Evidence map›Paper›PMID 31203490›Full record

ArticleJournal of computer-aided molecular design2019

Rational creation and systematic analysis of cervical cancer kinase-inhibitor binding profile.

Min Han, Dongdong Sun

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Article in Journal of computer-aided molecular design, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

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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

3 citing papers in PubMed, 9 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Min HanDepartment of Obstetrics and Gynaecology, the Fourth People's Hospital of Jinan, Second Affiliated Hospital of Taishan Medical University, Jinan, 250031, China.
Dongdong SunDepartment of Obstetrics and Gynaecology, the Fourth People's Hospital of Jinan, Second Affiliated Hospital of Taishan Medical University, Jinan, 250031, China. yingssun@sina.cn.
Affiliated Hospital of Taishan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The kinase-regulatory cell signaling networks play a central role in the pathogenesis of human cervical cancer (hCC). However, only few kinase inhibitors have been successfully developed for treatment of this cancer to date. Considering that the active sites of protein kinases are highly conserved and small-molecule inhibitors should generally exhibit high promiscuity and broad specificity across the hCC-related kinase array, it is supposed that the established kinase targets of hCC can be targeted unexpectedly by certain noncognate kinase inhibitors. This provides a novel idea to practice the new uses for old drugs in anti-cancer chemotherapy. Here, we create a systematic kinase-inhibitor binding profile in a high-throughput manner by molecular docking and consensus scoring, where the kinases have been collected as therapeutic targets of hCC and the inhibitors are reversible, ATP-competitive and readily available. The docking/scoring scheme is tested rigorously with structure-solved and affinity-known kinase-inhibitor complex samples, which is later demonstrated to be effective in inferring unexpected inhibitor response to hCC-related kinases. Few promising kinase-inhibitor pairs are identified from the profile and tested experimentally at cellular and molecular levels. It is found that the kinase-inhibitor promiscuity is a common phenomenon but only few can interaction effectively and inhibit potently. In addition, the high-scoring inhibitors generally exhibit good suppressing potency on hCC cell viability as compared to those low-scoring ones, imparting that the created profile can well reflect the tumor cytotoxicity of noncognate kinase inhibitors. A further kinase assay suggests that the ErbB family kinases are the potential targets of these high-scoring inhibitors, with noncognate inhibitory activity up to nanomolar level. Structure analysis reveals that the nonbonded interactions of potent noncogante kinase-inhibitor binding can divided into a polar tail and a nonpolar lobe, which confer specificity and stability to the binding, respectively.

Indexed as

Antineoplastic AgentsDrug DesignDrug DiscoveryFemaleHeLa CellsHumansMolecular Docking SimulationProtein BindingProtein Kinase InhibitorsProtein KinasesUterine Cervical NeoplasmsAntineoplastic AgentsProtein Kinase InhibitorsProtein KinasesCell viabilityCervical cancerConsensus scoringInhibitory activityKinase–inhibitor binding profileMolecular docking

Identifiers

PMID31203490
OpenAlexW2952766786

What OpenQuestion holds

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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.