人工智能驱动的补骨脂果实治疗骨质疏松症的协同组合的发现
AI-driven discovery of synergistic combinations from Psoralea corylifolia fruit for treating osteoporosis.
摘要(中文译文)
雌激素缺乏性骨质疏松需要安全有效的治疗药物。补骨脂果实（PCF）是一种用于骨质疏松的植物雌激素类中药，但其关键活性成分及协同组合尚不明确，限制了其应用。本研究建立了一种人工智能驱动的分步策略，从PCF中筛选抗骨质疏松协同组合，量化其协同作用，并验证药效学，从而为复杂疾病的治疗提供参考。本研究提出了一种人工智能驱动的分步整合策略：Ⅰ）通过雌激素/抗骨质疏松双重模型，利用人工智能辅助初步筛选PCF活性成分；Ⅱ）采用分子模拟（分子对接/分子动力学）对候选成分进行二次筛选；Ⅲ）通过多维评价精准锁定先导成分；Ⅳ）采用Chou-Talalay法判定协同作用（组合指数，CI<0.9）、相加作用（0.9≤CI≤1.1）或拮抗作用（CI>1.1）。最终，通过系统的体外和体内药效学评价，并结合基于90%置信区间的生物等效性分析，对筛选出的协同组合进行药效学活性验证。机器学习（ML）筛选鉴定出20种活性成分，经分子模拟缩小至6种。最终确定三种先导成分，即新补骨脂异黄酮（NBIF）、补骨脂二氢黄酮（BA）和异补骨脂查尔酮（IB）。NBIF+BA协同组合具有显著协同作用（CI<0.9），其疗效优于各单一成分，且与PCF提取物等效（90%置信区间：78.12%-132.15%）。该人工智能驱动策略成功从PCF中鉴定出具有强效抗骨质疏松作用的NBIF+BA协同组合，为复杂疾病的治疗提供了一种有前景的方法。
Abstract
Estrogen-deficient osteoporosis demands safe and effective therapies. Psoralea corylifolia fruit (PCF), a phytoestrogenic herbal medicine for osteoporosis, lacks clarified key active components and synergistic combinations, which limits its application. This study established an AI-driven stepwise strategy to identify anti-osteoporotic synergistic combination from PCF, quantify their synergism, and validate pharmacodynamics, thus providing a reference for complex disease treatment. An AI-driven stepwise integrated strategy was proposed: Ⅰ) Artificial intelligence-assisted preliminary screening of PCF active components via dual estrogenic/anti-osteoporotic models; Ⅱ) molecular simulation (docking/dynamics) for secondary screening of candidate components; Ⅲ) multi-dimensional evaluation for precision targeting of lead components; Ⅳ) Chou-Talalay method used to determine synergism (combination index, CI<0.9), additivity (0.9≤CI≤1.1), or antagonism (CI>1.1). Ultimately, the pharmacodynamic activity of the screened synergistic combination was validated through systematic in vitro and in vivo pharmacodynamic evaluations, combined bioequivalence analysis based on 90% confidence interval. Machine learning (ML) screening identified 20 active components, narrowed to 6 via molecular simulations. Three leads viz neobavaisoflavone (NBIF), bavachin (BA) and isobavachalcone (IB) were finalized. The NBIF+BA synergistic combination with significant synergism (CI<0.9) showed superior efficacy to individual components, and equivalence to PCF extract (90% confidence interval: 78.12%-132.15%). This AI-driven strategy successfully identified a synergistic combination of NBIF+BA with potent anti-osteoporotic effects from PCF, presenting a promising approach for the treatment of complex diseases.
如何引用
AMA
Chun-Lu Liu, Ming-Rui Li, Jing Long, Si-Tong Qian, Cai Zhang, Ping Li, et al. AI-driven discovery of synergistic combinations from Psoralea corylifolia fruit for treating osteoporosis.. Phytomedicine : international journal of phytotherapy and phytopharmacology. 2026; doi:10.1016/j.phymed.2026.158427.
APA
Chun-Lu Liu, Ming-Rui Li, Jing Long, Si-Tong Qian, Cai Zhang, Ping Li, et al (2026). AI-driven discovery of synergistic combinations from Psoralea corylifolia fruit for treating osteoporosis.. Phytomedicine : international journal of phytotherapy and phytopharmacology. https://doi.org/10.1016/j.phymed.2026.158427
GB/T 7714
Chun-Lu Liu, Ming-Rui Li, Jing Long, Si-Tong Qian, Cai Zhang, Ping Li, et al. AI-driven discovery of synergistic combinations from Psoralea corylifolia fruit for treating osteoporosis.[J]. Phytomedicine : international journal of phytotherapy and phytopharmacology, 2026 doi:10.1016/j.phymed.2026.158427.
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