Antimicrobial peptides at (lipid) interfaces: Insights from monolayer models

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Química Orgánica
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Física Aplicada
dc.contributor.affiliationUniversidade de Santiago de Compostela. Centro de Investigación en Química Biolóxica e Materiais Moleculares (CiQUS)
dc.contributor.authorAntelo Riveiro, Paula
dc.contributor.authorGarcía Fandiño, Rebeca
dc.contributor.authorPiñeiro Guillén, Ángel
dc.date.accessioned2026-04-09T10:22:31Z
dc.date.available2026-04-09T10:22:31Z
dc.date.issued2026
dc.description.abstractAntimicrobial peptides (AMPs) are key effectors of innate immunity that, beyond their canonical activity, exhibit promising therapeutic potential against cancer and cellular senescence. Their efficacy relies on selective membrane disruption driven by specific lipid signatures, yet quantifying these interactions in complex bilayer systems remains challenging. Lipid monolayers serve as powerful reductionist models to isolate the physicochemical determinants of this selectivity, effectively mimicking the outer leaflet of bacterial, cancerous, or senescent membranes. This review provides a critical analysis of how lipid composition, packing density, and phase behavior modulate AMP adsorption and insertion. We systematically integrate thermodynamic profiling (surface pressure, compressibility, mixing energy) with advanced structural and morphological characterization. Special emphasis is placed on how spectroscopic techniques (IRRAS, GIXD, SFG) and real-time microscopy (BAM, fluorescence, AFM) resolve peptide orientation, secondary structure induction, and lipid domain remodeling at the mesoscale. These experimental observables are bridged with Molecular Dynamics (MD) simulations, establishing a feedback loop between macroscopic measurements and atomistic resolution. By defining the advantages and limitations of monolayer models relative to vesicles and bilayers, we outline a rational framework for leveraging interfacial insights in the design of next-generation peptide therapeutics and nanobiotechnological applications.
dc.description.peerreviewedSI
dc.description.sponsorshipThis work was supported by the Spanish Agencia Estatal de Investigación (AEI) and the ERDF (PID2022-141534OB-I00 and CNS2023-144353), by Xunta de Galicia (ED431C 2025/15, ED431C 2021/21 and Centro de investigación do Sistema universitario de Galicia accreditation 2023-2027, ED431G 2023/03) and the European Union (European Regional Development Fund – ERDF). P.A-R. thanks Xunta de Galicia for her predoctoral contract (ED481A-2024-073).
dc.identifier.citationAntelo‑Riveiro, P., García‑Fandiño, R., Piñeiro, Á. (2026). Antimicrobial peptides at (lipid) interfaces: Insights from monolayer models." Advances in Colloid and Interface Science", 350
dc.identifier.doi10.1016/j.cis.2025.103775
dc.identifier.essn1873-3727
dc.identifier.issn0001-8686
dc.identifier.urihttps://hdl.handle.net/10347/46628
dc.journal.titleAdvances in Colloid and Interface Science
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-141534OB-I00/ES/DESCIFRANDO LA CONEXION DEL CODIGO LIPIDICO ENTRE CANCER, INFECCION Y ENVEJECIMIENTO: HACIA HERRAMIENTAS TERANOSTICAS NO CONVENCIONALES Y VACUNAS BASADAS EN LA MEMORIA INNATA
dc.relation.publisherversionhttps://doi.org/10.1016/j.cis.2025.103775
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAntimicrobial peptides
dc.subjectLipid interfaces
dc.subjectPeptide-lipid interactions
dc.subjectInterfacial thermodynamics
dc.subjectLangmuir monolayers
dc.subjectMolecular modeling
dc.subject.classification2306 Química orgánica
dc.subject.classification22 Física
dc.titleAntimicrobial peptides at (lipid) interfaces: Insights from monolayer models
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number350
dspace.entity.typePublication
relation.isAuthorOfPublication7207f196-ba01-47c3-a5a7-dac268e007d3
relation.isAuthorOfPublicationf4d82ce1-22fa-4ac4-a7f7-71690607ae55
relation.isAuthorOfPublication.latestForDiscovery7207f196-ba01-47c3-a5a7-dac268e007d3

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