ArticleBriefings in bioinformatics2021
Accurate prediction of inter-protein residue-residue contacts for homo-oligomeric protein complexes.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed.
- Improving protein and protein interactions using pseudo-dimers derived from monomeric proteins.Nature communications · 2026Article
- An integrated computational antigen discovery pipeline with hierarchical filtering for emerging viral variants.NAR molecular medicine · 2026Article
- Machine Learning-Guided Engineering of Protein Phase Separation Properties in Immune Regulation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment.Briefings in bioinformatics · 2025Article
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
- AI-integrated network for RNA complex structure and dynamic prediction.Biophysics reviews · 2024Review
- Review and Comparative Analysis of Methods and Advancements in Predicting Protein Complex Structure.Interdisciplinary sciences, computational life sciences · 2024Review
- Protein language model-embedded geometric graphs power inter-protein contact prediction.eLife · 2024Article
- Flexible protein-protein docking with a multitrack iterative transformer.Protein science : a publication of the Protein Society · 2024Article
- Article
- Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15.Communications biology · 2023Article
- Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15.Communications chemistry · 2023Article
- Deep transfer learning for inter-chain contact predictions of transmembrane protein complexes.Nature communications · 2023Article
- Recent Advances in Deep Learning for Protein-Protein Interaction Analysis: A Comprehensive Review.Molecules (Basel, Switzerland) · 2023Review
- A gated graph transformer for protein complex structure quality assessment and its performance in CASP15.Bioinformatics (Oxford, England) · 2023Article
- Enhancing AlphaFold-Multimer-based Protein Complex Structure Prediction with MULTICOM in CASP15.bioRxiv : the preprint server for biology · 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
- Prediction of inter-chain distance maps of protein complexes with 2D attention-based deep neural networks.Nature communications · 2022Article
- The Possible Mechanism of Amyloid Transformation Based on the Geometrical Parameters of Early-Stage Intermediate in Silico Model for Protein Folding.International journal of molecular sciences · 2022Article
- Investigating the Effect of Tyrosine Kinase Inhibitors on the Interaction between Human Serum Albumin by Atomic Force Microscopy.Biomolecules · 2022Article
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2 authors.
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Abstract
Protein-protein interactions play a fundamental role in all cellular processes. Therefore, determining the structure of protein-protein complexes is crucial to understand their molecular mechanisms and develop drugs targeting the protein-protein interactions. Recently, deep learning has led to a breakthrough in intra-protein contact prediction, achieving an unusual high accuracy in recent Critical Assessment of protein Structure Prediction (CASP) structure prediction challenges. However, due to the limited number of known homologous protein-protein interactions and the challenge to generate joint multiple sequence alignments of two interacting proteins, the advances in inter-protein contact prediction remain limited. Here, we have proposed a deep learning model to predict inter-protein residue-residue contacts across homo-oligomeric protein interfaces, named as DeepHomo. Unlike previous deep learning approaches, we integrated intra-protein distance map and inter-protein docking pattern, in addition to evolutionary coupling, sequence conservation, and physico-chemical information of monomers. DeepHomo was extensively tested on both experimentally determined structures and realistic CASP-Critical Assessment of Predicted Interaction (CAPRI) targets. It was shown that DeepHomo achieved a high precision of >60% for the top predicted contact and outperformed state-of-the-art direct-coupling analysis and machine learning-based approaches. Integrating predicted inter-chain contacts into protein-protein docking significantly improved the docking accuracy on the benchmark dataset of realistic homo-dimeric targets from CASP-CAPRI experiments. DeepHomo is available at http://huanglab.phys.hust.edu.cn/DeepHomo/.
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