ArticleBioinformatics (Oxford, England)2017
Large-scale structure prediction by improved contact predictions and model quality assessment.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- Development of anti-PD-L1 antibody based on structure prediction of AlphaFold2.Frontiers in immunology · 2023Article
- Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Interdependence of a mechanosensitive anion channel and glutamate receptors in distal wound signaling.Science advances · 2021Article
- Article
- Enhancing fragment-based protein structure prediction by customising fragment cardinality according to local secondary structure.BMC bioinformatics · 2020Article
- Analysis of several key factors influencing deep learning-based inter-residue contact prediction.Bioinformatics (Oxford, England) · 2020Article
- Fueling ab initio folding with marine metagenomics enables structure and function predictions of new protein families.Genome biology · 2019Article
- Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints.Nature communications · 2019Article
- Computational approaches to macromolecular interactions in the cell.Current opinion in structural biology · 2019Review
- Influence of multiple-sequence-alignment depth on Potts statistical models of protein covariation.Physical review. E · 2019Article
- RFQAmodel: Random Forest Quality Assessment to identify a predicted protein structure in the correct fold.PloS one · 2019Article
- DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.PloS one · 2019Article
- DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.Bioinformatics (Oxford, England) · 2018Article
- CONFOLD2: improved contact-driven ab initio protein structure modeling.BMC bioinformatics · 2018Article
- Large-scale structure prediction by improved contact predictions and model quality assessment.Bioinformatics (Oxford, England) · 2017Article
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4 authors.
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Abstract
motivationAccurate contact predictions can be used for predicting the structure of proteins. Until recently these methods were limited to very big protein families, decreasing their utility. However, recent progress by combining direct coupling analysis with machine learning methods has made it possible to predict accurate contact maps for smaller families. To what extent these predictions can be used to produce accurate models of the families is not known.
resultsWe present the PconsFold2 pipeline that uses contact predictions from PconsC3, the CONFOLD folding algorithm and model quality estimations to predict the structure of a protein. We show that the model quality estimation significantly increases the number of models that reliably can be identified. Finally, we apply PconsFold2 to 6379 Pfam families of unknown structure and find that PconsFold2 can, with an estimated 90% specificity, predict the structure of up to 558 Pfam families of unknown structure. Out of these, 415 have not been reported before. AVAILABILITY AND IMPLEMENTATION: Datasets as well as models of all the 558 Pfam families are available at http://c3.pcons.net/ . All programs used here are freely available. CONTACT: arne@bioinfo.se.
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