中华中医药学刊

基于三维定量构效关系、分子对接与实验验证对细辛中抗气道炎症成分的虚拟筛选

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李佳颖 ¹^,² , 黄慧学 ¹ , 李君 ³ , 邓芳 ¹^,² , 窦潞娜 ¹ , 梁晓 ¹^,²

中华中医药学刊 | 国家项目点击 2026,44(9): 160-166

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中华中医药学刊 |国家项目点击 2026 , 44 (9) : 160 -166

基于三维定量构效关系、分子对接与实验验证对细辛中抗气道炎症成分的虚拟筛选

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李佳颖¹^,², 黄慧学¹, 李君³, 邓芳¹^,², 窦潞娜¹, 梁晓¹^,²

作者信息

^1.桂林医科大学药学院，广西　桂林　541199

^2.广西药物分子发现与成药性优化重点实验室，广西　桂林　541199

^3.长沙医学院药学院，湖南　长沙　410219

通讯作者:

梁晓（1981-），男，河南南阳人，讲师，博士，研究方向：中医经典名方物质基础与方剂配伍。E-mail：liangxiao5680@163.com。

作者简介:

李佳颖（1997-），女，广西桂林人，硕士在读，研究方向：中药方剂物质基础与配伍。

Virtual Screening of Anti-Airway Inflammatory Components in Xixin (Asari Radix et Rhizoma) Based on 3D-QSAR, Molecular Docking and Experimental Validation

Jiaying LI¹^,², Huixue HUANG¹, Jun LI³, Fang DENG¹^,², Luna DOU¹, Xiao LIANG¹^,²

Affiliations

^1.Guilin Medical University, Guilin 541199, Guangxi, China

^2.Guangxi Key Laboratory of Drug Discovery and Optimization, Guilin 541199, Guangxi, China

^3.Changsha Medical University, Changsha 410219, Hunan, China

出版时间: 2026-09-10 doi: 10.13193/j.issn.1673-7717.2026.09.030

文章导航

摘要

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目的

基于三维定量构效关系（three-dimensional quantitative structure-activity relationships，3D-QSAR）、分子对接和细胞实验，研究细辛中潜在抑制核转录因子κB（nuclear factor-kappaB，NF-κB）的抗炎活性成分。

方法

使用Discovery Studio软件构建基于NF-κB的最佳3D-QSAR模型，虚拟筛选细辛中潜在活性成分，并预测其药动学性质；随后采用AutoDock Vina软件进行分子对接评判潜在活性成分与NF-κB通路靶点的结合能力；建立BEAS-2B细胞模型，采用体外酶联免疫吸附试验验证所选活性成分的抗炎效果。

结果

3D-QSAR模型与ADMET预测共筛选出细辛中细辛脂素、芝麻脂素等5种活性成分；分子对接结果显示所得活性成分与NF-κB蛋白均具有较好的亲和力。体外细胞实验表明所选成分细辛脂素、芝麻脂素具有显著抗炎效果。

结论

基于3D-QSAR模型、分子对接和体外实验技术可有效挖掘细辛中NF-κB抑制成分，揭示其药效物质基础。

关键词

3D-QSAR / 分子对接 / 细辛 / 核转录因子κB / 支气管哮喘

Abstract

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Objective

To identify the potential anti-inflammatory active components in Xixin (Asari Radix et Rhizoma) that inhibit nuclear factor-kappa B (NF-κB) using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and cell experiments.

Method

Discovery Studio software was employed to construct an optimal 3D-QSAR model based on NF-κB for virtual screening of potential active ingredients in Xixin (Asari Radix et Rhizoma) and to predict their pharmacokinetic (ADMET) properties. Subsequently, AutoDock Vina software was utilized for molecular docking to evaluate the binding affinity of the potential active ingredients with NF-κB pathway targets. A BEAS-2B cell model was established, and in vitro enzyme-linked immunosorbent assay (ELISA) was performed to verify the anti-inflammatory effects of the selected components.

Results

The 3D-QSAR model and ADMET prediction collectively identified five active compounds, including asarinin and sesamin from Xixin (Asari Radix et Rhizoma). Molecular docking results demonstrated that these active compounds exhibited good binding affinity with the NF-κB protein. In vitro cell experiments confirmed that asarinin and sesamin possessed significant anti-inflammatory effects.

Conclusion

The integration of 3D-QSAR modeling, molecular docking and in vitro experimental techniques effectively facilitates the discovery of NF-κB inhibitory components in Xixin (Asari Radix et Rhizoma) and elucidates their pharmacodynamic material basis.

Key words

3D-QSAR / molecular docking / Xixin (Asari Radix et Rhizoma) / nuclear factor-kappa B / bronchial asthma

引用本文

李佳颖, 黄慧学, 李君, 邓芳, 窦潞娜, 梁晓. 基于三维定量构效关系、分子对接与实验验证对细辛中抗气道炎症成分的虚拟筛选. 中华中医药学刊, 2026 , 44 (9) : 160 -166 . DOI: 10.13193/j.issn.1673-7717.2026.09.030

Jiaying LI, Huixue HUANG, Jun LI, Fang DENG, Luna DOU, Xiao LIANG. Virtual Screening of Anti-Airway Inflammatory Components in Xixin (Asari Radix et Rhizoma) Based on 3D-QSAR, Molecular Docking and Experimental Validation[J]. Chinese Archives of Traditional Chinese Medicine, 2026 , 44 (9) : 160 -166 . DOI: 10.13193/j.issn.1673-7717.2026.09.030

基金

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国家自然科学基金项目(82160778)
广西高校中青年教师科研基础能力提升项目(2021KYO513)

参考文献

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2026年第44卷第9期

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文章信息

doi: 10.13193/j.issn.1673-7717.2026.09.030

首发时间：2026-10-20
出版时间：2026-09-10

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基金

国家自然科学基金项目(82160778)

广西高校中青年教师科研基础能力提升项目(2021KYO513)

作者信息

^1.桂林医科大学药学院，广西　桂林　541199

^2.广西药物分子发现与成药性优化重点实验室，广西　桂林　541199

^3.长沙医学院药学院，湖南　长沙　410219

通讯作者:

梁晓（1981-），男，河南南阳人，讲师，博士，研究方向：中医经典名方物质基础与方剂配伍。E-mail：liangxiao5680@163.com。

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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