CVDHD: a cardiovascular disease herbal database for drug discovery and network pharmacology

Gu et al. Journal of Cheminformatics 2013, 5:51

Background: Cardiovascular disease (CVD) is the leading cause of death and associates with multiple risk factors.
Herb medicines have been used to treat CVD long ago in china and several natural products or derivatives (e.g.,
aspirin and reserpine) are most common drugs all over the world. The objective of this work was to construct a
systematic database for drug discovery based on natural products separated from CVD-related medicinal herbs and
to research on action mechanism of herb medicines.

Description: The cardiovascular disease herbal database (CVDHD) was designed to be a comprehensive resource for
virtual screening and drug discovery from natural products isolated from medicinal herbs for cardiovascular-related
diseases. CVDHD comprises 35230 distinct molecules and their identification information (chemical name, CAS registry
number, molecular formula, molecular weight, international chemical identifier (InChI) and SMILES), calculated molecular
properties (AlogP, number of hydrogen bond acceptor and donors, etc.), docking results between all molecules and
2395 target proteins, cardiovascular-related diseases, pathways and clinical biomarkers. All 3D structures were optimized
in the MMFF94 force field and can be freely accessed.

Conclusions: CVDHD integrated medicinal herbs, natural products, CVD-related target proteins, docking results, diseases
and clinical biomarkers. By using the methods of virtual screening and network pharmacology, CVDHD will provide a
platform to streamline drug/lead discovery from natural products and explore the action mechanism of medicinal herbs.
CVDHD is freely available at

Keywords: Cardiovascular disease, Drug discovery, Network pharmacology, Molecular docking, Virtual screening, Herbal
formula, Natural products, Medicinal herbs, Traditional Chinese medicine

Content Type OER
Uploaded By Steven Wathen
DOI 10.1186/1758-2946-5-51
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Content Tags Audience, Content type, English, Graduate, Language, Publication, Researcher