PDTD: A Web-Accessible Protein Database for Drug Target Identification
Author Information
Author(s): Gao Zhenting, Li Honglin, Zhang Hailei, Liu Xiaofeng, Kang Ling, Luo Xiaomin, Zhu Weiliang, Chen Kaixian, Wang Xicheng, Jiang Hualiang
Primary Institution: Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences
Hypothesis
The study aims to develop a comprehensive protein database to assist in drug target identification and validation.
Conclusion
PDTD is a valuable resource for identifying binding proteins for active compounds or existing drugs.
Supporting Evidence
- PDTD contains over 1100 protein entries with 3D structures.
- The database integrates with TarFisDock for identifying binding proteins.
- PDTD categorizes targets by therapeutic areas and biochemical functions.
Takeaway
PDTD is like a big library that helps scientists find the right proteins to target when making new medicines.
Methodology
The database was constructed using data from various sources and integrated with a reverse docking program.
Limitations
The database may contain redundancy for flexible proteins and is limited to proteins with known 3D structures.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website