ArticleThe journal of physical chemistry. A2024
EspalomaCharge: Machine Learning-Enabled Ultrafast Partial Charge Assignment.
Article in The journal of physical chemistry. A, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.Journal of chemical theory and computation · 2026Article
- Developing and Benchmarking Sage 2.3.0 with the AshGC Neural Network Charge Model.Journal of chemical theory and computation · 2026Article
- Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy Calculations.Journal of chemical theory and computation · 2026Article
- Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.ArXiv · 2026Article
- A Quadrupolar Fullerene Model System for Benchmarking Enhanced Sampling of Trapped Waters in Free Energy Calculations.The journal of physical chemistry. B · 2026Article
- A Graph Neural Network Charge Model Targeting Accurate Electrostatic Properties of Organic Molecules.Journal of chemical theory and computation · 2025Article
- Atomistic Polymer Modeling: Recent Advances and Challenges in Building and Parametrization Workflows.Macromolecules · 2025Review
- Polarizable Water Model with Ab Initio Neural Network Dynamic Charges and Spontaneous Charge Transfer.Journal of chemical theory and computation · 2025Article
- ABCG2: A Milestone Charge Model for Accurate Solvation Free Energy Calculation.Journal of chemical theory and computation · 2025Article
- Scaling Graph Neural Networks to Large Proteins.Journal of chemical theory and computation · 2025Article
- Fine-tuning molecular mechanics force fields to experimental free energy measurements.bioRxiv : the preprint server for biology · 2025Article
- Validating Small-Molecule Force Fields for Macrocyclic Compounds Using NMR Data in Different Solvents.Journal of chemical information and modeling · 2024Article
- QupKake: Integrating Machine Learning and Quantum Chemistry for Micro-pJournal of chemical theory and computation · 2024Article
- The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.The journal of physical chemistry. B · 2024Article
- Parameterization of General Organic Polymers within the Open Force Field Framework.Journal of chemical information and modeling · 2024Article
- DASH: Dynamic Attention-Based Substructure Hierarchy for Partial Charge Assignment.Journal of chemical information and modeling · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Atomic partial charges are crucial parameters in molecular dynamics simulation, dictating the electrostatic contributions to intermolecular energies and thereby the potential energy landscape. Traditionally, the assignment of partial charges has relied on surrogates of ab initio semiempirical quantum chemical methods such as AM1-BCC and is expensive for large systems or large numbers of molecules. We propose a hybrid physical/graph neural network-based approximation to the widely popular AM1-BCC charge model that is orders of magnitude faster while maintaining accuracy comparable to differences in AM1-BCC implementations. Our hybrid approach couples a graph neural network to a streamlined charge equilibration approach in order to predict molecule-specific atomic electronegativity and hardness parameters, followed by analytical determination of optimal charge-equilibrated parameters that preserve total molecular charge. This hybrid approach scales linearly with the number of atoms, enabling for the first time the use of fully consistent charge models for small molecules and biopolymers for the construction of next-generation self-consistent biomolecular force fields. Implemented in the free and open source package EspalomaCharge, this approach provides drop-in replacements for both AmberTools antechamber and the Open Force Field Toolkit charging workflows, in addition to stand-alone charge generation interfaces. Source code is available at https://github.com/choderalab/espaloma-charge.
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Registered trials
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.