Dataset Information

CHARMM-GUI PACE CG Builder for solution, micelle, and bilayer coarse-grained simulations.

ABSTRACT: Coarse-grained (CG) and multiscale simulations are widely used to study large biological systems. However, preparing the simulation system is time-consuming when the system has multiple components, because each component must be arranged carefully as in protein/micelle or protein/bilayer systems. We have developed CHARMM-GUI PACE CG Builder for building solution, micelle, and bilayer systems using the PACE force field, a united-atom (UA) model for proteins, and the Martini CG force field for water, ions, and lipids. The robustness of PACE CG Builder is validated by simulations of various systems in solution (?3D, fibronectin, and lysozyme), micelles (Pf1, DAP12-NKG2C, OmpA, and DHPC-only micelle), and bilayers (GpA, OmpA, VDAC, MscL, OmpF, and lipid-only bilayers for six lipids). The micelle's radius of gyration, the bilayer thickness, and the per-lipid area in bilayers are comparable to the values from previous all-atom and CG simulations. Most tested proteins have root-mean squared deviations of less than 3 Å. We expect PACE CG Builder to be a useful tool for modeling/refining large, complex biological systems at the mixed UA/CG level.

SUBMITTER: Qi Y

PROVIDER: S-EPMC3985889 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Publications

CHARMM-GUI PACE CG Builder for solution, micelle, and bilayer coarse-grained simulations.

Qi Yifei Y Cheng Xi X Han Wei W Jo Sunhwan S Schulten Klaus K Im Wonpil W

Journal of chemical information and modeling 20140313 3

Coarse-grained (CG) and multiscale simulations are widely used to study large biological systems. However, preparing the simulation system is time-consuming when the system has multiple components, because each component must be arranged carefully as in protein/micelle or protein/bilayer systems. We have developed CHARMM-GUI PACE CG Builder for building solution, micelle, and bilayer systems using the PACE force field, a united-atom (UA) model for proteins, and the Martini CG force field for wat ...[more]

PMID: 24624945

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Project description:A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, mRNA, and siRNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes a rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder â€™s capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol% PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus ( KA ) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for a rational LNP design.

Project description:A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, messenger RNA, and small interfering RNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies, albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder's capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol % PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus (KA) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and the head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for rational LNP design.

Dataset Information

CHARMM-GUI PACE CG Builder for solution, micelle, and bilayer coarse-grained simulations.

Publications

CHARMM-GUI PACE CG Builder for solution, micelle, and bilayer coarse-grained simulations.

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