ArticleProteins2014
BCL::Fold--protein topology determination from limited NMR restraints.
Article in Proteins, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Improving Protein Structure Prediction Using Integrative Cryo-EM and Ion Mobility Mass Spectrometry Modeling.Journal of chemical theory and computation · 2026Article
- Improving Protein Structure Prediction Using Integrative Cryo-EM and Ion Mobility Mass Spectrometry Modeling.bioRxiv : the preprint server for biology · 2026Article
- Improved 3-D Protein Structure Predictions using Deep ResNet Model.The protein journal · 2021Article
- Prediction of Protein Complex Structure Using Surface-Induced Dissociation and Cryo-Electron Microscopy.Analytical chemistry · 2021Article
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement.Journal of chemical information and modeling · 2020Article
- Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction.Biophysical journal · 2020Article
- Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures.Structure (London, England : 1993) · 2019Article
- Integrative Protein Modeling in RosettaNMR from Sparse Paramagnetic Restraints.Structure (London, England : 1993) · 2019Article
- Signaling through non-membrane nuclear phosphoinositide binding proteins in human health and disease.Journal of lipid research · 2019Review
- Development of a Prototype System for Archiving Integrative/Hybrid Structure Models of Biological Macromolecules.Structure (London, England : 1993) · 2018Article
- Integrated Structural Biology for α-Helical Membrane Protein Structure Determination.Structure (London, England : 1993) · 2018Article
- Finding the needle in the haystack: towards solving the protein-folding problem computationally.Critical reviews in biochemistry and molecular biology · 2018Review
- Improving prediction of helix-helix packing in membrane proteins using predicted contact numbers as restraints.Proteins · 2017Article
- Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning.PloS one · 2017Article
- CASP11--An Evaluation of a Modular BCL::Fold-Based Protein Structure Prediction Pipeline.PloS one · 2016Article
- Article
- Protein structure prediction guided by crosslinking restraints--A systematic evaluation of the impact of the crosslinking spacer length.Methods (San Diego, Calif.) · 2015Article
- Computational modeling of membrane proteins.Proteins · 2015Review
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Authors and funding
6 authors.
Funding
Abstract
When experimental protein NMR data are too sparse to apply traditional structure determination techniques, de novo protein structure prediction methods can be leveraged. Here, we describe the incorporation of NMR restraints into the protein structure prediction algorithm BCL::Fold. The method assembles discreet secondary structure elements using a Monte Carlo sampling algorithm with a consensus knowledge-based energy function. New components were introduced into the energy function to accommodate chemical shift, nuclear Overhauser effect, and residual dipolar coupling data. In particular, since side chains are not explicitly modeled during the minimization process, a knowledge based potential was created to relate experimental side chain proton-proton distances to Cβ -Cβ distances. In a benchmark test of 67 proteins of known structure with the incorporation of sparse NMR restraints, the correct topology was sampled in 65 cases, with an average best model RMSD100 of 3.4 ± 1.3 Å versus 6.0 ± 2.0 Å produced with the de novo method. Additionally, the correct topology is present in the best scoring 1% of models in 61 cases. The benchmark set includes both soluble and membrane proteins with up to 565 residues, indicating the method is robust and applicable to large and membrane proteins that are less likely to produce rich NMR datasets.
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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.