Article(id=1309634547613004675, tenantId=1146029695717560320, journalId=1227999776411738115, issueId=1309634546845442540, articleNumber=null, orderNo=null, doi=10.12048/j.issn.1674-229X.2026.05.005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1769875200000, receivedDateStr=2026-02-01, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790170807984, onlineDateStr=2026-09-23, pubDate=1779638400000, pubDateStr=2026-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790170807984, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790170807984, creator=13701087609, updateTime=1790170807984, updator=13701087609, issue=Issue{id=1309634546845442540, tenantId=1146029695717560320, journalId=1227999776411738115, year='2026', volume='36', issue='5', pageStart='321', pageEnd='400', issueExtLink='null', onlineDate='null', pubDate='1779638400000', pubDateStr='2026-05-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790170807800, creator='13701087609', updateTime=1790218979984, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309836595717570703, tenantId=1146029695717560320, journalId=1227999776411738115, issueId=1309634546845442540, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309836595717570704, tenantId=1146029695717560320, journalId=1227999776411738115, issueId=1309634546845442540, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=348, endPage=354, ext={EN=ArticleExt(id=1309634547784971140, articleId=1309634547613004675, tenantId=1146029695717560320, journalId=1227999776411738115, language=EN, title=Screening of Anti-inflammatory Drug Candidates Targeting Nur77 and Molecular Dynamics Study, columnId=null, journalTitle=Pharmacy Today, columnName=null, runingTitle=null, highlight=null, articleAbstract=
OBJECTIVE

This study aimed to identify novel ligands targeting Site C of Nur77-LBD (ligand binding domain), a critical regulatory binding site of inflammation, using computational approaches.

METHODS

A structure-based virtual screening of 9 371 DrugBank compounds was conducted against the Nur77 ligand-binding domain (PDB ID:4JGV) using molecular docking. Top-scoring hits were subjected to 500-ns molecular dynamics (MD) simulations using Schrödinger Desmond module. Binding stability was assessed by root mean square deviation (RMSD), root mean square fluctuation (RMSF), Protein-ligand interaction analysis, and MM-GBSA calculations.

RESULTS

Five candidate compounds were identified to potentially bind to Nur77-LBD. Among them, compounds 1, 2, and 3 demonstrated stable binding, with low RMSD fluctuations and persistent protein-ligand interactions comparable to reference ligands 13 and 29.

CONCLUSION

These findings highlight compound 1 as the most promising candidate, showing comprehensive binding stability and interaction strength, and provide new chemical scaffolds for further optimization of Nur77 modulators.

, authors=Jianbiao LIa, Shangjie GUOb, Xian'en FAc, *, authorsList=Jianbiao LI, Shangjie GUO, Xian'en FA, authorCompany=null, correspAuthors=Xian'en FA, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1309634548204401541, articleId=1309634547613004675, tenantId=1146029695717560320, journalId=1227999776411738115, language=CN, title=靶向Nur77的抗炎候选药物筛选与分子动力学研究, columnId=1228268589086606089, journalTitle=今日药学, columnName=论著, runingTitle=null, highlight=null, articleAbstract=
目的

本研究旨在使用计算方法识别针对Nur77-LBD(配体结合结构域)位点C的新型配体,该位点是炎症的关键调节结合位点。

方法

基于Nur77配体结合结构域(PDB ID:4JGV)的结构,使用分子对接筛选9 371种DrugBank化合物。使用Schrödinger Desmond模块对得分最高的命中化合物进行500 ns分子动力学(MD)模拟。通过均方根偏差(RMSD)、均方根波动(RMSF)和蛋白质-配体相互作用分析以及MM-GBSA(分子力学/广义Born表面积法)计算评估结合稳定性。

结果

识别出5个候选化合物具有潜在结合Nur77-LBD的能力。其中,化合物1、2和3表现出稳定的结合,RMSD波动较低,蛋白质-配体相互作用持续且可相比参考配体13和29。

结论

化合物1作为最有希望的候选化合物,表现出全面的结合稳定性和相互作用强度,为进一步优化Nur77调节剂提供了新的化学骨架。

, authors=李健镖a, 郭尚捷b, 法宪恩c, *, authorsList=李健镖, 郭尚捷, 法宪恩, authorCompany=null, correspAuthors=法宪恩, authorNote=

李健镖,主治医师,研究方向:重症医学和计算机虚拟筛选研究

, correspAuthorsNote=

*

法宪恩,主任医师,研究方向:心血管疾病研究和计算机虚拟筛选研究,E-mail:
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李健镖,主治医师,研究方向:重症医学和计算机虚拟筛选研究

