ArticleJournal of chemical theory and computation2023
Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models through Virtual Particles.
Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Disentangling cation-polyanion coupling reveals which anion motion dominates cation transport in solid electrolytes.Nature communications · 2026Article
- Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.Journal of chemical theory and computation · 2026Article
- Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.ArXiv · 2026Article
- Energy-Based Coarse-Graining in Molecular Dynamics: A Flow-Based Framework without Data.Journal of chemical theory and computation · 2026Article
- Development of Transferable Coarse-Grained Lipid Models with Optimized Structural and Elastic Membrane Properties.Journal of chemical theory and computation · 2025Article
- Bottom-up Coarse-Grained Models of Asymmetric Membranes.The journal of physical chemistry. B · 2025Article
- Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network.Journal of chemical theory and computation · 2025Article
- Martini 3 coarse-grained model of enzymes: Framework with validation by all-atom simulations and x-ray diffraction measurements.The Journal of chemical physics · 2025Article
- Scaling Graph Neural Networks to Large Proteins.Journal of chemical theory and computation · 2025Article
- Understanding the coarse-grained free energy landscape of phospholipids and their phase separation.Biophysical journal · 2025Article
- On the emergence of machine-learning methods in bottom-up coarse-graining.Current opinion in structural biology · 2025Review
- Prediction rigidities for data-driven chemistry.Faraday discussions · 2025Article
- Enhancing the Assembly Properties of Bottom-Up Coarse-Grained Phospholipids.Journal of chemical theory and computation · 2024Article
- Structure-Based Protein Assembly Simulations Including Various Binding Sites and Conformations.Journal of chemical information and modeling · 2024Article
- Coarse-Graining with Equivariant Neural Networks: A Path Toward Accurate and Data-Efficient Models.The journal of physical chemistry. B · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
Coarse-grained (CG) models parametrized using atomistic reference data, i.e., "bottom up" CG models, have proven useful in the study of biomolecules and other soft matter. However, the construction of highly accurate, low resolution CG models of biomolecules remains challenging. We demonstrate in this work how virtual particles, CG sites with no atomistic correspondence, can be incorporated into CG models within the context of relative entropy minimization (REM) as latent variables. The methodology presented, variational derivative relative entropy minimization (VD-REM), enables optimization of virtual particle interactions through a gradient descent algorithm aided by machine learning. We apply this methodology to the challenging case of a solvent-free CG model of a 1,2-dioleoyl-
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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.