鹅不食草中抗炎活性成分的虚拟筛选

Virtual Screening of Anti-Inflammatory Active Ingredients in Herba centipedae

摘要: 通过文献研究发现鹅不食草具有明显的抗炎活性，但其药效物质基础和作用机制尚不清楚。因此利用分子对接技术对鹅不食草中具有抗炎作用的化学成分进行虚拟筛选。在TCMSP数据库中筛选出鹅不食草的化学成分组成配体数据库，选择4个与抗炎活性密切相关的蛋白靶点组成受体数据库，用SYBYL软件进行分子对接。通过对接打分函数(Total Score ≥ 5)筛选出6个活性成分，并分析了蛋白复合体的相互作用。本研究初步筛选了鹅不食草抗炎的活性成分和关键靶点，为鹅不食草的进一步研究提供了参考。

Abstract: Through literature research, it was found that Herba centipedae has obvious anti-inflammatory activity, but its pharmacodynamic substance basis and mechanism of action are unclear. There-fore, the molecular docking technology was used to screen the chemical components in Herba centipedae with anti-inflammatory effects. In the TCMSP database, the chemical composition of Herba centipedae was selected to form a ligand database, 4 protein targets closely related to an-ti-inflammatory activity were selected to form a receptor database, and molecular docking was performed with SYBYL software. Six active ingredients were screened by the docking scoring function (Total Score ≥ 5), and the interaction of protein complexes was analyzed. In this study, the anti-inflammatory active ingredients and key targets of Herba centipedae were preliminarily screened, which provided a reference for its further research.