rewirebio.iobenchmarks
Configuration

Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)

Configuration as run in the cited comparison.

3 evaluations · 6 results

Overview

Configuration as run in the cited comparison.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

3 evaluations · 6 results. Different protocols are not a single leaderboard.

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Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configurationProtocol and datasetFindingEvidence and details
Configuration: Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)Protocol: Telling cognate from shuffled nanobody-antigen pairs by ipTM
Dataset: Smorodina et al. 2026 all-against-all VHH-antigen pairing matrix (91 unique PDB entries)
0.067 average-precision
unitless · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Chai-1 on Telling cognate from shuffled nanobody-antigen pairs by ipTM (Smorodina et al. 2026)

structural-20261009-protocol-smorodina2026-vhh-cognate-vs-shuffled

Aggregation: Not reported

Structural Plausibility Without Binding Specificity: Limits of AI-Based Antibody-Antigen Structure Prediction Confidence Scores · Results P11, 'AP = 0.067' for Chai-1
Configuration: Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)Protocol: Best DockQ against sampling depth on cognate nanobody-antigen complexes
Dataset: Smorodina et al. 2026 nanobody-antigen benchmark: 106 cognate VHH-antigen complexes
0.04 dockq
unitless · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Chai-1 on Best DockQ against sampling depth on cognate nanobody-antigen complexes (Smorodina et al. 2026)

structural-20261009-protocol-smorodina2026-vhh-dockq-vs-sampling

Aggregation: Not reported

Structural Plausibility Without Binding Specificity: Limits of AI-Based Antibody-Antigen Structure Prediction Confidence Scores · Results P36, Chai-1 (0.04 to 0.19), N = 1
Configuration: Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)Protocol: Best DockQ against sampling depth on cognate nanobody-antigen complexes
Dataset: Smorodina et al. 2026 nanobody-antigen benchmark: 106 cognate VHH-antigen complexes
0.19 dockq
unitless · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Chai-1 on Best DockQ against sampling depth on cognate nanobody-antigen complexes (Smorodina et al. 2026)

structural-20261009-protocol-smorodina2026-vhh-dockq-vs-sampling

Aggregation: Not reported

Structural Plausibility Without Binding Specificity: Limits of AI-Based Antibody-Antigen Structure Prediction Confidence Scores · Results P36, Chai-1 (0.04 to 0.19), N = 100
Configuration: Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)Protocol: How well ipTM tracks DockQ on cognate nanobody-antigen complexes
Dataset: Smorodina et al. 2026 nanobody-antigen benchmark: 106 cognate VHH-antigen complexes
0.612 pearson-correlation
unitless · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Chai-1 on How well ipTM tracks DockQ on cognate nanobody-antigen complexes (Smorodina et al. 2026)

structural-20261009-protocol-smorodina2026-vhh-iptm-dockq-calibration

Aggregation: Not reported

Structural Plausibility Without Binding Specificity: Limits of AI-Based Antibody-Antigen Structure Prediction Confidence Scores · Results P19, Chai-1: ipTM against DockQ for the best-DockQ sample of each complex
Configuration: Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)Protocol: How well ipTM tracks DockQ on cognate nanobody-antigen complexes
Dataset: Smorodina et al. 2026 nanobody-antigen benchmark: 106 cognate VHH-antigen complexes
-0.019 pearson-correlation
unitless · higher

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Chai-1 on How well ipTM tracks DockQ on cognate nanobody-antigen complexes (Smorodina et al. 2026)

structural-20261009-protocol-smorodina2026-vhh-iptm-dockq-calibration

Aggregation: Not reported

Structural Plausibility Without Binding Specificity: Limits of AI-Based Antibody-Antigen Structure Prediction Confidence Scores · Results P21, Chai-1: change in ipTM against change in DockQ under saturation sampling
Configuration: Chai-1 0.6.1, 5 trunk x 10 diffusion samples, seed 42, ESM embeddings without MSAs (Smorodina et al. 2026)Protocol: How well ipTM tracks DockQ on cognate nanobody-antigen complexes
Dataset: Smorodina et al. 2026 nanobody-antigen benchmark: 106 cognate VHH-antigen complexes
24% proportion
percent · lower

Uncertainty: Not reported by the source

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Chai-1 on How well ipTM tracks DockQ on cognate nanobody-antigen complexes (Smorodina et al. 2026)

structural-20261009-protocol-smorodina2026-vhh-iptm-dockq-calibration

Aggregation: Not reported

Structural Plausibility Without Binding Specificity: Limits of AI-Based Antibody-Antigen Structure Prediction Confidence Scores · Results P19, Chai-1: share of predictions with ipTM below 0.5 and DockQ at least 0.23 (unconfident successes, Q4)

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Technical metadata and extraction receipts

Stable ID: structural-20261009-config-smorodina2026-chai1

areas
proteins-complexes
contexts
research
method types
foundation_model
reported name
Chai-1
foundation model eligible
true
source locator
Methods, structure prediction (P73)
version
0.6.1
parameters
num_trunk_samples = 5; num_diffn_samples = 10; num_trunk_recycles = 3; num_diffn_timesteps = 200; seed = 42; no MSAs
training overlap
25 of 106 cognate systems in the training set; 81 not (Chai-1 cutoff about 12 January 2021)
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