Evidence map›Paper›PMID 42331856›Full record

ArticleScientific reports2026

PocketMaster provides a flexible and automated tool for analyzing, clustering, and visualizing structural diversity in protein pockets.

Narek Abelyan

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

1 author.

Narek AbelyanInstitute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan, Armenia. narekabelyan@gmail.com.

Funding

Higher Education and Science Committee of the Republic of Armenia 21AG-1F057
6 · The paper itself

Abstract

PocketMaster is a flexible and automated tool for the analysis, clustering, and interpretation of protein pockets, enabling the exploration of structural diversity in functional and interacting regions of proteins. The tool provides multiple strategies for defining pocket alignment regions, along with various alignment algorithms and clustering approaches, allowing analyses to be customized for different research objectives. In addition, it automatically documents results and provides informative visualizations and reports. With these capabilities, PocketMaster can be particularly valuable in the early stages of drug design, where accurate analysis and selection of protein structures are essential. Using TYK2 as a case study, PocketMaster demonstrates its ability to identify conformational differences between kinase and pseudokinase domains, as well as subtypes of structures within each domain, reflecting the influence of various ligands and protein states. The estrogen receptor alpha (ERα) ligand-binding pocket was also analyzed as an additional case study, showing the tool's performance in capturing conformational variations in helix 12 (H12) between active (agonist-bound) and inactive (antagonist-bound) states. The results confirm known structural features and illustrate the potential of the tool for systematic exploration of protein pockets, quantitative assessment of differences, and support of rational drug design. The PocketMaster source code, together with example input files and documentation, can be accessed at https://github.com/narek-abelyan/PocketMaster .

Indexed as

ProteinsSoftwareAlgorithmsBinding SitesCluster AnalysisClustering AlgorithmsDrug DesignEstrogen Receptor alphaHumansLigandsModels, MolecularProtein BindingProtein ConformationTYK2 KinaseEstrogen Receptor alphaLigandsProteinsTYK2 KinaseConformational diversityProtein alignmentProtein pocket analysisRMSD calculationStructural clusteringStructure-based drug design

Identifiers

PMID42331856
PMCPMC13575124

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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.