ArticleThe Journal of chemical physics2021
A critical perspective on Markov state model treatments of protein-protein association using coarse-grained simulations.
Article in The Journal of chemical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Highly Optimized Simulation of Atomic Resolution Cell-Like Protein Environment.The journal of physical chemistry. B · 2025Article
- Toward Grid-Based Models for Molecular Association.Journal of chemical theory and computation · 2025Article
- The Adsorption of P2X2 Receptors Interacting with IgG Antibodies Revealed by Combined AFM Imaging and Mechanical Simulation.International journal of molecular sciences · 2023Article
- Perspectives on Ligand/Protein Binding Kinetics Simulations: Force Fields, Machine Learning, Sampling, and User-Friendliness.Journal of chemical theory and computation · 2023Review
- Uncertainties in Markov State Models of Small Proteins.Journal of chemical theory and computation · 2023Article
- Predicting Biomolecular Binding Kinetics: A Review.Journal of chemical theory and computation · 2023Review
- Continuous millisecond conformational cycle of a DEAH box helicase reveals control of domain motions by atomic-scale transitions.Communications biology · 2023Article
- Committor-Consistent Variational String Method.The journal of physical chemistry letters · 2022Article
- Docking-based long timescale simulation of cell-size protein systems at atomic resolution.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Bottom-up Coarse-Graining: Principles and Perspectives.Journal of chemical theory and computation · 2022Review
- Protein-Protein Interaction-Gaussian Accelerated Molecular Dynamics (PPI-GaMD): Characterization of Protein Binding Thermodynamics and Kinetics.Journal of chemical theory and computation · 2022Article
- Challenges and frontiers of computational modelling of biomolecular recognition.QRB discovery · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
Atomic-level information is essential to explain the specific interactions governing protein-protein recognition in terms of structure and dynamics. Of particular interest is a characterization of the time-dependent kinetic aspects of protein-protein association and dissociation. A powerful framework to characterize the dynamics of complex molecular systems is provided by Markov State Models (MSMs). The central idea is to construct a reduced stochastic model of the full system by defining a set of conformational featured microstates and determining the matrix of transition probabilities between them. While a MSM framework can sometimes be very effective, different combinations of input featurization and simulation methods can significantly affect the robustness and the quality of the information generated from MSMs in the context of protein association. Here, a systematic examination of a variety of MSMs methodologies is undertaken to clarify these issues. To circumvent the uncertainties caused by sampling issues, we use a simplified coarse-grained model of the barnase-barstar protein complex. A sensitivity analysis is proposed to identify the microstates of an MSM that contribute most to the error in conjunction with the transition-based reweighting analysis method for a more efficient and accurate MSM construction.
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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.