Evidence map›Paper›PMID 25832798›Full record

ArticleJournal of molecular modeling2015

In silico identification of novel kinase inhibitors by targeting B-Raf(v660e) from natural products database.

Zi-jie Wang, Zhi-ning Wan, Xu-dong Chen, Chuan-fang Wu, Guo-long Gao, Rong Liu, Zheng Shi, Jin-ku Bao

Abstract read
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In one paragraph

Article in Journal of molecular modeling, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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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

8 authors at 4 institutions in 1 country.

Zi-jie WangSchool of Life Sciences and Key Laboratory of Bio-resources, Ministry of Education, & State Key Laboratory of Biotherapy, Sichuan University, Chengdu, 610064, China.
Zhi-ning Wan
Xu-dong Chen
Chuan-fang Wu
Guo-long Gao
Rong Liu
Zheng Shi
Jin-ku Bao
Sichuan University · CNChengdu University · CNShenzhen International Travel Health Care Center · CNState Key Laboratory of Biotherapy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Ras/Raf/MEK/ERK (MAPK) signaling pathway has gained much attention from scientific community for therapeutic intervention in the past decades, specifically in oncology. Notably, a most prevalent B-Raf(v600e) mutant in Raf kinase family exhibits elevated kinase activity and results in constitutive activation of the MAPK pathway, thus making it a promising drug target for cancer therapy. Herein, virtual screening is applied to identify its potential inhibitors. Following the 25 ns molecular dynamic (MD) simulations, ZINC38541768, ZINC38541767, and ZINC12496469 are identified as B-Raf(v600e) potential inhibitors in a DFG-in conformation. Furthermore, according to the molecular mechanics/generalized born surface area (MM/GBSA) method, these three small molecules exhibit similar and good binding affinity toward B-Raf(v600e) (-38.76 kcal mol(-1), -42.60 kcal mol(-1), and -39.04 kcal mol(-1)). At the same time, several critical residues, such as I463, V471 in the P-loop, and DFG motif residue D594 within the A-loop, are also well clarified. All these results may not only indicate some future applications of inhibitors targeting B-Raf(v600e), but also benefit B-Raf(v600e) harboring cancer patients.

Indexed as

Biological ProductsCell ProliferationHumansMitogen-Activated Protein Kinase KinasesMutationNeoplasmsPhosphorylationProtein Kinase InhibitorsProto-Oncogene Proteins B-rafSignal TransductionBiological ProductsBRAF protein, humanMitogen-Activated Protein Kinase KinasesProtein Kinase InhibitorsProto-Oncogene Proteins B-raf

Identifiers

PMID25832798
OpenAlexW2136958473

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.