ArticleJournal of computational chemistry2017
Residue-centric modeling and design of saccharide and glycoconjugate structures.
Article in Journal of computational chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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, 56 citations in OpenAlex.
- Molecular correlates of vaccine-induced protection against typhoid fever.The Journal of clinical investigation · 2023Trial
- Atom-level machine learning of protein-glycan interactions and cross-chiral recognition in glycobiology.Science advances · 2025Article
- mRNA delivery of circumsporozoite protein epitope-based malaria vaccines induces protection in a mouse model.NPJ vaccines · 2025Article
- Glycan masking in immunogen design: computational and experimental methods.Frontiers in immunology · 2025Review
- Epitope mapping via in vitro deep mutational scanning methods and its applications.The Journal of biological chemistry · 2025Review
- Modeling Protein-Glycan Interactions with HADDOCK.Journal of chemical information and modeling · 2024Article
- Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design.PLoS computational biology · 2024Article
- The Mutagenic Plasticity of the Cholera Toxin B-Subunit Surface Residues: Stability and Affinity.Toxins · 2024Article
- Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins.PLoS computational biology · 2024Article
- Computational toolbox for the analysis of protein-glycan interactions.Beilstein journal of organic chemistry · 2024Review
- Recent Advances in NMR Protein Structure Prediction with ROSETTA.International journal of molecular sciences · 2023Review
- Stabilizing proteins, simplified: A Rosetta-based webtool for predicting favorable mutations.Protein science : a publication of the Protein Society · 2022Article
- Strategies for Glycoengineering Therapeutic Proteins.Frontiers in chemistry · 2022Review
- Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks.Nature communications · 2021Article
- Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta.The journal of physical chemistry. B · 2021Article
- An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants.Structure (London, England : 1993) · 2021Article
- Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design.Biochemistry · 2021Review
- CoV3D: a database of high resolution coronavirus protein structures.Nucleic acids research · 2021Article
- Three-Dimensional Structures of Carbohydrates and Where to Find Them.International journal of molecular sciences · 2020Review
- Article
Corrections and comments
- Erratum issuedErratum.2017
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The RosettaCarbohydrate framework is a new tool for modeling a wide variety of saccharide and glycoconjugate structures. This report describes the development of the framework and highlights its applications. The framework integrates with established protocols within the Rosetta modeling and design suite, and it handles the vast complexity and variety of carbohydrate molecules, including branching and sugar modifications. To address challenges of sampling and scoring, RosettaCarbohydrate can sample glycosidic bonds, side-chain conformations, and ring forms, and it utilizes a glycan-specific term within its scoring function. Rosetta can work with standard PDB, GLYCAM, and GlycoWorkbench (.gws) file formats. Saccharide residue-specific chemical information is stored internally, permitting glycoengineering and design. Carbohydrate-specific applications described herein include virtual glycosylation, loop-modeling of carbohydrates, and docking of glyco-ligands to antibodies. Benchmarking data are presented and compared to other studies, demonstrating Rosetta's ability to predict glyco-ligand binding. The framework expands the tools available to glycoscientists and engineers. © 2016 Wiley Periodicals, Inc.
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.