ReviewAnnual review of analytical chemistry (Palo Alto, Calif.)2012
Computational models of protein kinematics and dynamics: beyond simulation.
Review in Annual review of analytical chemistry (Palo Alto, Calif.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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Who cites it
14 citing papers in PubMed.
- FoldDoF: Utilizing the Primary Degrees of Freedom of Protein Backbone for Geometric Modeling and Generation.Journal of chemical information and modeling · 2026Article
- MutPPI+: a multimodal framework for predicting mutation effects on protein-protein interactions via mutation-path-based data augmentation.Briefings in bioinformatics · 2026Article
- Probing the local conformational flexibility in receptor recognition: mechanistic insight from an atomic-scale investigation.RSC advances · 2019Article
- Investigating the Formation of Structural Elements in Proteins Using Local Sequence-Dependent Information and a Heuristic Search Algorithm.Molecules (Basel, Switzerland) · 2019Article
- Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data.International journal of molecular sciences · 2018Article
- Segmenting Proteins into Tripeptides to Enhance Conformational Sampling with Monte Carlo Methods.Molecules (Basel, Switzerland) · 2018Article
- Native State of Complement Protein C3d Analysed via Hydrogen Exchange and Conformational Sampling.International journal of computational biology and drug design · 2018Article
- Theoretical framework for analyzing structural compliance properties of proteins.Biophysics and physicobiology · 2018Article
- Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods.Journal of computational biology : a journal of computational molecular cell biology · 2018Article
- Coarse-Grained Conformational Sampling of Protein Structure Improves the Fit to Experimental Hydrogen-Exchange Data.Frontiers in molecular biosciences · 2017Article
- Crystallographic model validation: from diagnosis to healing.Current opinion in structural biology · 2013Review
- MoMA-LigPath: a web server to simulate protein-ligand unbinding.Nucleic acids research · 2013Article
- SIMS: a hybrid method for rapid conformational analysis.PloS one · 2013Article
- Article
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
Physics-based simulation represents a powerful method for investigating the time-varying behavior of dynamic protein systems at high spatial and temporal resolution. Such simulations, however, can be prohibitively difficult or lengthy for large proteins or when probing the lower-resolution, long-timescale behaviors of proteins generally. Importantly, not all questions about a protein system require full space and time resolution to produce an informative answer. For instance, by avoiding the simulation of uncorrelated, high-frequency atomic movements, a larger, domain-level picture of protein dynamics can be revealed. The purpose of this review is to highlight the growing body of complementary work that goes beyond simulation. In particular, this review focuses on methods that address kinematics and dynamics, as well as those that address larger organizational questions and can quickly yield useful information about the long-timescale behavior of a protein.
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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.