整合网络毒理学、分子对接与分子动力学模拟探究低氯代二苯并二噁英致抑郁症的机制

Integrating network toxicology， molecular docking， and molecular dynamics simulation to explore the mechanisms underlying depression induced by low-chlorinated polychlorinated dibenzo-p-dioxins

中文关键词:  网络毒理学  分子对接  分子动力学模拟  抑郁症  多氯代二苯并二噁英  低氯代二苯并二噁英

英文关键词:Network toxicology  Molecular docking  Molecular dynamics simulation  Depression  Polychlorinated dibenzo-p-dioxins  Low-chlorinated polychlorinated dibenzo-p-dioxins

中文摘要:

      背景 多氯代二苯并二噁英（PCDDs）为一类全球性环境污染物，多项研究提示其具有神经毒性，但现有研究多集中于2，3，7，8-四氯二苯并二噁英（2，3，7，8-TCDD），低氯代二苯并二噁英（LC-PCDDs）作为PCDDs家族中氯取代数较低的同族体，其是否会诱发抑郁症及其致病的分子机制尚不明确。目的 明确LC-PCDDs诱发抑郁症的相关分子机制，为环境精神毒理风险评估提供参考。方法 ①网络毒理学：以4种化合物［（2-单氯代二苯并二噁英（2-MCDD）、二氯代二苯并二噁英（DCDD）、1，2，4-三氯代二苯并二噁英（1，2，4-TrCDD）、2，3，7-TrCDD）］为研究对象，通过公共数据库预测其毒性，并分别获取LC-PCDDs与抑郁症的相关靶基因，利用STRING数据库对二者的交集靶基因构建蛋白质互作（PPI）网络，借助CytoNCA插件对PPI网络进行拓扑分析，筛选核心靶点。最后通过DAVID数据库将核心靶点进行基因本体（GO）分析及京都基因与基因组百科全书（KEGG）通路富集分析。②分子对接：采用AutoDock Tools 1.5.7模拟分子对接，并借助PyMOL（TM）3.1.6.1对对接所得的复合物构象及相互作用界面进行可视化展示。③分子动力学模拟：使用GROMACS 2025对最优对接复合物进行100 ns分子动力学模拟。蛋白质采用AMBER99SB-ILDN力场，配体采用GAFF2力场构建拓扑，并将二者合并为复合物体系。以TIP3P水模型溶剂化，添加0.15 mol/L Na?/Cl?构建生理离子环境，经能量最小化及2 ns等容等温系综平衡和等温等压系综平衡后，进行100 ns全原分子动力学模拟（310 K、1 bar）。结果 ①网络毒理学分析筛选出10个核心靶点，分别为ESR1、HSP90AA1、PPARG、EGFR、MAPK1、MAPK14、AR、PGR、CDK2、TGFBR1，上述核心靶点富集于多条关键信号通路。②分子对接结果显示，4种化合物与核心靶点均有较强的结合亲和力，其中2-MCDD与PPARG的结合亲和力最强（ΔG=-8.836 kcal/mol）。③分子动力学模拟结果显示，2-MCDD与PPARG形成的配体-受体复合物在100 ns模拟过程中结合构象保持稳定。结论 LC-PCDDs可能是诱发抑郁症的重要环境风险因子，其可介导“代谢-氧化损伤-凋亡”多维调控网络参与抑郁症的发病过程。

英文摘要:

      Background Polychlorinated dibenzo-p-dioxins （PCDDs） is a type of global environmental pollutants， have been shown in numerous studies to exert neurotoxic effects. Nevertheless， existing research has predominantly focused on 2，3，7，8-tetrachlorodibenzo-p-dioxin （2，3，7，8-TCDD）. Whether low-chlorinated PCDDs （LC-PCDDs）， a subclass with fewer chlorine substitutions， can induce depression as well as the corresponding molecular mechanisms remains unclear.Objective To elucidate molecular mechanisms underlying depression induced by LC-PCDDs， so as to provide evidence for environmental neuro-psychotoxicological risk assessment.Methods ①Network toxicology. Four compounds， namely 2-monochlorodibenzo-p-dioxin （2-MCDD）， dichlorodibenzo-p-dioxin （DCDD）， 1，2，4-trichlorodibenzo-p-dioxin （1，2，4-TrCDD）， and 2，3，7-TrCDD， were selected as research subjects. Their toxic profiles were predicted using public databases， and target genes associated with LC-PCDDs and depression were retrieved. The overlapping targets were imported into the STRING database to construct a protein-protein interaction （PPI） network. Topological analysis was subsequently performed via the CytoNCA plugin in Cytoscape to identify hub targets. Finally， Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses for these hub targets were completed in DAVID. ②Molecular docking. Docking simulations were conducted using AutoDock Tools 1.5.7， and the binding poses and interaction profiles of the resultant protein-ligand complexes were visualized using PyMOL （TM） 3.1.6.1. ③Molecular dynamics simulation. A 100-ns production simulation for the top-ranked docked complex was carried out using GROMACS 2025. The protein was parameterized with the AMBER99SB-ILDN force field， the ligand topologies were generated using GAFF2， and the two were then merged to construct the protein-ligand complex system. The complex was solvated in TIP3P water， and the system was adjusted to physiological ionic strength by adding 0.15 mol/L Na?/Cl?. Following energy minimization and sequential 2-ns equilibrations in canonical and isothermal-isobaric ensembles， a 100-ns production run was executed at 310 K and 1 bar.Results ①Network toxicology analysis identified 10 hub targets （ESR1， HSP90AA1， PPARG， EGFR， MAPK1， MAPK14， AR， PGR， CDK2， and TGFBR1）， which were enriched in multiple critical signaling pathways. ②Molecular docking revealed that all four compounds exhibited strong binding affinities for hub targets， with 2-MCDD showing the highest binding affinity for PPARG （ΔG=-8.836 kcal/mol）. ③Molecular dynamics simulations demonstrated that the ligand-receptor complex formed by 2-MCDD and PPARG maintained a stable binding conformation throughout the 100-ns simulation.Conclusion LC-PCDDs may serve as significant environmental risk factors for depression， participating in its pathogenesis by mediating a multidimensional regulatory network involving metabolism， oxidative damage and apoptosis. ［Funded by Hubei Province Traditional Chinese Medicine Clinical Excellent Talents Project］.