Schneider P, Schneider G
Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Vladimir-Prelog-Weg 4, CH-8093, Zurich, Switzerland.
Chem Commun (Camb). 2017 Feb 14;53(14):2272-2274. doi: 10.1039/c6cc09693j.
Exploring the full potential of bioactive natural products and phenotypic screening hits for drug discovery and design requires profound understanding of the macromolecular targets involved. We present a computational method for target prediction, and showcase its practical applicability, taking the marine anticancer compound (±)-marinopyrrole A as an example. With an overall accuracy of 67%, the ligand-based method employed identified the natural product as a potent glucocorticoid, cholecystokinin, and orexin receptor antagonist. The results of this study demonstrate the utility of fast computational target assessment for medicinal chemistry and chemical biology.
探索生物活性天然产物和表型筛选命中物在药物发现与设计方面的全部潜力，需要深入了解所涉及的大分子靶点。我们提出了一种用于靶点预测的计算方法，并以海洋抗癌化合物（±）-marinopyrrole A为例展示了其实际适用性。所采用的基于配体的方法总体准确率为67%，该方法将这种天然产物鉴定为一种有效的糖皮质激素、胆囊收缩素和食欲素受体拮抗剂。本研究结果证明了快速计算靶点评估在药物化学和化学生物学中的实用性。
