ArticleProteins2015
CONFOLD: Residue-residue contact-guided ab initio protein folding.
Article in Proteins, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed.
- The Blobulator: A Toolkit for Identification and Visual Exploration of Hydrophobic Modularity in Protein Sequences.Journal of chemical information and modeling · 2026Article
- Protein Structure Prediction Methods.Advances in experimental medicine and biology · 2026Review
- The blobulator: a toolkit for identification and visual exploration of hydrophobic modularity in protein sequences.bioRxiv : the preprint server for biology · 2025Article
- AlphaKnot 2.0: a web server for the visualization of proteins' knotting and a database of knotted AlphaFold-predicted models.Nucleic acids research · 2024Article
- Lactylation prediction models based on protein sequence and structural feature fusion.Briefings in bioinformatics · 2024Article
- Contact-Assisted Threading in Low-Homology Protein Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Article
- Enhancing protein inter-residue real distance prediction by scrutinising deep learning models.Scientific reports · 2022Article
- Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14.Proteins · 2022Article
- Inter-Residue Distance Prediction From Duet Deep Learning Models.Frontiers in genetics · 2022Article
- Improved Protein Structure Prediction Using a New Multi-Scale Network and Homologous Templates.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Article
- Improving fragment-based ab initio protein structure assembly using low-accuracy contact-map predictions.Nature communications · 2021Article
- The evolutionary history of topological variations in the CPA/AT transporters.PLoS computational biology · 2021Article
- COMTOP: Protein Residue-Residue Contact Prediction through Mixed Integer Linear Optimization.Membranes · 2021Article
- Evaluation of residue-residue contact prediction methods: From retrospective to prospective.PLoS computational biology · 2021Article
- Accurate contact-based modelling of repeat proteins predicts the structure of new repeats protein families.PLoS computational biology · 2021Article
- Hybridized distance- and contact-based hierarchical structure modeling for folding soluble and membrane proteins.PLoS computational biology · 2021Article
- DISTEVAL: a web server for evaluating predicted protein distances.BMC bioinformatics · 2021Article
- Recent Advances in Protein Homology Detection Propelled by Inter-Residue Interaction Map Threading.Frontiers in molecular biosciences · 2021Review
- Generating tertiary protein structures via interpretable graph variational autoencoders.Bioinformatics advances · 2021Article
7 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
Abstract
Predicted protein residue-residue contacts can be used to build three-dimensional models and consequently to predict protein folds from scratch. A considerable amount of effort is currently being spent to improve contact prediction accuracy, whereas few methods are available to construct protein tertiary structures from predicted contacts. Here, we present an ab initio protein folding method to build three-dimensional models using predicted contacts and secondary structures. Our method first translates contacts and secondary structures into distance, dihedral angle, and hydrogen bond restraints according to a set of new conversion rules, and then provides these restraints as input for a distance geometry algorithm to build tertiary structure models. The initially reconstructed models are used to regenerate a set of physically realistic contact restraints and detect secondary structure patterns, which are then used to reconstruct final structural models. This unique two-stage modeling approach of integrating contacts and secondary structures improves the quality and accuracy of structural models and in particular generates better β-sheets than other algorithms. We validate our method on two standard benchmark datasets using true contacts and secondary structures. Our method improves TM-score of reconstructed protein models by 45% and 42% over the existing method on the two datasets, respectively. On the dataset for benchmarking reconstructions methods with predicted contacts and secondary structures, the average TM-score of best models reconstructed by our method is 0.59, 5.5% higher than the existing method. The CONFOLD web server is available at http://protein.rnet.missouri.edu/confold/.
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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.