ArticleCurrent issues in molecular biology2026
In Silico Molecular Docking and Pharmacokinetic Evaluation of Cannabinoid Derivatives as Multi-Target Inhibitors for EGFR, VEGFR-1, and VEGFR-2 Proteins.
Article in Current issues in molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed.
- Identification of selectiveRSC advances · 2026Article
- Identification of potential MenT3 inhibitors for Mycobacterium tuberculosis using the generative artificial intelligence and SilicoXplore platform.Scientific reports · 2026Article
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Authors and funding
2 authors.
Funding
Abstract
Cancer therapy development increasingly focuses on multi-target approaches to inhibit key proteins involved in tumor growth and angiogenesis. This study explored the potential inhibitory interactions of 110 cannabinoid derivatives using molecular docking simulations against epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor-1 (VEGFR-1), and VEGFR-2. Blind docking with AutoDock Vina identified eight recurrent hits across all three targets, including polar THC glucuronides and more drug-like cannabinoid scaffolds. Among these, 2'-Hydroxy-Delta (9)-THC and Ajulemic Acid combined favorable multi-target binding with superior predicted pharmacokinetic properties compared with other cannabinoids and reference inhibitors (lapatinib, motesanib, and sorafenib). ADME predictions highlighted Ajulemic Acid as the most promising oral candidate, showing optimal molecular weight, high oral bioavailability, and good gastrointestinal absorption, while 2'-Hydroxy-Delta (9)-THC exhibited potential for central nervous system exposure due to predicted blood-brain barrier permeability. In contrast, glucuronidated THC metabolites and highly lipophilic cannabinol esters displayed strong docking scores but suboptimal drug-likeness, suggesting prodrug- or metabolite-like behavior rather than suitability as primary oral leads. Toxicity predictions classified all compounds as moderately toxic, with Ajulemic Acid showing a comparatively more favorable safety profile. These findings do not demonstrate biological inhibition and should be interpreted strictly as hypothesis-generating computational evidence, providing a rational framework for future in vivo and in vitro validations.
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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.