ArticleNature communications2019
Past-future information bottleneck for sampling molecular reaction coordinate simultaneously with thermodynamics and kinetics.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
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Who cites it
71 citing papers in PubMed.
- From Enhanced Sampling to Human-Readable Representations of Protein Dynamics.Journal of chemical theory and computation · 2026Article
- Latent thermodynamic flows: unified representation learning and generative modeling of temperature-dependent behaviors from limited data.Chemical science · 2026Article
- Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications.Chemical reviews · 2026Review
- Enhanced Sampling for Efficient Learning of Coarse-Grained Machine Learning Potentials.Journal of chemical theory and computation · 2026Article
- Quantum mechanics in drug design: Progress, challenges, and future frontiers.Communicative & integrative biology · 2026Review
- Using Time Dependent Rate Analysis to Evaluate the Quality of Machine Learned Reaction Coordinates for Biasing and Computing Kinetics.The journal of physical chemistry. B · 2025Article
- More Sophisticated Is Not Always Better: A Comparison of Similarity Measures for Unsupervised Learning of Pathways in Biomolecular Simulations.The journal of physical chemistry. B · 2025Article
- MOLECULE: Molecular-dynamics and Optimized deep Learning for Entropy-regularized Classification and Uncertainty-aware Ligand Evaluation.Journal of chemical theory and computation · 2025Article
- Hierarchical AF2RAVE for Multiconformation Virtual Screening Targeting S100 CaJournal of chemical theory and computation · 2025Article
- Iterative variational learning of committor-consistent transition pathways using artificial neural networks.Nature computational science · 2025Article
- Modeling Boltzmann-weighted structural ensembles of proteins using artificial intelligence-based methods.Current opinion in structural biology · 2025Review
- Reaction Coordinates Are Optimal Channels of Energy Flow.Annual review of physical chemistry · 2025Review
- Thermodynamic Interpolation: A Generative Approach to Molecular Thermodynamics and Kinetics.Journal of chemical theory and computation · 2025Article
- Use of AI-methods over MD simulations in the sampling of conformational ensembles in IDPs.Frontiers in molecular biosciences · 2025Review
- Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning-Based Information Bottleneck.Journal of chemical theory and computation · 2024Article
- Host-Guest Binding Free Energies à la Carte: An Automated OneOPES Protocol.Journal of chemical theory and computation · 2024Article
- Article
- Expanded Functionality and Portability for the Colvars Library.The journal of physical chemistry. B · 2024Article
- Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE.eLife · 2024Article
- Generative β-hairpin design using a residue-based physicochemical property landscape.Biophysical journal · 2024Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability to rapidly learn from high-dimensional data to make reliable bets about the future is crucial in many contexts. This could be a fly avoiding predators, or the retina processing gigabytes of data to guide human actions. In this work we draw parallels between these and the efficient sampling of biomolecules with hundreds of thousands of atoms. For this we use the Predictive Information Bottleneck framework used for the first two problems, and re-formulate it for the sampling of biomolecules, especially when plagued with rare events. Our method uses a deep neural network to learn the minimally complex yet most predictive aspects of a given biomolecular trajectory. This information is used to perform iteratively biased simulations that enhance the sampling and directly obtain associated thermodynamic and kinetic information. We demonstrate the method on two test-pieces, studying processes slower than milliseconds, calculating free energies, kinetics and critical mutations.
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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.