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靶向Nur77的抗炎候选药物筛选与分子动力学研究
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李健镖 a , 郭尚捷 b , 法宪恩 c, *
今日药学 | 论著 2026,36(5): 348-354
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今日药学 |论著 2026 , 36 (5) : 348 -354
靶向Nur77的抗炎候选药物筛选与分子动力学研究
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李健镖a, 郭尚捷b, 法宪恩c, *
作者信息
  • a.郑州大学第二附属医院,重症医学科,河南 郑州 450014
  • b.郑州大学第二附属医院,药学部,河南 郑州 450014
  • c.郑州大学第二附属医院,心血管外科,河南 郑州 450014
通讯作者:

*

法宪恩,主任医师,研究方向:心血管疾病研究和计算机虚拟筛选研究,E-mail:
作者简介:

李健镖,主治医师,研究方向:重症医学和计算机虚拟筛选研究

Screening of Anti-inflammatory Drug Candidates Targeting Nur77 and Molecular Dynamics Study
Jianbiao LIa, Shangjie GUOb, Xian'en FAc, *
Affiliations
  • a.Department of Critical Care Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450014, China
  • b.Department of Pharmacy, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450014, China
  • c.Department of Cardiovascular Surgery, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450014, China
出版时间: 2026-05-25 doi: 10.12048/j.issn.1674-229X.2026.05.005
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目的

本研究旨在使用计算方法识别针对Nur77-LBD(配体结合结构域)位点C的新型配体,该位点是炎症的关键调节结合位点。

方法

基于Nur77配体结合结构域(PDB ID:4JGV)的结构,使用分子对接筛选9 371种DrugBank化合物。使用Schrödinger Desmond模块对得分最高的命中化合物进行500 ns分子动力学(MD)模拟。通过均方根偏差(RMSD)、均方根波动(RMSF)和蛋白质-配体相互作用分析以及MM-GBSA(分子力学/广义Born表面积法)计算评估结合稳定性。

结果

识别出5个候选化合物具有潜在结合Nur77-LBD的能力。其中,化合物1、2和3表现出稳定的结合,RMSD波动较低,蛋白质-配体相互作用持续且可相比参考配体13和29。

结论

化合物1作为最有希望的候选化合物,表现出全面的结合稳定性和相互作用强度,为进一步优化Nur77调节剂提供了新的化学骨架。

Nur77(NR4A1)  /  孤儿核受体  /  虚拟筛选  /  分子动力学模拟
OBJECTIVE

This study aimed to identify novel ligands targeting Site C of Nur77-LBD (ligand binding domain), a critical regulatory binding site of inflammation, using computational approaches.

METHODS

A structure-based virtual screening of 9 371 DrugBank compounds was conducted against the Nur77 ligand-binding domain (PDB ID:4JGV) using molecular docking. Top-scoring hits were subjected to 500-ns molecular dynamics (MD) simulations using Schrödinger Desmond module. Binding stability was assessed by root mean square deviation (RMSD), root mean square fluctuation (RMSF), Protein-ligand interaction analysis, and MM-GBSA calculations.

RESULTS

Five candidate compounds were identified to potentially bind to Nur77-LBD. Among them, compounds 1, 2, and 3 demonstrated stable binding, with low RMSD fluctuations and persistent protein-ligand interactions comparable to reference ligands 13 and 29.

CONCLUSION

These findings highlight compound 1 as the most promising candidate, showing comprehensive binding stability and interaction strength, and provide new chemical scaffolds for further optimization of Nur77 modulators.

Nur77 (NR4A1)  /  orphan nuclear receptors  /  virtual screening  /  molecular dynamics simulations
李健镖, 郭尚捷, 法宪恩. 靶向Nur77的抗炎候选药物筛选与分子动力学研究. 今日药学, 2026 , 36 (5) : 348 -354 . DOI: 10.12048/j.issn.1674-229X.2026.05.005
Jianbiao LI, Shangjie GUO, Xian'en FA. Screening of Anti-inflammatory Drug Candidates Targeting Nur77 and Molecular Dynamics Study[J]. Pharmacy Today, 2026 , 36 (5) : 348 -354 . DOI: 10.12048/j.issn.1674-229X.2026.05.005
  • 河南省医学科技攻关计划项目(LHGJ20200400)
  • 河南省科技厅科技攻关项目(242102310472; 212102310315)
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文章信息
doi: 10.12048/j.issn.1674-229X.2026.05.005
  • 接收时间:2026-02-01
  • 首发时间:2026-09-23
  • 出版时间:2026-05-25
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出版历史
  • 收稿日期:2026-02-01
基金
河南省医学科技攻关计划项目(LHGJ20200400)
河南省科技厅科技攻关项目(242102310472; 212102310315)
作者信息
    a.郑州大学第二附属医院,重症医学科,河南 郑州 450014
    b.郑州大学第二附属医院,药学部,河南 郑州 450014
    c.郑州大学第二附属医院,心血管外科,河南 郑州 450014

通讯作者:

*

法宪恩,主任医师,研究方向:心血管疾病研究和计算机虚拟筛选研究,E-mail:
参考文献
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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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