Evidence map›Paper›PMID 40873722›Full record

ArticleIn silico pharmacology2025

Computational assessment of natural compounds as potential hexokinase 2 inhibitors.

Abdullahi Ibrahim Uba, Eleonora Procino, Lorenza Marinaccio, Adriano Mollica, Gokhan Zengin

Abstract read
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Article in In silico pharmacology, 2025. 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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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Abdullahi Ibrahim UbaDepartment of Molecular Biology and Genetics, Istanbul AREL University, 34537 Istanbul, Turkey.ORCID 0000-0002-0853-108X
Eleonora ProcinoUniversità degli Studi "G. d'Annunzio" di Chieti-Pescara, Chieti, Italy.ORCID 0000-0002-7242-4860
Lorenza MarinaccioUniversità degli Studi "G. d'Annunzio" di Chieti-Pescara, Chieti, Italy.
Adriano MollicaUniversità degli Studi "G. d'Annunzio" di Chieti-Pescara, Chieti, Italy.
Gokhan ZenginDepartment of Biology, Science Faculty, Selcuk University, 42300 Konya, Turkey.ORCID 0000-0001-6548-7823

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hexokinase 2 (HK2), a central enzyme in the glycolytic pathway, is frequently overexpressed in malignant cells, contributing to enhanced glucose metabolism and tumor progression. Despite its recognized role in cancer metabolism, effective and selective HK2 inhibitors from natural sources remain underexplored. This study aimed to identify promising natural product inhibitors of HK2 through an integrated computational approach. A diverse set of 100 natural compounds-including phenolics, terpenoids, alkaloids, and anthraquinones-was virtually screened using Glide XP docking to predict binding affinities. Subsequent molecular dynamics (MD) simulations and MM-GBSA binding free energy calculations were performed to validate docking results and evaluate complex stability over time. Notably, several phenolics, particularly salvianolic acid A, salvianolic acid B, verbascoside, quercetin, and hyperoside, exhibited strong binding affinities and favorable interaction profiles. Salvianolic acid A recorded the best docking score (- 9.58 kcal/mol), while hyperoside showed exceptional structural stability during 30 ns MD simulations and a competitive MM-GBSA binding energy (- 42.35 kcal/mol), approaching that of the native ligand (- 55.51 kcal/mol). Structural interaction analysis revealed that hyperoside formed persistent hydrogen bonds with key catalytic residues of HK2 (Glu742, Asp657, Glu708), supporting its potential as a lead scaffold. These findings highlight the value of phenolic natural products as potential HK2 inhibitors and lay the groundwork for future anticancer drug development targeting cancer-specific metabolic pathways.

Indexed as

Cancer metabolismGlycolytic enzyme inhibitionIn silico analysisLead optimizationNatural product drug discoveryPhenolic compoundsProtein–ligand interactionVirtual screening

Identifiers

PMID40873722
PMCPMC12378251

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