Accelerating Scaffold Hopping in Fourth-Generation Epidermal Growth Factor Receptor Inhibitors via Multilevel Virtual Screening.

Zhiqi Sun, Donghui Huo, Jiangyu Guo, Aixia Yan

Abstract read

In one paragraph

Article in ACS medicinal chemistry letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhiqi SunState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing 100029, P. R. China.

Donghui HuoState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing 100029, P. R. China.

Jiangyu GuoState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing 100029, P. R. China.

Aixia YanState Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing 100029, P. R. China.ORCID https://orcid.org/0000-0003-4811-8510

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The epidermal growth factor receptor (EGFR) family plays a crucial role in regulating cell proliferation, apoptosis, and differentiation. However, challenges related to drug resistance have emerged in the clinical applications of this family. This study addresses resistance mediated by the L858R/T790M/C797S EGFR mutation through a multilevel virtual screening strategy that integrates 3D shape similarity screening, multitask deep learning-based activity prediction, molecular docking, and molecular dynamics simulations. From 18 million drug-like molecules screened, 12 candidates underwent in vitro enzymatic testing, leading to the identification of three novel scaffold inhibitors. Compound L15 demonstrated potent inhibitory activity against the L858R/T790M/C797S mutant EGFR (IC

Indexed as

epidermal growth factor receptor (EGFR)L858R/T790M/C797S mutant EGFRmolecular dynamics simulationmultitask deep learningvirtual screening

Identifiers

PMID41089476

DOI10.1021/acsmedchemlett.5c00194

PMCPMC12516364

What OpenQuestion holds

Textmetadata

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Registered trials

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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.