ArticleProceedings of the National Academy of Sciences of the United States of America2021
A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
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- Frontier advances in molecular dynamics simulations for the design and optimization of oil-displacement polymers.RSC advances · 2025Review
- Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy.Biochemistry · 2023Article
- Machine learning and protein allostery.Trends in biochemical sciences · 2023Review
- Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches.Journal of chemical information and modeling · 2023Review
- NMR Studies of Aromatic Ring Flips to Probe Conformational Fluctuations in Proteins.The journal of physical chemistry. B · 2023Review
- Sample Preparation for Time-Resolved Serial Crystallography: Practical Considerations.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Path sampling of recurrent neural networks by incorporating known physics.Nature communications · 2022Article
- Information theory: A foundation for complexity science.Proceedings of the National Academy of Sciences of the United States of America · 2022Review
- Correlation between the binding affinity and the conformational entropy of nanobody SARS-CoV-2 spike protein complexes.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Best practices for time-resolved serial synchrotron crystallography.Acta crystallographica. Section D, Structural biology · 2022Review
- Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures.The journal of physical chemistry. B · 2021Article
- Determination of intermediate state structures in the opening pathway of SARS-CoV-2 spike using cryo-electron microscopy.Chemical science · 2021Article
- Recent Developments in Data-Assisted Modeling of Flexible Proteins.Frontiers in molecular biosciences · 2021Review
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Abstract
From the point of view of statistical mechanics, a full characterization of a molecular system requires an accurate determination of its possible states, their populations, and the respective interconversion rates. Toward this goal, well-established methods increase the accuracy of molecular dynamics simulations by incorporating experimental information about states using structural restraints and about populations using thermodynamics restraints. However, it is still unclear how to include experimental knowledge about interconversion rates. Here, we introduce a method of imposing known rate constants as constraints in molecular dynamics simulations, which is based on a combination of the maximum-entropy and maximum-caliber principles. Starting from an existing ensemble of trajectories, obtained from either molecular dynamics or enhanced trajectory sampling, this method provides a minimally perturbed path distribution consistent with the kinetic constraints, as well as modified free energy and committor landscapes. We illustrate the application of the method to a series of model systems, including all-atom molecular simulations of protein folding. Our results show that by combining experimental rate constants and molecular dynamics simulations, this approach enables the determination of transition states, reaction mechanisms, and free energies. We anticipate that this method will extend the applicability of molecular simulations to kinetic studies in structural biology and that it will assist the development of force fields to reproduce kinetic and thermodynamic observables. Furthermore, this approach is generally applicable to a wide range of systems in biology, physics, chemistry, and material science.
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