ArticleNature communications2022
AF2Complex predicts direct physical interactions in multimeric proteins with deep learning.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 144 papers.
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Who cites it
144 citing papers in PubMed.
- The cellular landscape of druggable RNA-binding proteins.Nature reviews. Drug discovery · 2026Review
- Integrating evolutionary signals and predicted protein structure reveals localized molecular divergence in Cereus lineages.Genetica · 2026Article
- A curated benchmark for cofolding models on kinase conformational states.npj drug discovery · 2026Article
- Elucidating the molecular basis of ATP synthase inhibition: A virtual screening framework for next-gen selective acaricides.Science advances · 2026Article
- DirectContacts2: a wiring diagram of human physical protein interactions.Nature communications · 2026Article
- AI-validated fusion proteins for local inhibition of interleukin-17A.Journal of controlled release : official journal of the Controlled Release Society · 2026Article
- Structural insights into predicted protein-protein interactions and protein complexes in the human proteome.Scientific reports · 2026Article
- AlphaInterp: Mechanistic Interpretability of AlphaFold 3 Reveals How Evolutionary Information Shapes Protein Structure Prediction.bioRxiv : the preprint server for biology · 2026Article
- PPIscreenML is a method for structure-based screening of protein-protein interactions using AlphaFold.eLife · 2026Article
- KinConfBench: A Curated Benchmark for Cofolding Models on Kinase Conformational States.bioRxiv : the preprint server for biology · 2026Article
- Interactys-AI: Toward AI-Driven Structural Mapping of Virus-Host Interfaces for Antiviral Repurposing and Pandemic Preparedness.Biomolecules · 2026Review
- Proteome-wide AlphaFold pool party.Molecular systems biology · 2026Article
- Fast sampling of protein conformational dynamics.Science advances · 2026Article
- GlueFinder: A Data-Driven Framework for the Rational Discovery of Molecular Glues.Journal of chemical information and modeling · 2026Article
- BEST: Basic Embedding Search Tool Enhancing Discovery of Novel Enzyme.Interdisciplinary sciences, computational life sciences · 2026Article
- Adversarial Sequence Mutations in AlphaFold and ESMFold Reveal Nonphysical Structural Invariance, Confidence Failures, and Concerns for Protein Design.Computational and structural biotechnology journal · 2026Article
- Optimizing the breadth of SARS-CoV-2-neutralizing antibodies in vivo and in silico.Human vaccines & immunotherapeutics · 2025Review
- Article
- A proximity map of RAB GTPases delineates roles for RAB14 in EARP complex and UHRF1BP1 endosomal recruitments.Communications biology · 2025Article
- DeepFold-PLM: accelerating protein structure prediction via efficient homology search using protein language models.Bioinformatics (Oxford, England) · 2025Article
84 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
Abstract
Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the same neural network models from AF2 developed for single protein sequences can be adapted to predict the structures of multimeric protein complexes without retraining. In contrast to common approaches, our method, AF2Complex, does not require paired multiple sequence alignments. It achieves higher accuracy than some complex protein-protein docking strategies and provides a significant improvement over AF-Multimer, a development of AlphaFold for multimeric proteins. Moreover, we introduce metrics for predicting direct protein-protein interactions between arbitrary protein pairs and validate AF2Complex on some challenging benchmark sets and the E. coli proteome. Lastly, using the cytochrome c biogenesis system I as an example, we present high-confidence models of three sought-after assemblies formed by eight members of this system.
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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.