Evidence map›Paper›PMID 22918724›Full record

ArticleMolecular diversity2012

A rational approach to selective pharmacophore designing: an innovative strategy for specific recognition of Gsk3β.

H Pradeep, G K Rajanikant

Open access · bronzeAbstract read
In one paragraph

Article in Molecular diversity, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 19 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.

H PradeepBioinformatics Centre, School of Biotechnology, National Institute of Technology, Calicut 673601, India.
G K Rajanikant
National Institute of Technology Calicut · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose a novel cheminformatics approach that combines structure and ligand-based design to identify target-specific pharmacophores with well-defined exclusion ability. Our strategy includes the prediction of selective interactions, developing structure, and knowledge-based selective pharmacophore models, followed by database screening and molecular docking. This unique strategy was employed in addressing the off-target toxicity of Gsk3β and CDKs. The connections of Gsk3β in eukaryotic cell apoptosis and the extensive potency of Gsk3β inhibitors to block cell death have made it a potential drug-discovery target for many grievous human disorders. Gsk3β is phylogenetically very closely related to the CDKs, such as CDK1 and CDK2, which are suggested to be the off-target proteins of Gsk3β inhibitors. Here, we have employed novel computational approaches in designing the ligand candidates that are potentially inhibitory against Gsk3β, with well-defined the exclusion ability to CDKs. A structure-ligand -based selective pharmacophore was modeled. This model was used to retrieve molecules from the zinc database. The hits retrieved were further screened by molecular docking and protein-ligand interaction fingerprints. Based on these results, four molecules were predicted as selective Gsk3β antagonists. It is anticipated that this unique approach can be extended to investigate any protein-ligand specificity.

Indexed as

Drug DesignDrug Evaluation, PreclinicalGlycogen Synthase Kinase 3Glycogen Synthase Kinase 3 betaInformaticsLigandsModels, MolecularMolecular Docking SimulationProtein BindingProtein ConformationProtein Kinase InhibitorsSubstrate SpecificityGlycogen Synthase Kinase 3Glycogen Synthase Kinase 3 betaGSK3B protein, humanLigandsProtein Kinase Inhibitors

Identifiers

PMID22918724
PMCPMC7089308
OpenAlexW2079193190

What OpenQuestion holds

Textmetadata
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.