ArticleProceedings of the National Academy of Sciences of the United States of America2018
Protein homology model refinement by large-scale energy optimization.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed.
- To pack or not to pack: revisiting protein side-chain packing in the post-AlphaFold era.Briefings in bioinformatics · 2025Article
- Design of High Affinity Binders to Convex Protein Target Sites.bioRxiv : the preprint server for biology · 2024Article
- Modeling of protein conformational changes with Rosetta guided by limited experimental data.Structure (London, England : 1993) · 2022Article
- Comparative molecular docking and molecular-dynamic simulation of wild-type- and mutant carboxylesterase with BTA-hydrolase for enhanced binding to plastic.Engineering in life sciences · 2022Article
- Article
- Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.Proteins · 2021Article
- Article
- Article
- Design and Prototyping of Genetically Encoded Arsenic Biosensors Based on Transcriptional Regulator AfArsR.Biomolecules · 2021Article
- Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation.Journal of chemical theory and computation · 2021Article
- Improved protein structure refinement guided by deep learning based accuracy estimation.Nature communications · 2021Article
- Computational Prediction of Chemical Tools for Identification and Validation of Synthetic Lethal Interaction Networks.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Computer Modeling of N-Acetylglutamate Synthase: From Primary Structure to Elemental Stages of Catalysis.Doklady. Biochemistry and biophysics · 2020Article
- Deep learning enables the atomic structure determination of the Fanconi Anemia core complex from cryoEM.IUCrJ · 2020Article
- Article
- Comparative modeling and docking of chemokine-receptor interactions with Rosetta.Biochemical and biophysical research communications · 2020Article
- Macromolecular modeling and design in Rosetta: recent methods and frameworks.Nature methods · 2020Review
- Structure determination of the HgcAB complex using metagenome sequence data: insights into microbial mercury methylation.Communications biology · 2020Article
- Comparative modelling studies of fruit bromelain using molecular dynamics simulation.Journal of molecular modeling · 2020Article
- Structural basis of ER-associated protein degradation mediated by the Hrd1 ubiquitin ligase complex.Science (New York, N.Y.) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.
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.