Evidence map›Paper›PMID 30582689›Full record

ArticleJournal of chemical information and modeling2019

Structural Insights into Characterizing Binding Sites in Epidermal Growth Factor Receptor Kinase Mutants.

Zheng Zhao, Lei Xie, Philip E Bourne

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Journal of chemical information and modeling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.0field-weighted citation impact, top 12% of its field
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

23 citing papers in PubMed, 52 citations in OpenAlex.

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  5. Current computer-aided drug design · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Zheng ZhaoDepartment of Biomedical Engineering , University of Virginia , Charlottesville , Virginia 22904 , United States of America.ORCID 0000-0003-1453-3230
Lei XieDepartment of Computer Science, Hunter College , The City University of New York , New York , New York 10065 , United States of America.
Philip E BourneDepartment of Biomedical Engineering , University of Virginia , Charlottesville , Virginia 22904 , United States of America.
University of Virginia · USThe Graduate Center, CUNY · US

Funding

Omics data integration and analysis for structure-based multi-target drug designR01GM122845 · NIGMS · NORTHEASTERN UNIVERSITY · PI Lei Xie · 2017 to 2026
$3.0M
Drug discovery by integrating chemical genomics and structural systems biologyR01LM011986 · NLM · HUNTER COLLEGE · PI BRINKMAN, FIONA, BURLEY, STEPHEN K · 2014 to 2017
$1.2M
NIGMS NIH HHS R01 GM122845NLM NIH HHS R01 LM011986
6 · The paper itself

Abstract

Over the last two decades epidermal growth factor receptor (EGFR) kinase has become an important target to treat nonsmall cell lung cancer (NSCLC). Currently, three generations of EGFR kinase-targeted small molecule drugs have been FDA approved. They nominally produce a response at the start of treatment and lead to a substantial survival benefit for patients. However, long-term treatment results in acquired drug resistance and further vulnerability to NSCLC. Therefore, novel EGFR kinase inhibitors that specially overcome acquired mutations are urgently needed. To this end, we carried out a comprehensive study of different EGFR kinase mutants using a structural systems pharmacology strategy. Our analysis shows that both wild-type and mutated structures exhibit multiple conformational states that have not been observed in solved crystal structures. We show that this conformational flexibility accommodates diverse types of ligands with multiple types of binding modes. These results provide insights for designing a new generation of EGFR kinase inhibitor that combats acquired drug-resistant mutations through a multiconformation-based drug design strategy.

Indexed as

Molecular Dynamics SimulationMutationBinding SitesErbB ReceptorsLigandsMutant ProteinsProtein ConformationErbB ReceptorsLigandsMutant Proteins

Identifiers

PMID30582689
PMCPMC6441332
OpenAlexW2906132609

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.