虚拟筛选
对接(动物)
计算生物学
子宫内膜异位症
芳香烃受体
化学
生物活性
生物信息学
药理学
医学
分子描述符
受体
生物信息学
立体化学
数量结构-活动关系
棋盘
作者
Sutrisno Sutrisno,Maharani Maharani
出处
期刊:
日期:2026-05-01
卷期号:14 (3): 2658-2658
标识
DOI:10.56499/jppres_14.3.2658
摘要
Context: Endometriosis is a chronic estrogen-dependent inflammatory disorder associated with pelvic pain and infertility. Flavonoids from Phaleria macrocarpa have been reported to exhibit anti-inflammatory activity; however, their molecular mechanisms relevant to endometriosis remain insufficiently characterized. Aims: To predict biological activities of selected P. macrocarpa flavonoids and to explore potential protein–ligand interactions with endometriosis-relevant targets using molecular docking. Methods: Six flavonoids (eriodictyol, glycitin, 5-O-methylgenistein, catechin 7-O-β-D-xyloside, 8-prenylnaringenin, and naringenin) were assessed using the PASS web server to estimate biological activity probabilities (Pa/Pi). The compound with the highest predicted anti-inflammatory probability (Pa > 0.7) was selected for docking against cyclooxygenase-2 (COX-2), estrogen receptor (ER), AKT, aryl hydrocarbon receptor (AHR), and caspase-3 using Molegro Virtual Docker. Docking protocol validation was performed by redocking co-crystallized ligands and evaluating RMSDs. Results: PASS prediction indicated that all compounds exhibited potential anti-inflammatory activity (Pa > Pi), with 5-O-methylgenistein showing the highest confidence prediction (Pa = 0.838). Docking analysis suggested that 5-O-methylgenistein can occupy the binding sites of COX-2, ER, AKT, and AHR, showing comparable interaction patterns and overlapping residues with those of reference ligands, as indicated by software-derived scores. Redocking validation confirmed the acceptable reproduction of the pose (RMSD ≤ 2.0 Å). Conclusions: 5-O-methylgenistein was identified as a promising candidate for further investigation. The predicted interactions support hypotheses related to inflammation- and hormone-associated pathways in endometriosis; however, these findings are based on computational models and require experimental validation to confirm biological activity and therapeutic relevance.
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