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Open access databases available for the pesticide lead discovery
Daozhong Wang1, Hua Deng2, Tao Zhang3
1State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; Interdisciplinary Sciences Institute, Huazhong Agricultural University, Wuhan 430070, China; College of Veterinary Medicine, National Reference Laboratory of Veterinary Drug Residues (HZAU) and MAO Key Laboratory for Detection of Veterinary Drug Residues, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health，Huazhong Agricultural University, Shenzhen 518000, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China.
This review categorizes 26 open-access pesticide databases, aiding pesticide research and discovery. It organizes data on chemical structures, activities, toxicity, and computational tools for better decision-making.
Area of Science:
- Agricultural Science
- Computational Chemistry
- Toxicology
Background:
- Pesticide research relies on multidisciplinary collaboration and big data analysis.
- Numerous pesticide databases exist, but data is scattered, overlapping, and inconsistently formatted.
- This fragmentation hinders efficient information analysis and comparison for pesticide discovery.
Purpose of the Study:
- To review and categorize 26 open-access pesticide research databases.
- To assess database content relevant to ligand-based drug design (LBDD) and structure-based drug design (SBDD).
- To improve data accessibility and accelerate decision-making in pesticide research.
Main Methods:
- Systematic review of 26 open-access pesticide databases.
- Classification of database content into three main categories.
- Analysis of information relevant to LBDD and SBDD.
Main Results:
- Databases were categorized based on: chemical structure-property relationships (activity, resistance, toxicity, environmental adaptation), mode of action studies (target identification, pathways), and computational design tools.
- This is the first comprehensive review of open-access pesticide databases.
- The classification facilitates information retrieval and comparison.
Conclusions:
- Organizing pesticide data from diverse open-access databases enhances accessibility.
- Streamlined data access accelerates the pesticide discovery and development process.
- This structured approach supports informed decision-making in pesticide research.
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