ArticleProteins2014
One contact for every twelve residues allows robust and accurate topology-level protein structure modeling.
Article in Proteins, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Foundation models in molecular biology.Biophysics reports · 2024Article
- Coevolution combined with molecular dynamics simulations provides structural and mechanistic insights into the interactions between the integrator complex subunits.Computational and structural biotechnology journal · 2023Article
- Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations.eLife · 2022Article
- A tale of solving two computational challenges in protein science: neoantigen prediction and protein structure prediction.Briefings in bioinformatics · 2022Review
- Article
- COMTOP: Protein Residue-Residue Contact Prediction through Mixed Integer Linear Optimization.Membranes · 2021Article
- Recent Applications of Deep Learning Methods on Evolution- and Contact-Based Protein Structure Prediction.International journal of molecular sciences · 2021Review
- An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling.Frontiers in molecular biosciences · 2021Article
- De Novo Protein Design for Novel Folds Using Guided Conditional Wasserstein Generative Adversarial Networks.Journal of chemical information and modeling · 2020Article
- ISSEC: inferring contacts among protein secondary structure elements using deep object detection.BMC bioinformatics · 2020Article
- When a foreign gene meets its native counterpart: computational biophysics analysis of two PgiC loci in the grass Festuca ovina.Scientific reports · 2020Article
- Deep learning enables the atomic structure determination of the Fanconi Anemia core complex from cryoEM.IUCrJ · 2020Article
- High-accuracy protein structures by combining machine-learning with physics-based refinement.Proteins · 2020Article
- RDbBMC bioinformatics · 2020Article
- Protein contact prediction using metagenome sequence data and residual neural networks.Bioinformatics (Oxford, England) · 2020Article
- Deep learning methods in protein structure prediction.Computational and structural biotechnology journal · 2020Review
- Evaluating Protein Transfer Learning with TAPE.Advances in neural information processing systems · 2019Article
- Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13.Proteins · 2019Article
- Driven to near-experimental accuracy by refinement via molecular dynamics simulations.Proteins · 2019Article
- Article
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5 authors.
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Abstract
A number of methods have been described for identifying pairs of contacting residues in protein three-dimensional structures, but it is unclear how many contacts are required for accurate structure modeling. The CASP10 assisted contact experiment provided a blind test of contact guided protein structure modeling. We describe the models generated for these contact guided prediction challenges using the Rosetta structure modeling methodology. For nearly all cases, the submitted models had the correct overall topology, and in some cases, they had near atomic-level accuracy; for example the model of the 384 residue homo-oligomeric tetramer (Tc680o) had only 2.9 Å root-mean-square deviation (RMSD) from the crystal structure. Our results suggest that experimental and bioinformatic methods for obtaining contact information may need to generate only one correct contact for every 12 residues in the protein to allow accurate topology level modeling.
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