ArticleJournal of chemical theory and computation2024
Enhancing the Assembly Properties of Bottom-Up Coarse-Grained Phospholipids.
Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Structure and Dynamics of the HIV-1 Envelope Protein on the Virion Envelope.Journal of the American Chemical Society · 2026Article
- NNP/CG-MM: Embedding of All-Atom Neural Network Potentials into a Coarse-Grained Molecular Mechanics Environment.Journal of chemical theory and computation · 2026Article
- Membrane remodeling by the collective action of caveolin-1.Nature communications · 2026Article
- The LOK C-terminus is an IBAR-like domain that facilitates membrane binding and ezrin colocalization.Biophysical journal · 2026Article
- Structure and Dynamics of the HIV-1 Envelope Protein on the Virion Envelope.bioRxiv : the preprint server for biology · 2026Article
- Structural Heterogeneity of the Membrane-Interacting Region of the HIV-1 Envelope Glycoprotein.Journal of the American Chemical Society · 2025Article
- Bottom-up Coarse-Grained Models of Asymmetric Membranes.The journal of physical chemistry. B · 2025Article
- Membrane Remodeling by the Collective Action of Caveolin-1.bioRxiv : the preprint server for biology · 2025Article
- Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network.Journal of chemical theory and computation · 2025Article
- Structural Heterogeneity of the Membrane-Interacting Region of the HIV-1 Envelope Glycoprotein.bioRxiv : the preprint server for biology · 2025Article
- MSBack: Multiscale Backmapping of Highly Coarse-Grained Proteins Using Constrained Diffusion.Journal of chemical theory and computation · 2025Article
- A Hybrid Bottom-Up and Data-Driven Machine Learning Approach for Accurate Coarse-Graining of Large Molecular Complexes.Journal of chemical theory and computation · 2025Article
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2 authors.
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Abstract
A plethora of key biological events occur at the cellular membrane where the large spatiotemporal scales necessitate dimensionality reduction or coarse-graining approaches over conventional all-atom molecular dynamics simulation. Constructing coarse-grained descriptions of membranes systematically from statistical mechanical principles has largely remained challenging due to the necessity of capturing amphipathic self-assembling behavior in coarse-grained models. We show that bottom-up coarse-grained lipid models can possess metastable morphological behavior and that this potential metastability has ramifications for accurate development and training. We in turn develop a training algorithm which evades metastability issues by linking model training to self-assembling behavior, and demonstrate its robustness via construction of solvent-free coarse-grained models of various phospholipid membranes, including lipid species such as phosphatidylcholines, phosphatidylserines, sphingolipids, and cholesterol. The resulting coarse-grained lipid models are orders of magnitude faster than their atomistic counterparts while retaining structural fidelity and constitute a promising direction for the development of coarse-grained models of realistic cell membranes.
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