Abstract：
Traditional Chinese medicines (TCMs) are popular in clinic because of their safety and efficacy. They contain abundant natural active compounds, which are important sources of new drug discovery. However, how to efficiently identify active compounds from complex ingredients remains a challenge. In this study, a method combining UHPLC-MS/MS characterization and in silico screening was developed to discover compounds with dopamine D2 receptor (D2R) activity in Stephania epigaea (S. epigaea). By combining the compounds identified in S. epigaea by UHPLC-MS/MS with reported compounds, a virtual library of 80 compounds was constructed for in silico screening. Potentially active compounds were chosen based on screening scores and subsequently tested for in vitro activity on a transfected cell line CHO-K1-D2 model using label-free cellular phenotypic assay. Three D2R agonists and five D2R antagonists were identified. (-)-Asimilobine, N-nornuciferine and (-)-roemerine were reported for the first time as D2R agonists, with EC50 values of 0.35 ± 0.04 μM, 1.37 ± 0.10 μM and 0.82 ± 0.22 μM, respectively. Their target specificity was validated by desensitization and antagonism assay. (-)-Isocorypalmine, (-)-tetrahydropalmatine, (-)-discretine, (+)-corydaline and (-)-roemeroline showed strong antagonistic activity on D2R with IC50 values of 92 ± 9.9 nM, 1.73 ± 0.13 μM, 0.34 ± 0.02 μM, 2.09 ± 0.22 μM and 0.85 ± 0.08 μM, respectively. Their kinetic binding profiles were characterized using co-stimulation assay and they were both D2R competitive antagonists. We docked these ligands with human D2R crystal structure and analyzed the structure-activity relationship of aporphine-type D2R agonists and protoberberine-type D2R antagonists. These results would help to elucidate the mechanism of action of S. epigaea for its analgesic and sedative efficacy and benefit for D2R drug design. This study demonstrated the potential of integrating UHPLC-MS/MS with in silico and in vitro screening for accelerating the discovery of active compounds from TCMs.
摘要：
中药由于其安全性和有效性而在临床上很受欢迎。它们含有丰富的天然活性化合物，这是新药发现的重要来源。然而,如何有效地从复杂的成分中识别活性化合物仍然是一个挑战。在这项研究中,开发了一种结合UHPLC-MS/MS表征和计算机筛选的方法，以发现在Stephaniaepigaea中具有多巴胺D2受体（D2R）活性的化合物（S.epigaea）。通过将通过UHPLC-MS/MS鉴定的S.epigaea中的化合物与已报告的化合物组合，构建了一个包含80种化合物的虚拟文库，用于计算机筛选。基于筛选评分选择潜在活性化合物,随后使用无标记细胞表型测定在转染细胞系CHO-K1-D2模型上测试体外活性。鉴定了三种D2R激动剂和五种D2R拮抗剂。(-)-阿西多辛,N-去甲氮素和(-)-罗梅林首次被报道为D2R激动剂，EC50值为0.35±0.04μM，1.37±0.10μM和0.82±0.22μM，分别。通过脱敏和拮抗试验验证了它们的靶特异性。(-)-异钴胺，(-)-四氢巴马汀,(-)-离散，(+)-紫藤碱和(-)-罗美罗碱对D2R显示出强拮抗活性,IC50值为92±9.9nM,1.73±0.13μM，0.34±0.02μM，2.09±0.22μM和0.85±0.08μM，分别。使用共刺激测定表征它们的动力学结合谱,并且它们都是D2R竞争性拮抗剂。我们将这些配体与人D2R的晶体结构对接，并分析了阿朴酚型D2R激动剂和原小檗碱型D2R拮抗剂的构效关系。这些结果将有助于阐明S.epigaea的镇痛和镇静功效以及对D2R药物设计的益处的作用机制。这项研究证明了将UHPLC-MS/MS与计算机和体外筛选相结合以加速从TCM中发现活性化合物的潜力。
