随着人口老龄化速度加快，骨质疏松已成为全球关注的健康与社会问题，开发有效的抗骨质疏松药物成为新药开发的重要方向。研究表明OPG/RANKL/RANK信号轴是骨代谢中重要的信号通路。因此，RANKL-NFκB通路是抗骨质疏松药物的重要靶点。天然产物因其结构多样和丰富的生物活性成为药物发现的重要来源，而目前抗骨质疏松的活性天然产物主要是通过随机筛选发现的，具有一定的随机性与盲目性。前期研究中，申请人团队已发现一系列抗骨质疏松活性天然产物，并建立了基于机器学习及基于活性骨架的筛选系统。本项目将在前期研究基础上，利用建立的计算机辅助药物筛选技术，对天然产物数据库展开系统理性的虚拟筛选，结合成熟的抗骨质疏松活性筛选平台，发现结构新颖的活性天然产物，为开发新型抗骨质疏松药物提供物质基础。同时结合生物实验与计算模拟方法，阐释活性化合物与关键蛋白的作用机制，为设计抗骨质疏松活性化合物提供思路和理论依据。

Osteoporosis has become a worldwide health and social issue due to an aging population. Development of new anti-osteoporosis drugs has become the objective of drug development. Powerful evidences of bone biology has approved that RANKL/RANK/OPG axis plays pivotal roles in regulating diverse physiological processes such as osteoclast formation and function. Thus, RANKL-NFκB pathway is ideal targets for anti-osteoporosis drug development. Owning to the structural diversity and multiple pharmacological activities, natural products are one of the most important sources of the lead compounds in drug discovery. However, the bioactive natural products targeting RANKL-NFκB pathway were randomly discovered currently. Owning to the chemical diversity of natural products, there is still a great opportunity for the discovery of bioactive natural products. In our previous studies, our group have identified a serials of bioactive anti-osteoporosis natural products. Meanwhile, we have developed the machine learning based and scaffold based virtual screening system. In this study, we will apply the previous developed virtual screening methods, and combine the mature anti-osteoporosis bioassay platform to screen the novel anti-osteoporosis natural products. This would be significant for providing material base for anti-osteoporosis drug development. Meanwhile, combining the experiment and the theoretical computation methods to elucidate the mechanism of action of the bioactive natural products with the key protein in the pathway. This would provide more insights for the further design of anti-osteoporosis drug.