Evidence map›Paper›PMID 29966734›Full record

ReviewBiochimie2018

G-quadruplex virtual drug screening: A review.

Robert C Monsen, John O Trent

Abstract readReview
In one paragraph

Review in Biochimie, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Structure-based drug design of small-molecule c-Myc G-quadruplex binders.Journal of computer-aided molecular design · 2026
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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.

Robert C MonsenDepartment of Biochemistry and Molecular Biology, University of Louisville, Louisville, KY, 40206, USA.
John O TrentJames Graham Brown Cancer Center, University of Louisville, Louisville, KY, 40206, USA; Department of Biochemistry and Molecular Biology, University of Louisville, Louisville, KY, 40206, USA; Department of Medicine, University of Louisville, Louisville, KY, 40206, USA. Electronic address: john.trent@louisville.edu.

Funding

Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
PILOT PROJECT PROGRAMP30GM106396 · NIGMS · UNIVERSITY OF LOUISVILLE · PI MILLER, DONALD M. · 2013 to 2017
$5.4M
Targeting Nucleic Acids with an Integrated Vitural and Actual ScreenR01GM077422 · NIGMS · UNIVERSITY OF LOUISVILLE · PI CHAIRES, JONATHAN B., TRENT, JOHN O · 2007 to 2020
$3.7M
NIGMS NIH HHS P30 GM106396NIGMS NIH HHS P41 GM103311NIGMS NIH HHS R01 GM077422
6 · The paper itself

Abstract

Over the past two decades biologists and bioinformaticians have unearthed substantial evidence supporting a role for G-quadruplexes as important mediators of biological processes. This includes telomere damage signaling, transcriptional activity, and splicing. Both their structural heterogeneity and their abundance in oncogene promoters makes them ideal targets for drug discovery. Currently, there are hundreds of deposited DNA and RNA quadruplex atomic structures which have allowed researchers to begin using in silico drug screening approaches to develop novel stabilizing ligands. Here we provide a review of the past decade of G-quadruplex virtual drug discovery approaches and campaigns. With this we introduce relevant virtual screening platforms followed by a discussion of best practices to assist future G4 VS campaigns.

Indexed as

G-QuadruplexesAlgorithmsComputer SimulationDNADrug DiscoveryHigh-Throughput Screening AssaysMolecular Docking SimulationNucleic Acid ConformationRNADNARNADockingDrug discoveryG-quadruplexVirtual screening

Identifiers

PMID29966734
PMCPMC6134840

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.