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DOI 10.1007/s00894-026-06903-4

Медицинская библиотека · Journal of molecular modeling · 2026

Membrane interactions and pore stability of aurein 1.2 and LLAA in single- and multi-peptide systems revealed by coarse-grained molecular dynamics simulations.

Ansarihaghi Roshanak

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Аннотация

CONTEXT: Aurein 1.2 is a short cationic antimicrobial peptide secreted by the Australian tree frog Litoria aurea. In this study, we investigated the membrane interactions of aurein 1.2 and its analog LLAA in single- and multi-peptide systems using model bacterial-like and eukaryotic-like lipid bilayers. LLAA exhibited stronger membrane interactions and deeper insertion than aurein, particularly in the bacterial-like membrane models. The simulations further indicated that peptide dissociation from aggregates was generally associated with increased membrane insertion. In pre-formed pore simulations, LLAA pore assemblies rapidly disassembled, whereas aurein pore assemblies remained stable for longer periods, particularly in the bacterial-like membrane models. These findings suggest that differences in peptide sequence and charge distribution are associated with distinct membrane insertion behavior, peptide organization, and the stability of pre-formed pore assemblies in the membrane models investigated.

METHODS

Coarse-grained molecular dynamics simulations were performed using the MARTINI force field with the polarizable water model. Simulations were carried out with GROMACS for systems containing single peptides, five-peptide membrane insertion systems, and pre-formed pore assemblies in POPC, DPPC, and POPE/POPG bilayers. Peptide insertion, orientation, electrostatic interactions, clustering, pre-formed pore stability, and water occupancy were analyzed using GROMACS analysis tools together with custom VMD Tcl, Python, and C++ scripts.

Для цитирования: Ansarihaghi Roshanak. Membrane interactions and pore stability of aurein 1.2 and LLAA in single- and multi-peptide systems revealed by coarse-grained molecular dynamics simulations.. Journal of molecular modeling. 2026. DOI: 10.1007/s00894-026-06903-4.

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