ReviewFrontiers in genetics2019
Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives.
Review in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.
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
56 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Colombian Contributions Fighting Leishmaniasis: A Systematic Review on Antileishmanials Combined with Chemoinformatics Analysis.Molecules (Basel, Switzerland) · 2020Pooled it
- Computational Investigation of Cinnamon Phytochemicals Targeting Key Cancer Signaling Pathways: Molecular Docking, ADMET and Molecular Dynamics Simulations Analysis.Current issues in molecular biology · 2026Article
- Natural Products in Epilepsy Treatment: From Traditional Medicine Towards Computational Drug Discovery.Current issues in molecular biology · 2026Review
- Quantum computing applications in drug discovery.Briefings in bioinformatics · 2026Review
- Nature meets machine: the AI renaissance in natural product drug discovery.Natural products and bioprospecting · 2026Review
- Bioinformatics-Driven, Plant-Based Antibiotic Research Against Quorum Sensing and Biofilm Formation inBiomolecules · 2026Review
- BEDB: a comprehensive binding energy database for molecular docking and dynamics: insights into Human Metapneumovirus (HMPV) Inhibitors.Database : the journal of biological databases and curation · 2026Article
- A Comparative Chemoinformatics Analysis of Compounds Extracted fromCombinatorial chemistry & high throughput screening · 2026Article
- Microbial-Derived Anti-Cancer Compounds: Advances in Drug Discovery, Bioengineering, and Therapeutic Applications.Anti-cancer agents in medicinal chemistry · 2026Review
- Acetylcholinesterase as a Multifunctional Target in Amyloid-Driven Neurodegeneration: From Dual-Site Inhibitors to Anti-Agregation Strategies.International journal of molecular sciences · 2025Review
- Network Pharmacology as a Tool to Investigate the Antioxidant and Anti-Inflammatory Potential of Plant Secondary Metabolites-A Review and Perspectives.International journal of molecular sciences · 2025Review
- Strategies Used for the Discovery of New Microbial Metabolites with Antibiotic Activity.Molecules (Basel, Switzerland) · 2025Review
- Unlocking the potential of phytochemicals in inhibiting SARS-CoV-2 MScientific reports · 2025Article
- Quantum-inspired computational drug design for phytopharmaceuticals: a herbal holography analysis.Journal of molecular modeling · 2025Review
- Artificial Intelligence in Natural Product Drug Discovery: Current Applications and Future Perspectives.Journal of medicinal chemistry · 2025Review
- Comprehensive assessment of antioxidant, antidiabetic, and anti-glycation properties of aqueous and methanolic extracts fromFrontiers in pharmacology · 2025Article
- G-Computational and structural biotechnology journal · 2024Article
- Harnessing genomic technologies for one health solutions in the tropics.Globalization and health · 2024Review
- In-Silico discovery of 17alpha-hydroxywithanolide-D as potential neuroprotective allosteric modulator of NMDA receptor targeting Alzheimer's disease.Scientific reports · 2024Article
- Docking and Molecular Dynamics Simulation Revealed the Potential Inhibitory Activity of Amygdalin in Triple-Negative Breast Cancer Therapeutics Targeting the BRCT Domain of BARD1 Receptor.Molecular biotechnology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The discovery of new pharmaceutical drugs is one of the preeminent tasks-scientifically, economically, and socially-in biomedical research. Advances in informatics and computational biology have increased productivity at many stages of the drug discovery pipeline. Nevertheless, drug discovery has slowed, largely due to the reliance on small molecules as the primary source of novel hypotheses. Natural products (such as plant metabolites, animal toxins, and immunological components) comprise a vast and diverse source of bioactive compounds, some of which are supported by thousands of years of traditional medicine, and are largely disjoint from the set of small molecules used commonly for discovery. However, natural products possess unique characteristics that distinguish them from traditional small molecule drug candidates, requiring new methods and approaches for assessing their therapeutic potential. In this review, we investigate a number of state-of-the-art techniques in bioinformatics, cheminformatics, and knowledge engineering for data-driven drug discovery from natural products. We focus on methods that aim to bridge the gap between traditional small-molecule drug candidates and different classes of natural products. We also explore the current informatics knowledge gaps and other barriers that need to be overcome to fully leverage these compounds for drug discovery. Finally, we conclude with a "road map" of research priorities that seeks to realize this goal.
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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 OpenQuestion graph.