione S-transferase(GST), poplar secondary metabolites, homology modeling, molecular docking, binding energy

中图分类号:

S763
Q89

谢佳铭,曹传旺,孙丽丽,等. 舞毒蛾谷胱甘肽S-转移酶的结构预测及其与杨树次生物质的分子对接分析[J]. 南京林业大学学报（自然科学版）, 2024, 48(5): 211-220.

XIE Jiaming, CAO Chuanwang, SUN Lili, LI Mingjun, ZHANG Ruiqiong. Structural prediction of glutathione S-transferase (GST) in Lymantria dispar and its molecular docking analysis with poplar secondary metabolites[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(5): 211-220.DOI: 10.12302/j.issn.1000-2006.202212012.

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谷胱甘肽 S-转移酶 glutathione S-transferase	最佳影响区域中占比 percentage in best affected area	额外允许区域中占比 percentage in additional allowed area	宽松允许区域中占比 percentage in loose allowable area
LdGSTe1	91.6	6.5	0.8
LdGSTe2	91.1	7.3	1.0
LdGSTe3	92.4	6.0	0.8
LdGSTo1	92.6	6.4	1.0
LdGSTo2	93.8	5.8	0
LdGSTs1	91.1	6.9	1.7
LdGSTs2	91.9	6.7	1.4
LdGSTt1	90.2	8.0	0
LdGSTz1	94.8	4.7	0.5
LdGSTz2	92.5	7.0	0.5

谷胱甘肽 S-转移酶 glutathione S-transferase	水杨苷 salicin	咖啡酸 caffeic acid	邻苯二酚 catechol	黄酮 flavone	芦丁 rutin	槲皮素 quercetin
LdGSTe1	-39.53	-36.13	-18.17	-24.19	-47.60	-53.74
LdGSTe2	-37.78	-23.14	-20.15	-32.49	-56.45	-54.02
LdGSTe3	-32.07	-37.71	-15.95	-23.26	-41.28	-48.60
LdGSTo1	-42.00	-39.03	-21.61	-26.48	-76.46	-58.19
LdGSTo2	-24.55	-26.55	-12.67	-17.89	-43.55	-62.09
LdGSTs1	-41.14	-28.34	-19.39	-26.02	-68.58	-47.96
LdGSTs2	-45.70	-40.30	-21.08	-29.44	-73.24	-60.05
LdGSTt1	-32.25	-30.39	-20.50	-25.02	-61.55	-43.28
LdGSTz1	-43.50	-39.21	-25.85	-27.22	-95.46	-49.54
LdGSTz2	-43.48	-43.96	-18.48	-30.92	-82.14	-37.88

舞毒蛾谷胱甘肽S-转移酶的结构预测及其与杨树次生物质的分子对接分析

Structural prediction of glutathione S-transferase (GST) in Lymantria dispar and its molecular docking analysis with poplar secondary metabolites

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