ArticleInternational journal of molecular sciences2026
In Silico Development of Novel Quinazoline-Based EGFR Inhibitors via 3D-QSAR, Docking, ADMET, and Molecular Dynamics.
Article in International journal of molecular sciences, 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Novel Fluorophenylated Dihydroimidazotriazinones as Potential Anticancer Agents: Design, Synthesis, In Vitro, Ex Vivo and In Silico Characterisation.International journal of molecular sciences · 2026Article
- Cannabis as a source of novel therapeutics: A computational study combining LBDD and structure-based docking/dynamics to identify novel drug-like compounds for colorectal cancer.Journal, genetic engineering & biotechnology · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A library of thirty-one quinazoline derivatives was assessed as potential inhibitors of epidermal growth factor receptor kinase (EGFR) using 3D-QSAR methods, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). Training and test sets were generated by aligning the molecules to the lowest-energy conformer of the most active compound. The optimized models exhibited strong statistical performance, with R
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Registered trials
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