ArticleNucleic acids research2025
Prediction and quality assessment of protein quaternary structure models using the MultiFOLD2 and ModFOLDdock2 servers.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- A Step-by-Step Protocol for Efficient Global Accuracy Estimation of Protein Complex Structural Models with MViewEMA.Bio-protocol · 2026Article
- Article
- Stoic: fast and accurate protein stoichiometry prediction.Bioinformatics (Oxford, England) · 2026Article
- YdbL directly modulates YdbH-YnbE bridge formation to maintainbioRxiv : the preprint server for biology · 2026Article
- Efficient global accuracy estimation for protein complex structural models using multi-view representation learning.Cell reports methods · 2026Article
- Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model EvaluatiOn (CAMEO).Proteins · 2026Article
- Progress and Bottlenecks for Deep Learning in Computational Structure Biology: CASP Round XVI.Proteins · 2026Article
- StoPred: Accurate Stoichiometry Prediction for Protein Complexes Using Protein Language Models and Graph Attention.Research square · 2025Article
- StoPred: Accurate Stoichiometry Prediction for Protein Complexes Using Protein Language Models and Graph Attention.bioRxiv : the preprint server for biology · 2025Article
- Estimating protein complex model accuracy using graph transformers and pairwise similarity graphs.Bioinformatics advances · 2025Article
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Understanding the structures of protein complexes is pivotal for breakthroughs in health, agriculture, bioengineering, and beyond. MultiFOLD2 and ModFOLDdock2 are leading servers for protein quaternary structure prediction and model quality assessment, respectively. MultiFOLD2 includes integrated stoichiometry prediction for quaternary structures and improved sampling and scoring, leading to high performance in continuous independent benchmarks such as CAMEO. ModFOLDdock2 uses a hybrid consensus approach to generate global and local quality scores for predicted quaternary structures. ModFOLDdock2 is integrated with MultiFOLD2 while also being available as a stand-alone server, enabling the independent evaluation of quaternary structure models from any source. Both servers have been independently rigorously evaluated, demonstrating high performance and ranking among the top servers in their respective categories in the recent CASP16 experiment. The MultiFOLD2 and ModFOLDdock2 servers are freely accessible through user-friendly web interfaces at https://www.reading.ac.uk/bioinf/.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.