DrugMAP: molecular atlas and pharma-information of all drugs.

Journal: Nucleic acids research
PMID:

Abstract

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/.

Authors

  • Fengcheng Li
    College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China.
  • Jiayi Yin
    Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China.
  • Mingkun Lu
    College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
  • Minjie Mou
    College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
  • Zhaorong Li
    Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, 330110, China.
  • Zhenyu Zeng
    Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, 330110, China.
  • Ying Tan
  • Shanshan Wang
    Key Laboratory of Agri-food Safety and Quality, Institute of Quality Standard and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Ministry of Agriculture of China, Beijing, 100081, PR China.
  • Xinyi Chu
    Yunnan Hongqingfu Biotechnology Co., LTD., Kunming 650000, Yunnan, P. R. China.
  • Haibin Dai
    College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
  • Tingjun Hou
    College of Pharmaceutical Sciences, Zhejiang University , Hangzhou, Zhejiang 310058, China.
  • Su Zeng
    Laboratory of Pharmaceutical Analysis and Drug Metabolism, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Yuzong Chen
    Bioinformatics and Drug Design Group, Department of Pharmacy, National, University of Singapore, Singapore, 117543, Singapore.
  • Feng Zhu
    Department of Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People's Republic of China.