College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China.
Nucleic Acids Res. 2023 Jan 6;51(D1):D1288-D1299. doi: 10.1093/nar/gkac813.
The efficacy and safety of drugs are widely known to be determined by their interactions with multiple molecules of pharmacological importance, and it is therefore essential to systematically depict the molecular atlas and pharma-information of studied drugs. However, our understanding of such information is neither comprehensive nor precise, which necessitates the construction of a new database providing a network containing a large number of drugs and their interacting molecules. Here, a new database describing the molecular atlas and pharma-information of drugs (DrugMAP) was therefore constructed. It provides a comprehensive list of interacting molecules for >30 000 drugs/drug candidates, gives the differential expression patterns for >5000 interacting molecules among different disease sites, ADME (absorption, distribution, metabolism and excretion)-relevant organs and physiological tissues, and weaves a comprehensive and precise network containing >200 000 interactions among drugs and molecules. With the great efforts made to clarify the complex mechanism underlying drug pharmacokinetics and pharmacodynamics and rapidly emerging interests in artificial intelligence (AI)-based network analyses, DrugMAP is expected to become an indispensable supplement to existing databases to facilitate drug discovery. It is now fully and freely accessible at: https://idrblab.org/drugmap/.
药物的疗效和安全性被广泛认为取决于它们与多种具有重要药理学意义的分子的相互作用,因此系统地描绘研究药物的分子图谱和药物信息是至关重要的。然而,我们对这些信息的了解既不全面也不精确,这就需要构建一个新的数据库,提供一个包含大量药物及其相互作用分子的网络。在这里,我们构建了一个新的数据库来描述药物的分子图谱和药物信息(DrugMAP)。它为 >30000 种药物/药物候选物提供了相互作用分子的综合清单,给出了 >5000 种相互作用分子在不同疾病部位、ADME(吸收、分布、代谢和排泄)相关器官和生理组织中的差异表达模式,并编织了一个包含 >200000 个药物和分子之间相互作用的综合而精确的网络。通过阐明药物药代动力学和药效动力学的复杂机制的巨大努力,以及对人工智能(AI)为基础的网络分析的快速涌现的兴趣,DrugMAP 有望成为现有数据库的不可或缺的补充,以促进药物发现。它现在可以在:https://idrblab.org/drugmap/ 上全面免费获取。