ArticleJournal of chemical theory and computation2013
AUTOMATED FORCE FIELD PARAMETERIZATION FOR NON-POLARIZABLE AND POLARIZABLE ATOMIC MODELS BASED ON
Article in Journal of chemical theory and computation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
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Who cites it
107 citing papers in PubMed.
- A Graph-Based Machine Learning Framework to Assign Empirical Interaction Parameters for Novel Molecules.Journal of computational chemistry · 2026Article
- Developing Efficient and Accurate Polarizable Molecular Simulation Models for Studying Refrigerants and Their Binary Mixtures.The journal of physical chemistry. B · 2026Article
- Fast Fourier Transform Enables Automated Parametrization of Complex Dihedral Potentials in All-Atom and Coarse-Grained Force Fields.Journal of chemical information and modeling · 2026Article
- Predicting Properties of Cyclohexene with Electronic Structure Methods through Adaptive Force Matching.The journal of physical chemistry. C, Nanomaterials and interfaces · 2026Article
- Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy Calculations.Journal of chemical theory and computation · 2026Article
- Automated Force Field Developer and Optimizer Platform: Torsion Reparameterization.Journal of chemical information and modeling · 2026Article
- A fluorescent probe under the microscope showing dual recognition of B-DNA and G-quadruplex DNA.Communications chemistry · 2026Article
- On the Energy Contributions Driving Pyridine Adsorption on Silver and Gold Nanoparticles.Nanomaterials (Basel, Switzerland) · 2025Article
- Thermodynamics of arginine interactions with organic phosphates.Biophysical journal · 2025Article
- Increasing the Accuracy and Robustness of the CHARMM General Force Field with an Expanded Training Set.Journal of chemical theory and computation · 2025Article
- Aryl benzoyl hydrazide derivatives as potent inhibitors of the NS2B-NS3 protease and RNA-dependent RNA polymerase of the zika virus.In silico pharmacology · 2025Article
- Paritaprevir as a pan-antiviral against different flaviviruses.Frontiers in molecular biosciences · 2025Article
- An α-ketoglutarate conformational switch controls iron accessibility, activation, and substrate selection of the human FTO protein.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- FFParam-v2.0: A Comprehensive Tool for CHARMM Additive and Drude Polarizable Force-Field Parameter Optimization and Validation.The journal of physical chemistry. B · 2024Article
- Simulating the Fluorescence of the Locally Excited State of DMABN in Solvents of Different Polarities.The journal of physical chemistry. B · 2024Article
- Simulating the Fluorescence of Di-8-ANEPPS in Solvents of Different Polarity.The journal of physical chemistry. B · 2024Article
- Simulating the Voltage-Dependent Fluorescence of Di-8-ANEPPS in a Lipid Membrane.The journal of physical chemistry letters · 2023Article
- Accurate and Efficient Multilevel Free Energy Simulations with Neural Network-Assisted Enhanced Sampling.Journal of chemical theory and computation · 2023Article
- OFraMP: a fragment-based tool to facilitate the parametrization of large molecules.Journal of computer-aided molecular design · 2023Article
- A fluorinated cation introduces new interphasial chemistries to enable high-voltage lithium metal batteries.Nature communications · 2023Article
47 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
Classical molecular dynamics (MD) simulations based on atomistic models are increasingly used to study a wide range of biological systems. A prerequisite for meaningful results from such simulations is an accurate molecular mechanical force field. Most biomolecular simulations are currently based on the widely used AMBER and CHARMM force fields, which were parameterized and optimized to cover a small set of basic compounds corresponding to the natural amino acids and nucleic acid bases. Atomic models of additional compounds are commonly generated by analogy to the parameter set of a given force field. While this procedure yields models that are internally consistent, the accuracy of the resulting models can be limited. In this work, we propose a method, General Automated Atomic Model Parameterization (GAAMP), for generating automatically the parameters of atomic models of small molecules using the results from
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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.