ArticlePLoS computational biology2014
Improved contact predictions using the recognition of protein like contact patterns.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
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79 citing papers in PubMed.
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- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- Tertiary structure assessment at CASP15.Proteins · 2023Article
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- Gene prediction of aging-related diseases based on DNN and Mashup.BMC bioinformatics · 2021Article
- Machine-Learned Molecular Surface and Its Application to Implicit Solvent Simulations.Journal of chemical theory and computation · 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
- Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8.Protein science : a publication of the Protein Society · 2021Article
- Toward Characterising the Cellular 3D-Proteome.Frontiers in bioinformatics · 2021Article
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Deep Learning in Protein Structural Modeling and Design.Patterns (New York, N.Y.) · 2020Review
- FilterDCA: Interpretable supervised contact prediction using inter-domain coevolution.PLoS computational biology · 2020Article
- RDbBMC bioinformatics · 2020Article
- Analysis of several key factors influencing deep learning-based inter-residue contact prediction.Bioinformatics (Oxford, England) · 2020Article
- Protein contact prediction using metagenome sequence data and residual neural networks.Bioinformatics (Oxford, England) · 2020Article
- Article
- Homology modeling in the time of collective and artificial intelligence.Computational and structural biotechnology journal · 2020Review
- Alzheimer's Disease: The Role of Mutations in Protein Folding.Advances in experimental medicine and biology · 2020Article
19 more citing papers are in PubMed but not listed here.
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4 authors.
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Abstract
Given sufficient large protein families, and using a global statistical inference approach, it is possible to obtain sufficient accuracy in protein residue contact predictions to predict the structure of many proteins. However, these approaches do not consider the fact that the contacts in a protein are neither randomly, nor independently distributed, but actually follow precise rules governed by the structure of the protein and thus are interdependent. Here, we present PconsC2, a novel method that uses a deep learning approach to identify protein-like contact patterns to improve contact predictions. A substantial enhancement can be seen for all contacts independently on the number of aligned sequences, residue separation or secondary structure type, but is largest for β-sheet containing proteins. In addition to being superior to earlier methods based on statistical inferences, in comparison to state of the art methods using machine learning, PconsC2 is superior for families with more than 100 effective sequence homologs. The improved contact prediction enables improved structure prediction.
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