ArticleJournal of chemical theory and computation2020
An Information-Theory-Based Approach for Optimal Model Reduction of Biomolecules.
Article in Journal of chemical theory and computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- From Quantum Mechanics to Coarse-Grained Models: Bridging the Gap toward Polymer Rational Design.Journal of chemical theory and computation · 2026Article
- Bridging Scales: Coarse-Grained Protein Models in Computational Biology.Advances in experimental medicine and biology · 2026Review
- Machine Learning Approaches in Soft Matter Molecular Simulation and Materials Characterization: Challenges and Perspectives.ChemPlusChem · 2025Article
- Information-Theoretic Analysis of Selected Water Force Fields: From Molecular Clusters to Bulk Properties.Entropy (Basel, Switzerland) · 2025Article
- Review
- A FAIR-Compliant Management Solution for Molecular Simulation Trajectories.Journal of chemical information and modeling · 2025Article
- On the emergence of machine-learning methods in bottom-up coarse-graining.Current opinion in structural biology · 2025Review
- Modeling Protein-Glycan Interactions with HADDOCK.Journal of chemical information and modeling · 2024Article
- Quality assessment and community detection methods for anonymized mobility data in the Italian Covid context.Scientific reports · 2024Article
- ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information.Communications biology · 2024Article
- OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.The journal of physical chemistry. B · 2023Article
- Machine learned coarse-grained protein force-fields: Are we there yet?Current opinion in structural biology · 2023Review
- Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics.ACS central science · 2023Article
- Bottom-up Coarse-Graining: Principles and Perspectives.Journal of chemical theory and computation · 2022Review
- Fifty years of Shannon information theory in assessing the accuracy and agreement of diagnostic tests.Medical & biological engineering & computing · 2022Review
- "Dividing and Conquering" and "Caching" in Molecular Modeling.International journal of molecular sciences · 2021Review
- A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). II. Temperature transferability and structural properties at low temperature.The Journal of chemical physics · 2021Article
- A journey through mapping space: characterising the statistical and metric properties of reduced representations of macromolecules.The European physical journal. B · 2021Article
- From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules.Frontiers in molecular biosciences · 2021Review
- A Deep Graph Network-Enhanced Sampling Approach to Efficiently Explore the Space of Reduced Representations of Proteins.Frontiers in molecular biosciences · 2021Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In theoretical modeling of a physical system, a crucial step consists of the identification of those degrees of freedom that enable a synthetic yet informative representation of it. While in some cases this selection can be carried out on the basis of intuition and experience, straightforward discrimination of the important features from the negligible ones is difficult for many complex systems, most notably heteropolymers and large biomolecules. We here present a thermodynamics-based theoretical framework to gauge the effectiveness of a given simplified representation by measuring its information content. We employ this method to identify those reduced descriptions of proteins, in terms of a subset of their atoms, that retain the largest amount of information from the original model; we show that these highly informative representations share common features that are intrinsically related to the biological properties of the proteins under examination, thereby establishing a bridge between protein structure, energetics, and function.
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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.