ArticleJournal of chemical theory and computation2019
Systematic Coarse-Grained Lipid Force Fields with Semiexplicit Solvation via Virtual Sites.
Article in Journal of chemical theory and computation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Collective fluctuations underlying nanobody inhibitory activity targetingbioRxiv : the preprint server for biology · 2026Article
- The LOK C-terminus is an IBAR-like domain that facilitates membrane binding and ezrin colocalization.Biophysical journal · 2026Article
- Probabilistic Forecasting for Coarse-Grained Molecular Dynamics.Journal of chemical theory and computation · 2026Article
- Optimizing a coarse-grained model for large-scale membrane protein simulation.Biophysical reports · 2025Article
- Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network.Journal of chemical theory and computation · 2025Article
- Adversarial training for dynamics matching in coarse-grained models.The Journal of chemical physics · 2025Article
- Voacangine targeting of PI3K/Akt/ERK via the knockdown of inflammation in DEN-induced liver cancer: in vivo and in silico approach.Journal of molecular histology · 2025Article
- MSBack: Multiscale Backmapping of Highly Coarse-Grained Proteins Using Constrained Diffusion.Journal of chemical theory and computation · 2025Article
- Understanding the coarse-grained free energy landscape of phospholipids and their phase separation.Biophysical journal · 2025Article
- Enhancing the Assembly Properties of Bottom-Up Coarse-Grained Phospholipids.Journal of chemical theory and computation · 2024Article
- Computational Prediction of Coiled-Coil Protein Gelation Dynamics and Structure.Biomacromolecules · 2024Article
- OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.The journal of physical chemistry. B · 2023Article
- Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models through Virtual Particles.Journal of chemical theory and computation · 2023Article
- Mesoscale simulations: An indispensable approach to understand biomembranes.Biophysical journal · 2023Review
- Cholesterol and M2 Rendezvous in Budding and Scission of Influenza A Virus.Sub-cellular biochemistry · 2023Article
- A Core-Shell Approach for Systematically Coarsening Nanoparticle-Membrane Interactions: Application to Silver Nanoparticles.Nanomaterials (Basel, Switzerland) · 2022Article
- Bottom-up Coarse-Graining: Principles and Perspectives.Journal of chemical theory and computation · 2022Review
- Physical Characterization of Triolein and Implications for Its Role in Lipid Droplet Biogenesis.The journal of physical chemistry. B · 2021Article
- A multiscale coarse-grained model of the SARS-CoV-2 virion.Biophysical journal · 2021Article
- A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). I. General theory and model.The Journal of chemical physics · 2021Article
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Authors and funding
4 authors.
Funding
Abstract
Despite the central role of lipids in many biophysical functions, the molecular mechanisms that dictate macroscopic lipid behavior remain elusive to both experimental and computational approaches. As such, there has been much interest in the development of low-resolution, implicit-solvent coarse-grained (CG) models to dynamically simulate biologically relevant spatiotemporal scales with molecular fidelity. However, in the absence of solvent, a key challenge for CG models is to faithfully emulate solvent-mediated forces, which include both hydrophilic and hydrophobic interactions that drive lipid aggregation and self-assembly. In this work, we provide a new methodological framework to incorporate semiexplicit solvent effects through the use of virtual CG particles, which represent structural features of the solvent-lipid interface. To do so, we leverage two systematic coarse-graining approaches, multiscale coarse-graining (MS-CG) and relative entropy minimization (REM), in a hybrid fashion to construct our virtual-site CG (VCG) models. As a proof-of-concept, we focus our efforts on two lipid species, 1,2-dioleoyl- sn-glycero-3-phosphocholine (DOPC) and 1,2-dipalmitoyl- sn-glycero-3-phosphocholine (DPPC), which adopt a liquid-disordered and gel phase, respectively, at room temperature. Through our analysis, we also present, to our knowledge, the first direct comparison between the MS-CG and REM methods for a complex biomolecule and highlight each of their strengths and weaknesses. We further demonstrate that VCG models recapitulate the rich biophysics of lipids, which enable self-assembly, morphological diversity, and multiple phases. Our findings suggest that the VCG framework is a powerful approach for investigation into macromolecular biophysics.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.