ArticleJournal of chemical theory and computation2021
Time-Lagged Independent Component Analysis of Random Walks and Protein Dynamics.
Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Identification of Natural Flavonoids Targeting PLK-1 as Potential Anti-Metastatic Agents: A Computational Approach.International journal of molecular sciences · 2026Article
- AI-Physics-Experiment Trinity for Integrated Protein Dynamics Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Elucidating the Structure and Activation Mechanisms of GPCRs Using Modern Computational and AI Tools.Cell biochemistry and biophysics · 2026Review
- Solvent Environment Influences Molecular Conformation and Electron Transport in Peptides.The journal of physical chemistry letters · 2026Article
- Unveiling hidden intermediate states in protein folding with AI-based conditional transition clustering.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Article
- Comparing cryo-EM methods and molecular dynamics simulation to investigate heterogeneity in ligand-bound TRPV1.Nature communications · 2025Article
- Artificial intelligence in protein-based detection and inhibition of AMR pathways.Journal of computer-aided molecular design · 2025Review
- Mechanistic basis for the opposing effects of H2A and H2B ubiquitination on nucleosome stability and dynamics.Epigenetics & chromatin · 2025Article
- High-Throughput Computation of Anharmonic Low-Frequency Protein Vibrations.The journal of physical chemistry. B · 2025Article
- Unbiased Enhanced Sampling in Molecular Dynamics via Simultaneously Accelerating Diffusion in Multiple Low-Dimensional Collective Variable Spaces.Journal of chemical theory and computation · 2025Article
- Coupling causality and interpretable machine learning to reveal the reaction coordinate of C-N coupling with a supramolecular Cu-calix[8]arene catalyst.Digital discovery · 2025Article
- Synthesis and Computational Evaluation ofACS omega · 2025Article
- Robustness in biomolecular simulations: Addressing challenges in data generation, analysis, and curation.Cell reports. Physical science · 2025Article
- A beginner's approach to deep learning applied to VS and MD techniques.Journal of cheminformatics · 2025Review
- Cardaria draba subspecies Shalepensis exerts in vitro and in silico inhibition of α-glucosidase, TRP1, and DLD-1 proliferation.Scientific reports · 2025Article
- Increasing the Efficiency of Ensemble Molecular Dynamics Simulations with Termination of Unproductive Trajectories Identified at Runtime.The journal of physical chemistry. A · 2025Article
- Systematic analysis of biomolecular conformational ensembles with PENSA.The Journal of chemical physics · 2025Article
- Kinetics-Based State Definitions for Discrete Binding Conformations of T4 L99A in MD via Markov State Modeling.Journal of chemical information and modeling · 2024Article
- Automated collective variable discovery for MFSD2A transporter from molecular dynamics simulations.Biophysical journal · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Time-lagged independent component analysis (tICA) is a widely used dimension reduction method for the analysis of molecular dynamics (MD) trajectories and has proven particularly useful for the construction of protein dynamics Markov models. It identifies those "slow" collective degrees of freedom onto which the projections of a given trajectory show maximal autocorrelation for a given lag time. Here we ask how much information on the actual protein dynamics and, in particular, the free energy landscape that governs these dynamics the tICA-projections of MD-trajectories contain, as opposed to noise due to the inherently stochastic nature of each trajectory. To answer this question, we have analyzed the tICA-projections of high dimensional random walks using a combination of analytical and numerical methods. We find that the projections resemble cosine functions and strongly depend on the lag time, exhibiting strikingly complex behavior. In particular, and contrary to previous studies of principal component projections, the projections change noncontinuously with increasing lag time. The tICA-projections of selected 1 μs protein trajectories and those of random walks are strikingly similar, particularly for larger proteins, suggesting that these trajectories contain only little information on the energy landscape that governs the actual protein dynamics. Further the tICA-projections of random walks show clusters very similar to those observed for the protein trajectories, suggesting that clusters in the tICA-projections of protein trajectories do not necessarily reflect local minima in the free energy landscape. We also conclude that, in addition to the previous finding that certain ensemble properties of nonconverged protein trajectories resemble those of random walks; this is also true for their time correlations.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.