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北京大学学报（医学版） ›› 2022, Vol. 54 ›› Issue (1): 23-30. doi: 10.19723/j.issn.1671-167X.2022.01.005

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计算机模拟亚甲基蓝与牙龈卟啉单胞菌部分蛋白的分子对接

袁临天1,2,马利沙2,刘润园3,齐伟1,2,张栌丹2,4,王贵燕2,5,王宇光2,△()   

  1. 1.北京大学口腔医学院·口腔医院 综合科,国家口腔疾病临床医学研究中心,口腔数字化医疗技术和材料国家工程实验室,口腔数字医学北京市重点实验室,北京 100081
    2.北京大学口腔医学院·口腔医院 口腔医学数字化研究中心,北京 100081
    3.大连医科大学口腔医学院牙体牙髓科,辽宁大连 116044
    4.北京大学口腔医学院·口腔医院门诊部,北京 100081
    5.北京大学口腔医学院·口腔医院 儿童口腔科,北京 100081
  • 收稿日期:2020-10-10 出版日期:2022-02-18 发布日期:2022-02-21
  • 通讯作者: 王宇光 E-mail:wangyuguang@bjmu.edu.cn
  • 基金资助:
    国家自然科学基金(51972003);国家重点研发计划(2018YFE0192500);首都特色临床研究(Z181100001718186);北大医学交叉研究种子基金-中央高校基本科研业务费(BMU2020MX013);北京大学医学部智慧医疗专项(BMU2019ZHYL003)

Computer simulation of molecular docking between methylene blue and some proteins of Porphyromonas gingivalis

YUAN Lin-tian1,2,MA Li-sha2,LIU Run-yuan3,QI wei1,2,ZHANG Lu-dan2,4,WANG Gui-yan2,5,WANG Yu-guang2,△()   

  1. 1. Department of General Medicine, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
    2. Center for Digital Dentistry, Peking University School and Hospital of Stomatology, Beijing 100081, China
    3. Department of Endodontics, College of Stomatology, Dalian Medical University, Dalian 116044, Liaoning, China
    4. First Clinical Division, Peking University School and Hospital of Stomatology, Beijing 100081, China
    5. Department of Pediatric Dentistry, Peking University School and Hospital of Stomatology, Beijing 100081, China
  • Received:2020-10-10 Online:2022-02-18 Published:2022-02-21
  • Contact: Yu-guang WANG E-mail:wangyuguang@bjmu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(51972003);National Key Research and Development Plan(2018YFE0192500);Capital Characteristic Clinical Research(Z181100001718186);Fundamental Research Funds for the Central Universities: Peking University Medicine Seed Fund for Interdisciplinary Research(BMU2020MX013);Smart Medical Project of Peking University Health Science Center(BMU2019ZHYL003)

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摘要：

目的: 使用计算机模拟的靶点预测与分子对接的方法,研究抗菌光动力疗法中光敏剂与细菌结合的靶点,并计算结合能。方法: 在Uniprot数据库和RCSB PDB数据库中获取并汇总牙龈卟啉单胞菌(Porphyromonas gingivalis,Pg)的蛋白名称;在SciFinder数据库、PubChem数据库、ChemSpider数据库和Chemical Book中筛选并对比亚甲基蓝的结构图,并用ChemBioDraw软件绘制确认;在PharmMapper数据库对亚甲基蓝三维结构进行靶点预测,并用Cytoscape 软件构建可视化网络图;在 String 数据库中构建亚甲基蓝靶点与Pg蛋白交集的相互作用网络;选择FimA、Mfa4、RgpB、Kgp K1蛋白,使用AutoDock软件计算亚甲基蓝与上述蛋白的对接能量,并进行分子对接。结果: 靶点预测结果显示,268个亚甲基蓝潜在靶点和1 865个Pg的蛋白之间有19个共同的靶点,这19个靶点为:groS、radA、rplA、dps、fabH、pyrG、thyA、panC、RHO、frdA、ileS、bioA、def、ddl、TPR、murA、lepB、cobT、gyrB。分子对接结果显示,亚甲基蓝能与FimA蛋白的9个位点结合,结合能-6.26 kcal/mol;与Mfa4蛋白的4个位点和氢键形成位点GLU47结合,结合能-5.91 kcal/mol;与RgpB蛋白的氢键形成位点LYS80结合,结合能-5.14 kcal/mol;与Kgp K1蛋白的6个位点和氢键形成位点GLY1114结合,结合能-5.07 kcal/mol。结论: 计算机模拟的靶点预测与分子对接技术可以初步揭示亚甲基蓝与Pg部分蛋白发生结合、结合程度及结合位点,为将来研究光敏剂与细胞、细菌结合位点的筛选提供参考。

关键词: 靶点预测, 分子对接, 光动力, 亚甲基蓝, 牙龈卟啉单胞菌

Abstract:

Objective: To study the binding target of photosensitizer and bacteria in antimicrobial photodynamic therapy with computer-simulated target prediction and molecular docking research methods and to calculate the binding energy. Methods: The protein names of Porphyromonas gingivalis (Pg) were obtained and summarized in Uniprot database and RCSB PDB database; the structure diagrams of methy-lene blue were screened in SciFinder database, PubChem database, ChemSpider database, and Chemical Book, and ChemBioDraw software was used to draw and confirm the three-dimensional structure for target prediction and Cytoscape software was used to build a visual network diagram; a protein interaction network was searched and built between the methylene blue target and the common target of Pg in the String database; then we selected FimA, Mfa4, RgpB, and Kgp K1 proteins, used AutoDock software to calculate the docking energy of methylene blue and the above-mentioned proteins and performed molecular docking. Results: The target prediction results showed that there were 19 common targets between the 268 potential targets of methylene blue and 1 865 Pg proteins. The 19 targets were: groS, radA, rplA, dps, fabH, pyrG, thyA, panC, RHO, frdA, ileS, bioA, def, ddl, TPR, murA, lepB, cobT, and gyrB. The results of the molecular docking showed that methylene blue could bind to 9 sites of FimA protein, with a binding energy of -6.26 kcal/mol; with 4 sites of Mfa4 protein and hydrogen bond formation site GLU47, and the binding energy of -5.91 kcal/mol, the binding energy of LYS80, the hydrogen bond forming site of RgpB protein, was -5.14 kcal/mol, and the binding energy of 6 sites of Kgp K1 protein and the hydrogen bond forming site GLY1114 of -5.07 kcal/mol. Conclusion: Computer simulation of target prediction and molecular docking technology can initially reveal the binding, degree of binding and binding sites of methylene blue and Pg proteins. This method provides a reference for future research on the screening of binding sites of photosensitizers to cells and bacteria.

Key words: Target prediction, Molecular docking, Photodynamic, Methylene blue, Porphyromonas gingivalis

中图分类号: 

  • R781.4

图1

药物成分-靶点可视化网络图"

图2

药物-细菌共同作用蛋白的PPI网络图"

图3

亚甲基蓝与靶蛋白FimA的分子对接模式图"

图4

亚甲基蓝与靶蛋白Mfa4蛋白的分子对接模式图"

图5

亚甲基蓝与RgpB蛋白的分子对接模式图"

图6

亚甲基蓝与Kgp K1蛋白的分子对接模式图"

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ISSN 1671-167X
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