ArticleBioinformatics (Oxford, England)2023
A gated graph transformer for protein complex structure quality assessment and its performance in CASP15.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- TINA: a geometry-aware post-hoc scoring framework for protein-protein interaction.Acta pharmacologica Sinica · 2026Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.Journal of chemical information and modeling · 2026Article
- Incorporating Surfaced-Induced Dissociation Mass Spectrometry Data into an AlphaFold-derived deep learning network improves protein structure prediction.bioRxiv : the preprint server for biology · 2026Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.bioRxiv : the preprint server for biology · 2026Article
- TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment.Briefings in bioinformatics · 2025Article
- EquiRank: Improved protein-protein interface quality estimation using protein language-model-informed equivariant graph neural networks.Computational and structural biotechnology journal · 2025Article
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
- Estimating protein complex model accuracy using graph transformers and pairwise similarity graphs.Bioinformatics advances · 2025Article
- Protein structure prediction via deep learning: an in-depth review.Frontiers in pharmacology · 2025Review
- Chemical cross-linking and mass spectrometry enabled systems-level structural biology.Current opinion in structural biology · 2024Review
- EGG: Accuracy Estimation of Individual Multimeric Protein Models Using Deep Energy-Based Models and Graph Neural Networks.International journal of molecular sciences · 2024Article
- A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models.Biomolecules · 2024Review
- Protein structure accuracy estimation using geometry-complete perceptron networks.Protein science : a publication of the Protein Society · 2024Article
- Article
- AlphaFold Accurately Predicts the Structure of Ribosomally Synthesized and Post-Translationally Modified Peptide Biosynthetic Enzymes.Biomolecules · 2023Article
- Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15.bioRxiv : the preprint server for biology · 2023Article
- PIQLE: protein-protein interface quality estimation by deep graph learning of multimeric interaction geometries.Bioinformatics advances · 2023Article
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4 authors.
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Abstract
motivationProteins interact to form complexes to carry out essential biological functions. Computational methods such as AlphaFold-multimer have been developed to predict the quaternary structures of protein complexes. An important yet largely unsolved challenge in protein complex structure prediction is to accurately estimate the quality of predicted protein complex structures without any knowledge of the corresponding native structures. Such estimations can then be used to select high-quality predicted complex structures to facilitate biomedical research such as protein function analysis and drug discovery.
resultsIn this work, we introduce a new gated neighborhood-modulating graph transformer to predict the quality of 3D protein complex structures. It incorporates node and edge gates within a graph transformer framework to control information flow during graph message passing. We trained, evaluated and tested the method (called DProQA) on newly-curated protein complex datasets before the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) and then blindly tested it in the 2022 CASP15 experiment. The method was ranked 3rd among the single-model quality assessment methods in CASP15 in terms of the ranking loss of TM-score on 36 complex targets. The rigorous internal and external experiments demonstrate that DProQA is effective in ranking protein complex structures. AVAILABILITY AND IMPLEMENTATION: The source code, data, and pre-trained models are available at https://github.com/jianlin-cheng/DProQA.
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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.