Jiangsu Key Lab of Drug Screening, China Pharmaceutical University, Nanjing, China.
Stroke Vasc Neurol. 2019 Nov 7;4(4):206-213. doi: 10.1136/svn-2019-000290. eCollection 2019 Dec.
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database including detailed information of approved, investigational and withdrawn drugs, as well as other nutraceutical and metabolite structures. PubChem is a chemical compound database including all commercially available compounds as well as other synthesisable compounds. Protein Data Bank is a crystal structure database including X-ray, cryo-EM and nuclear magnetic resonance protein three-dimensional structures as well as their ligands. On the other hand, artificial intelligence (AI) is playing an important role in the drug discovery progress. The integration of such big data and AI is making a great difference in the discovery of novel targeted drug. In this review, we focus on the currently available advanced methods for the discovery of highly effective lead compounds with great absorption, distribution, metabolism, excretion and toxicity properties.
如今,不同类型的生物数据库为我们提供了一个多学科大数据的金矿。癌症基因组图谱是一个癌症数据库,包含许多癌症患者的详细信息。DrugBank 是一个包含已批准、正在研究和已撤回药物以及其他营养药物和代谢物结构详细信息的数据库。PubChem 是一个化学化合物数据库,包含所有市售化合物以及其他可合成化合物。蛋白质数据库是一个晶体结构数据库,包含 X 射线、冷冻电镜和核磁共振蛋白质三维结构及其配体。另一方面,人工智能(AI)在药物发现进展中发挥着重要作用。这种大数据和人工智能的融合在新型靶向药物的发现中产生了巨大的影响。在这篇综述中,我们专注于目前可用于发现具有高吸收、分布、代谢、排泄和毒性特性的高效先导化合物的先进方法。