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.
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。
Keywords: Methylene blue; Molecular docking; Photodynamic; Porphyromonas gingivalis; Target prediction.