ArticleThe Journal of chemical physics2023
Integrative generalized master equation: A method to study long-timescale biomolecular dynamics via the integrals of memory kernels.
Article in The Journal of chemical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed.
- A continuous-space analytical framework for committor functions from molecular dynamics.The Journal of chemical physics · 2026Article
- Article
- Metastable Protein-Protein Interactions as a Design Principle for PROTACs: Insights from the RIPK1-VHL System.JACS Au · 2026Article
- Nucleosome condensate and linker DNA alter chromatin folding pathways and rates.Biophysical journal · 2026Article
- A Practical Guide to Transition State Analysis in Biomolecular Simulations with TS-DAR.The journal of physical chemistry. B · 2025Article
- Memory kernel minimization-based neural networks for discovering slow collective variables of biomolecular dynamics.Nature computational science · 2025Article
- Structural Insights into the Substrate Egress Pathways Explains Specificity and Inhibition of Human Glucose Transporters (GLUT1 and GLUT9).ACS pharmacology & translational science · 2025Article
- AMUSET-TICA: A Tensor-Based Approach for Identifying Slow Collective Variables in Biomolecular Dynamics.Journal of chemical theory and computation · 2025Article
- Nonequilibrium relaxation exponentially delays the onset of quantum diffusion.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.Biochemistry · 2025Review
- Thermodynamic Interpolation: A Generative Approach to Molecular Thermodynamics and Kinetics.Journal of chemical theory and computation · 2025Article
- Markov-Type State Models to Describe Non-Markovian Dynamics.Journal of chemical theory and computation · 2025Article
- Non-Markovian Dynamic Models Identify Non-Canonical KRAS-VHL Encounter Complex Conformations for Novel PROTAC Design.JACS Au · 2024Article
- Information Bottleneck Approach for Markov Model Construction.Journal of chemical theory and computation · 2024Article
- Article
- Accurate Memory Kernel Extraction from Discretized Time-Series Data.Journal of chemical theory and computation · 2024Article
- Tutorial on how to build non-Markovian dynamic models from molecular dynamics simulations for studying protein conformational changes.The Journal of chemical physics · 2024Article
- Submillisecond Atomistic Molecular Dynamics Simulations Reveal Hydrogen Bond-Driven Diffusion of a Guest Peptide in Protein-RNA Condensate.The journal of physical chemistry. B · 2024Article
- Accurate estimates of dynamical statistics using memory.The Journal of chemical physics · 2024Article
- An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes.Journal of chemical theory and computation · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The generalized master equation (GME) provides a powerful approach to study biomolecular dynamics via non-Markovian dynamic models built from molecular dynamics (MD) simulations. Previously, we have implemented the GME, namely the quasi Markov State Model (qMSM), where we explicitly calculate the memory kernel and propagate dynamics using a discretized GME. qMSM can be constructed with much shorter MD trajectories than the MSM. However, since qMSM needs to explicitly compute the time-dependent memory kernels, it is heavily affected by the numerical fluctuations of simulation data when applied to study biomolecular conformational changes. This can lead to numerical instability of predicted long-time dynamics, greatly limiting the applicability of qMSM in complicated biomolecules. We present a new method, the Integrative GME (IGME), in which we analytically solve the GME under the condition when the memory kernels have decayed to zero. Our IGME overcomes the challenges of the qMSM by using the time integrations of memory kernels, thereby avoiding the numerical instability caused by explicit computation of time-dependent memory kernels. Using our solutions of the GME, we have developed a new approach to compute long-time dynamics based on MD simulations in a numerically stable, accurate and efficient way. To demonstrate its effectiveness, we have applied the IGME in three biomolecules: the alanine dipeptide, FIP35 WW-domain, and Taq RNA polymerase. In each system, the IGME achieves significantly smaller fluctuations for both memory kernels and long-time dynamics compared to the qMSM. We anticipate that the IGME can be widely applied to investigate biomolecular conformational changes.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.