ArticleNature communications2022
Predicting the structure of large protein complexes using AlphaFold and Monte Carlo tree search.
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 103 papers.
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103 citing papers in PubMed.
- FoldaVirus, a knowledge-based icosahedral capsid prediction tool using AlphaFold.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Evaluation of methods for AlphaFold-based integrative modeling.bioRxiv : the preprint server for biology · 2026Article
- A cross-vertebrate brain protein interaction map identifies conserved neural and non-neural complexes.Cell reports · 2026Article
- Applications of large-scale artificial intelligence models in bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Automated assembly of protein complexes from cryo-EM maps with structure-informed Monte Carlo Tree Search.bioRxiv : the preprint server for biology · 2026Article
- Hierarchical small molecule inhibition of MYST acetyltransferases.Nature communications · 2026Article
- Advancing single-cell omics and cell-based therapeutics with quantum computing.Nature reviews. Molecular cell biology · 2026Review
- Phycoerythrin nanoemulsion-enriched probiotic sausage: enhancing Bacillus coagulans viability via Aliinostoc sp. 2 exopolysaccharides.Scientific reports · 2026Article
- Sequestration of growth cone surface proteins by cytoplasmic Lrrtm2 inducesbioRxiv : the preprint server for biology · 2026Article
- Atlas of predicted protein complex structures across kingdoms.Nature communications · 2026Article
- Peptide-Based Probe Targeting Angiotensin Type‑1 Receptor Identifies Pancreatic Ductal Adenocarcinoma Using Multispectral Optoacoustic Tomography.Chemical & biomedical imaging · 2026Article
- Self-assembling protein cages: from coiled-coil module to machine learning-drivenMaterials advances · 2026Review
- NanoporeDB: a structural resource of multimeric protein nanopores for single-molecule sensing.GigaScience · 2026Article
- Highlights of Model Quality Assessment in CASP16.Proteins · 2026Article
- Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026Review
- The power and limits of predicting inter-protein exon-exon interactions using protein 3D structures.Bioinformatics advances · 2026Article
- AlphaFold3 at CASP16.Proteins · 2026Article
- Molecular basis for multidrug efflux by an anaerobic-associated RND transporter.Nature communications · 2025Article
- Convergent evolution of viral-like Borg archaeal extrachromosomal elements and giant eukaryotic viruses.Nature communications · 2025Article
- VerteBrain reveals novel neural and non-neural protein assemblies conserved across vertebrate evolution.bioRxiv : the preprint server for biology · 2025Article
43 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AlphaFold can predict the structure of single- and multiple-chain proteins with very high accuracy. However, the accuracy decreases with the number of chains, and the available GPU memory limits the size of protein complexes which can be predicted. Here we show that one can predict the structure of large complexes starting from predictions of subcomponents. We assemble 91 out of 175 complexes with 10-30 chains from predicted subcomponents using Monte Carlo tree search, with a median TM-score of 0.51. There are 30 highly accurate complexes (TM-score ≥0.8, 33% of complete assemblies). We create a scoring function, mpDockQ, that can distinguish if assemblies are complete and predict their accuracy. We find that complexes containing symmetry are accurately assembled, while asymmetrical complexes remain challenging. The method is freely available and accesible as a Colab notebook https://colab.research.google.com/github/patrickbryant1/MoLPC/blob/master/MoLPC.ipynb .
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