ArticleProceedings of the National Academy of Sciences of the United States of America2021
Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes.
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 8 papers.
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8 citing papers in PubMed, 26 citations in OpenAlex.
- The Spectral Rrepresentation of a Discrete Version of Blackwell's Markov Chain.Entropy (Basel, Switzerland) · 2026Article
- Review
- Integrative spatiotemporal modeling of biomolecular processes: Application to the assembly of the nuclear pore complex.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Integrative spatiotemporal modeling of biomolecular processes: application to the assembly of the Nuclear Pore Complex.bioRxiv : the preprint server for biology · 2024Article
- Conformational exchange divergence along the evolutionary pathway of eosinophil-associated ribonucleases.Structure (London, England : 1993) · 2023Article
- Deep learning to decompose macromolecules into independent Markovian domains.Nature communications · 2022Article
- Is There a Need for a More Precise Description of Biomolecule Interactions to Understand Cell Function?Current issues in molecular biology · 2022Review
- Unifying Single-Channel Permeability From Rare-Event Sampling and Steady-State Flux.Frontiers in molecular biosciences · 2022Article
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
To advance the mission of in silico cell biology, modeling the interactions of large and complex biological systems becomes increasingly relevant. The combination of molecular dynamics (MD) simulations and Markov state models (MSMs) has enabled the construction of simplified models of molecular kinetics on long timescales. Despite its success, this approach is inherently limited by the size of the molecular system. With increasing size of macromolecular complexes, the number of independent or weakly coupled subsystems increases, and the number of global system states increases exponentially, making the sampling of all distinct global states unfeasible. In this work, we present a technique called independent Markov decomposition (IMD) that leverages weak coupling between subsystems to compute a global kinetic model without requiring the sampling of all combinatorial states of subsystems. We give a theoretical basis for IMD and propose an approach for finding and validating such a decomposition. Using empirical few-state MSMs of ion channel models that are well established in electrophysiology, we demonstrate that IMD models can reproduce experimental conductance measurements with a major reduction in sampling compared with a standard MSM approach. We further show how to find the optimal partition of all-atom protein simulations into weakly coupled subunits.
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