ReviewJournal of proteomics2020
Experimentally-driven protein structure modeling.
Review in Journal of proteomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- CPE-Pro: A Structure-Sensitive Deep Learning Method for Protein Representation and Origin Evaluation.Interdisciplinary sciences, computational life sciences · 2026Article
- Integrating AI-Based Protein Modeling and Fragment Molecular Orbital Analysis for Structure-Based Drug Design.Methods in molecular biology (Clifton, N.J.) · 2026Article
- The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.Journal of molecular biology · 2025Review
- Accurate Protein Dynamic Conformational Ensembles: Combining AlphaFold, MD, and AmideInternational journal of molecular sciences · 2025Article
- Dynamics understanding of novel solvated drug molecules against emergingResults in chemistry · 2025Article
- Artificial Intelligence: A New Tool for Structure-Based G Protein-Coupled Receptor Drug Discovery.Biomolecules · 2025Review
- Autonomous Nucleic Acid and Protein Nanocomputing Agents Engineered to Operate in Living Cells.ACS nano · 2025Review
- Structures of Oligomeric States of Tau Protein, Amyloid-β, α-Synuclein and Prion Protein Implicated in Alzheimer's Disease, Parkinson's Disease and Prionopathies.International journal of molecular sciences · 2024Review
- CAPRI-Q: The CAPRI resource evaluating the quality of predicted structures of protein complexes.Journal of molecular biology · 2024Article
- Local Disordered Region Sampling (LDRS) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments.Bioinformatics (Oxford, England) · 2023Article
- Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments.bioRxiv : the preprint server for biology · 2023Article
- Structural and dynamic insights into α-synuclein dimer conformations.Structure (London, England : 1993) · 2023Article
- Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology.Biomolecules · 2023Review
- Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma.Biophysics reviews · 2022Review
- Review
- Integrative structural dynamics probing of the conformational heterogeneity in synaptosomal-associated protein 25.Cell reports. Physical science · 2021Article
- Structure of prion β-oligomers as determined by short-distance crosslinking constraint-guided discrete molecular dynamics simulations.Proteomics · 2021Article
- The structural heterogeneity of α-synuclein is governed by several distinct subpopulations with interconversion times slower than milliseconds.Structure (London, England : 1993) · 2021Article
- Dystrophin gene editing by CRISPR/Cas9 system in human skeletal muscle cell line (HSkMC).Iranian journal of basic medical sciences · 2021Article
- Titr-DMD-A Rapid, Coarse-Grained Quasi-All-Atom Constant pH Molecular Dynamics Framework.Journal of chemical theory and computation · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.
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.