ArticleJournal of cheminformatics2013
CVDHD: a cardiovascular disease herbal database for drug discovery and network pharmacology.
Article in Journal of cheminformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Overview and limitations of database in global traditional medicines: A narrative review.Acta pharmacologica Sinica · 2025Review
- Artificial intelligence in traditional Chinese medicine: advances in multi-metabolite multi-target interaction modeling.Frontiers in pharmacology · 2025Review
- DISPEL: database for ascertaining the best medicinal plants to cure human diseases.Database : the journal of biological databases and curation · 2023Article
- Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review.Frontiers in pharmacology · 2023Review
- Review
- phytochemdb: a platform for virtual screening and computer-aided drug designing.Database : the journal of biological databases and curation · 2022Article
- Therapeutic Effects and Safe Uses of Plant-Derived Polyphenolic Compounds in Cardiovascular Diseases: A Review.Drug design, development and therapy · 2021Review
- Pain Chemogenomics Knowledgebase (Pain-CKB) for Systems Pharmacology Target Mapping and Physiologically Based Pharmacokinetic Modeling Investigation of Opioid Drug-Drug Interactions.ACS chemical neuroscience · 2020Article
- Applications of Network Pharmacology in Traditional Chinese Medicine Research.Evidence-based complementary and alternative medicine : eCAM · 2020Review
- Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery.Frontiers in pharmacology · 2019Review
- IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics.Scientific reports · 2018Article
- YaTCM: Yet another Traditional Chinese Medicine Database for Drug Discovery.Computational and structural biotechnology journal · 2018Article
- How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?Molecules (Basel, Switzerland) · 2017Review
- Network Pharmacology Studies on the Bioactive Compounds and Action Mechanisms of Natural Products for the Treatment of Diabetes Mellitus: A Review.Frontiers in pharmacology · 2017Review
- Review of natural product databases.Cell proliferation · 2015Review
- Many InChIs and quite some feat.Journal of computer-aided molecular design · 2015Article
- AlzPlatform: an Alzheimer's disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research.Journal of chemical information and modeling · 2014Article
- TCMSP: a database of systems pharmacology for drug discovery from herbal medicines.Journal of cheminformatics · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiovascular 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.
conclusionsCVDHD 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 http://pkuxxj.pku.edu.cn/CVDHD.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.