Lipid nanoparticles (LNPs) are essential for RNA delivery and play a crucial role in gene therapy and vaccine development. Despite their success, low endosomal escape efficiency remains a major bottleneck, the molecular origin of which is still poorly understood. Molecular dynamics and coarse-grained simulations are powerful tools for investigating the dynamic structural changes occurring during endosomal maturation, as well as the pathways of fusion with the endosomal membrane and RNA release. As a result, simulations have become increasingly valuable for resolving fundamental biophysical processes in ionizable lipid model systems and for the rational design of LNPs. To achieve reliable and predictive simulations of lipid systems, we systematically optimize lipid models based on comprehensive experimental data (1, 2, 3).

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Recently, we performed simulations and experiments in collaboration with J. R?dler from LMU on LNP core phases comprising the ionizable lipid MC3, cholesterol, and water. These studies revealed an inverse micellar phase at high pH and an inverse hexagonal phase at low pH, with quantitative agreement between scattering profiles obtained from simulations and experiments (Fig. 1). Moreover, the combined approach using scattering, simulation, and in-vivo experiments demonstrated that phase transitions to inverse hexagonal phases enhance fusogenic activity (1). Continuing this work, we recently investigated ion-specific effects on LNP efficiency. Notably, citrate ions were found to be more effective at inducing phase transitions to inverse micellar phases. Consequently, LNPs prepared in citrate buffers exhibited higher transfection efficiencies compared to those formulated in phosphate or acetate buffers (4).

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Figure 1: pH-dependent phase transitions are crucial for the delivery efficiency of LNPs. (A) Inverse micellar and inverse hexagonal phase (B) from simulation of LNP core phases at high and low pH. MC3 lipids are shown in green, protonated MC3 headgroups are shown in red, cholesterol in yellow and water in cyan. With decreasing pH, the MC3 headgroups get protonated and enter the water phase. This induces a structural phase transition from the inverse micellar to the hexago nal phase. (C) Direct comparison of the scattering profiles for the inverse hexagonal phase from experiments and simulations.

Publications

1. J. Philipp, A. Dabkowska, A. Reiser, K. Frank, R. Krzyszton, C. Brummer, B. Nickel, C.E. Blanchet, A. Sudarsan, M .Ibrahim, S. Johansson, P. Skantze, U. Skantze, S. O. ?stman, M. Johansson, N. Henderson, K. Elvevold, B. Smedsr?d, N. Schwierz, L. Lindfors and J. O. R?dler. pH-dependent structural transitions in cationic ionizable lipid mesophases are critical for lipid nanoparticle function, Proc. Natl. Acad. Sci. USA, 120(50):e2310491120, 2023. https://doi.org/10.1073/pnas.2310491120
2. M. Ibrahim, J. Gilbert, M. Heinz, T. Nylander and N. Schwierz. Structural Insights on Ionizable Dlin-MC3-DMA Lipids in DOPC Layers by Combining Accurate Atomistic Force Fields, Molecular Dynamics Simulations and Neutron Reflectivity, Nanoscale, 15, 11647-11656, 2023. https://doi.org/10.1039/D3NR00987D
3. M. Grava, M.; Ibrahim, A. Sudarsan, J. Pusterla, J. O. R?dler, N. Schwierz, E. Schneck. Combining Molecular Dynamics Simulations and X-Ray Scattering Techniques for the Accurate Treatment of Protonation Degree and Packing of Ionizable Lipids in Monolayers. J. Chem. Phys., 159(15):154706, 2023, https://doi.org/10.1101/2023.08.10.552652
4. C. Carucci, J. Philipp, J. A. Müler, A. Sudarsan, E. Kostyurina, C. E. Blanchet, N. Schwierz, D. F. Parsons, A. Salis, J. O. R?dler. Buffer specificity of ionizable lipid nanoparticle transfection efficiency and bulk phase transition. ACS Nano, 19, 11, 10829–10840 2025. https://doi.org/10.1021/acsnano.4c14098

Amyloidosis comprises a group of severe protein misfolding diseases characterized by the accumulation of insoluble amyloid fibrils in tissues and organs, ultimately leading to dysfunction and failure. Among the most well-known forms is Alzheimer’s disease, which results from the aggregation of amyloid-beta peptides in the brain, causing progressive neurodegeneration (1, 2). Other forms, such as systemic amyloidosis, involve the deposition of misfolded proteins in multiple organs, leading to severe complications. Despite their clinical significance, the molecular mechanisms underlying protein misfolding and amyloid formation remain poorly understood, and no pharmacological treatments currently exist. The primary objective of our research is to identify the structural and sequence-specific factors that drive misfolding and fibril formation (2-4). In recent work, we focus on amyloid light chain amyloidosis, a rare but often fatal disease. Our work aims to develop a systematic computational approach to resolve the factors that trigger misfolding and the onset of this fatal disease.

In close collaboration with M. F?ndrich from University Ulm, B. Reif and J. Buchner from TUM, we combine MD simulations, cryo-EM, nuclear magnetic resonance and fibril assays to systematically investigate the impact of the pathological point mutations and post-translational modifications on amyloid formation.