ArticleComputational and mathematical methods in medicine2021
Ligand-Based and Docking-Based Virtual Screening of MDM2 Inhibitors as Potent Anticancer Agents.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Cytotoxic Activity and In Silico Study of Secondary Metabolites Derived fromMarine drugs · 2026Article
- Synthesis, characterization, and anticancer evaluation ofToxicology reports · 2026Article
- Artificial Intelligence in Selected Domains of Drug Discovery: A Critical Narrative Review.Drug design, development and therapy · 2026Review
- Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade.Pharmaceuticals (Basel, Switzerland) · 2023Review
- In-silico identification of small molecule benzofuran-1,2,3-triazole hybrids as potential inhibitors targeting EGFR in lung cancer via ligand-based pharmacophore modeling and molecular docking studies.In silico pharmacology · 2023Article
- Systems andFrontiers in pharmacology · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A ligand-based and docking-based virtual screening was carried out to identify novel MDM2 inhibitors. A pharmacophore model with four features was used for virtual screening, followed by molecular docking. Seventeen compounds were selected for an
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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.