Evidence map›Paper›PMID 42133206›Full record

ArticleJournal of computer-aided molecular design2026

Integrated computational modeling of chalcone-based inhibitors targeting carbonic anhydrase I and II: 3D-QSAR, molecular docking, and dynamics simulations.

Mauricio Soto, David Cabezas, Felipe Stambuk, Cesar González, Alison Acosta, Marcos Lorca, Luis Espinoza, Katy Díaz, Andrés F Olea, Marco Mellado and 1 more

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Article in Journal of computer-aided molecular design, 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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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

11 authors.

Mauricio SotoDepartamento de Química, Universidad Técnica Federico Santa María, 2390123, Valparaíso, Chile.
David CabezasCenter for Nuclear Research in Health and Biomedical Applications, Comisión Chilena de Energía Nuclear,, Nueva Bilbao 12051, 7550000, Las Condes, Santiago, Chile.
Felipe StambukGrupo de Marcadores Inmunológicos, Instituto de Biología, Pontificia Universidad Católica de Valparaíso, 2374631, Valparaíso, Chile.
Cesar GonzálezDepartamento de Química, Universidad Técnica Federico Santa María, 2390123, Valparaíso, Chile.
Alison AcostaFacultad de Ciencias Exactas, Departamento de Ciencias Químicas, Universidad Andrés Bello, 2531015, Viña del Mar, Chile.
Marcos LorcaFacultad de Ciencias de la Vida, Carrera de Química y Farmacia, Universidad de Viña del Mar, 2572002, Viña del Mar, Chile.
Luis EspinozaDepartamento de Química, Universidad Técnica Federico Santa María, 2390123, Valparaíso, Chile.
Katy DíazDepartamento de Química, Universidad Técnica Federico Santa María, 2390123, Valparaíso, Chile.
Andrés F OleaGrupo QBAB, Instituto de Ciencias Aplicadas, Facultad de Ingeniería, Universidad Autónoma de Chile, 89580640, Huechuraba, Chile.
Marco MelladoDirección de Investigación, Universidad Bernardo O'Higgins, 8370993, Santiago, Chile. marco.mellado@psh.ubo.cl.ORCID 0000-0001-9577-5180
Jaime MellaInstituto de Química, Facultad de Ciencias, Universidad de Valparaíso, 2360102, Valparaíso, Chile. jaime.mella@uv.cl.ORCID 0000-0002-2434-8461

Funding

Agencia Nacional de Investigación y Desarrollo Convocatoria Nacional Subvención a Instalación en la Academia Convocatoria año 2021 Folio SA77210078
6 · The paper itself

Abstract

Carbonic anhydrase isoforms I and II (hCA-I and hCA-II) are metalloenzymes involved in essential physiological processes and represent relevant therapeutic targets for disorders such as glaucoma and osteoporosis. Chalcones have emerged as promising scaffolds for carbonic anhydrase inhibition; however, their structure-activity relationships, particularly for non-sulfonamide derivatives, remain insufficiently explored from a computational point of view. In this study, a dataset of 118 chalcone derivatives has been analyzed by using a three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, which comprises Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA). The developed models exhibited strong internal consistency and predictive capability for both isoforms. For hCA-I, steric, electrostatic, hydrophobic, and hydrogen bond acceptor fields has been identified as key contributors to inhibitory activity, whereas for hCA-II, hydrogen bond donor features played a more prominent role. Molecular docking and molecular dynamics simulations have been employed as complementary approaches to analyze ligand-protein interactions and binding stability. In addition, quantum chemical descriptors, derived from density functional theory, that have been integrated with the 3D-QSAR analysis, reveal a consistent correspondence between contour map features and the distribution of frontier molecular orbitals and molecular electrostatic potential. Furthermore, ADME-based pharmacokinetic properties of the proposed compounds have been evaluated to assess their potential drug-likeness. Based on the integrated computational analysis, six new chalcone derivatives, with predicted inhibitory activity in the nanomolar range, are proposed. Overall, this study provides a consistent physicochemical framework for understanding the inhibitory activity of chalcone derivatives and highlights key molecular features that may guide the modulation of activity across hCA-I and hCA-II isoforms.

Indexed as

Carbonic Anhydrase ICarbonic Anhydrase IICarbonic Anhydrase InhibitorsChalconeChalconesBinding SitesDrug DesignHumansHydrogen BondingHydrophobic and Hydrophilic InteractionsLigandsMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingQuantitative Structure-Activity RelationshipCarbonic Anhydrase ICarbonic Anhydrase IICarbonic Anhydrase InhibitorsChalconeChalconesLigands3D-QSARCarbonic anhydrase I and II inhibitorsChalcone pharmacophoric coreHydrogen bondingSelectivity

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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.