Martini 3 Building Blocks for Lipid Nanoparticle Design

Welcome to the repository for Martini 3 ionizable lipid parameters and protocols tailored for the design and simulation of Lipid Nanoparticles (LNPs). These resources are designed to facilitate molecular dynamics simulations, enabling deeper insights into LNP formulation and function, particularly for pharmaceutical applications such as mRNA delivery.

What’s Included

This repository provides:

1. Ionizable Lipid Parameters:

   • Access the Lipid_parameters folder for ready-to-use Martini 3 parameters for:
     • Literature known Ionizable Lipids - Lipid_parameters > Literature_known_lipids;
     • Pre-built Ionizable Lipids - Lipid_parameters > Ionizable_lipid_library;
     • Ionizable Lipid Fragments - Lipid_parameters > Fragments.
   • Detailed descriptions on how to generate new lipid itps are provided in Lipid_parameters > Scripts.

2. Case Studies and Protocols:

   • Explore the Case_studies folder to obtain the protocols that guide you through:
     • Building Lipid Nanoparticles - Case_studies > Lipid_Nanoparticle_construction
     • Quantifying stalk formation - Case_studies > Quantifying_stalk_formation
     • Simulating Unbiased Fusion - Case_studies > Unbiased_Fusion

Citations

If you use the parameters/protocols from this repository, please cite the following publication:
Kjølbye, L. R., Valério, M., Paloncýová, M., Borges-Araújo, L., Pestana-Nobles, R., Grünewald, F., ... & Souza, P. C. (2024). Martini 3 building blocks for Lipid Nanoparticle design.

Please also cite the following packages/publications:

Protocol	Powered by
Inverse Hexagonal core LNP	MDAnalysis; Packmol; TS2CG; freud; mdvwhole; mdvcontainment
"Bleb" LNP	MDAnalysis; Packmol; TS2CG; freud; mdvwhole
Stalk Free Energy	Gromacs-chain-coordinate; insane.py; GROMACS