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Docker
Protein-Protein Docking
Quality Assessment
ModFOLDdock2Q
Quality assessment of protein-protein complex models using deep learning and structural features.
ModFOLDdock2Q scores the quality of protein–protein and quaternary complex models, combining single-model and consensus signals through deep learning over a large engineered feature set — benchmarked at the CASP15 and CASP16 assessments.
16K+
Quaternary
CASP15/16
$ docker pull radiyaman/modfolddock2q$ docker run -v $(pwd):/data radiyaman/modfolddock2q \
-i /data/complex.pdb -o /data/outputDeep-learning QA
Networks trained on CASP complex targets predict per-interface and global accuracy.
Multi-signal scoring
Combines structural, statistical and energetic features (DockQ, QS, iLDDT, …).
Reproducible
Containerised so results are identical across machines and pipelines.
> key_publications
Peer-reviewed foundations
Prediction and quality assessment of protein quaternary structure models using the MultiFOLD2 and ModFOLDdock2 servers
Nucleic Acids Research · 2025
Estimation of model accuracy in CASP15 using the ModFOLDdock server
Proteins: Structure, Function, and Bioinformatics · 2023 · 20 citations
Highlights of model quality assessment in CASP16
Proteins: Structure, Function, and Bioinformatics · 2025