Decoding Membrane Biophysics for Nucleic Acid Delivery: Bridging Bilayer Simulations and Lipid Nanoparticle Functionality
Abstract
Lipid nanoparticles (LNPs) are a proven platform for delivering nucleic acids, evidenced by the approvals of patisiran and COVID-19 mRNA vaccines. However, the molecular mechanisms behind lipid organization, cargo encapsulation, and intracellular release remain partially understood. This review links molecular dynamics (MD) simulations of lipid bilayers to functional LNP systems through a three-level framework. (i) Structural observables: area per lipid, bilayer thickness, intrinsic curvature. (ii) Dynamic and mechanical properties: bending modulus (Kc), deuterium order parameter (SCD), lateral diffusion coefficient (DL), potential of mean force (PMF). (iii) Functional delivery outcomes: endosomal escape efficiency, RNA encapsulation, PEG shedding kinetics, cytosolic cargo release. We assess various MD frameworks, including all-atom, classical coarse-grained, and machine learning-based methods, evaluating their accuracy across the scale frontier. The pH-responsive behavior of ionizable lipids is linked to curvature stress, driving transitions from lamellar to inverted hexagonal (HII) phases, crucial for endosomal escape. We also analyze how cholesterol, helper phospholipids, and PEGylated lipids modify membrane mechanics and aid in cargo release. We highlight current limitations like fixed-protonation force fields and inadequate parameterization for new ionizable lipids. Future directions include constant-pH
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BibTeX
@misc{barange2026decoding,
title = {{Decoding Membrane Biophysics for Nucleic Acid Delivery: Bridging Bilayer Simulations and Lipid Nanoparticle Functionality}},
author = {Anjana Barange and Miteshkumar Moirangthem and Santosh Kumar Meena},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008480/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008480/v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Decoding Membrane Biophysics for Nucleic Acid Delivery: Bridging Bilayer Simulations and Lipid Nanoparticle Functionality
AU - Anjana Barange
AU - Miteshkumar Moirangthem
AU - Santosh Kumar Meena
PY - 2026
DA - 2026/09/08
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008480/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008480/v1
AB - Lipid nanoparticles (LNPs) are a proven platform for delivering nucleic acids, evidenced by the approvals of patisiran and COVID-19 mRNA vaccines. However, the molecular mechanisms behind lipid organization, cargo encapsulation, and intracellular release remain partially understood. This review links molecular dynamics (MD) simulations of lipid bilayers to functional LNP systems through a three-level framework. (i) Structural observables: area per lipid, bilayer thickness, intrinsic curvature. (ii) Dynamic and mechanical properties: bending modulus (Kc), deuterium order parameter (SCD), lateral diffusion coefficient (DL), potential of mean force (PMF). (iii) Functional delivery outcomes: endosomal escape efficiency, RNA encapsulation, PEG shedding kinetics, cytosolic cargo release. We assess various MD frameworks, including all-atom, classical coarse-grained, and machine learning-based methods, evaluating their accuracy across the scale frontier. The pH-responsive behavior of ionizable lipids is linked to curvature stress, driving transitions from lamellar to inverted hexagonal (HII) phases, crucial for endosomal escape. We also analyze how cholesterol, helper phospholipids, and PEGylated lipids modify membrane mechanics and aid in cargo release. We highlight current limitations like fixed-protonation force fields and inadequate parameterization for new ionizable lipids. Future directions include constant-pH
ER -