rewirebio.iobenchmarks
Evaluation

AlphaFold3 top model by pDockQ2 on 110 post-cutoff antibody-antigen complexes (Fromm et al. 2026)

Published comparison; transcribed, not reproduced.

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Release 2026-10-10-6e93f504adfc · Evidence verified: Not verified

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Evaluation results

1 evaluation · 3 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: AlphaFold3, 200 models per target, top model picked by pDockQ2 (Zhu et al. 2023) (Fromm et al. 2026)Protocol: Picking the top AlphaFold3 model per antibody-antigen target with a confidence score
Dataset: Fromm et al. 2026 antibody-antigen benchmark: 110 complexes released after 30 September 2021
0.352 dockq
unitless · higher

Uncertainty: Not reported by the source

Coverage: 110 scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

AlphaFold3 top model by pDockQ2 on 110 post-cutoff antibody-antigen complexes (Fromm et al. 2026)

structural-20261009-protocol-fromm2026-abag-model-selection

Aggregation: Not reported

Evaluating deep learning based structure prediction methods on antibody-antigen complexes · Table 1, row 'pDockQ2', column '<DockQ>'
Configuration: AlphaFold3, 200 models per target, top model picked by pDockQ2 (Zhu et al. 2023) (Fromm et al. 2026)Protocol: Picking the top AlphaFold3 model per antibody-antigen target with a confidence score
Dataset: Fromm et al. 2026 antibody-antigen benchmark: 110 complexes released after 30 September 2021
0.603 spearman-correlation
unitless · higher

Uncertainty: Not reported by the source

Coverage: 110 scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

AlphaFold3 top model by pDockQ2 on 110 post-cutoff antibody-antigen complexes (Fromm et al. 2026)

structural-20261009-protocol-fromm2026-abag-model-selection

Aggregation: Not reported

Evaluating deep learning based structure prediction methods on antibody-antigen complexes · Table 1, row 'pDockQ2', column 'R'
Configuration: AlphaFold3, 200 models per target, top model picked by pDockQ2 (Zhu et al. 2023) (Fromm et al. 2026)Protocol: Picking the top AlphaFold3 model per antibody-antigen target with a confidence score
Dataset: Fromm et al. 2026 antibody-antigen benchmark: 110 complexes released after 30 September 2021
0.184 spearman-correlation
unitless · higher

Uncertainty: Not reported by the source

Coverage: 110 scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

AlphaFold3 top model by pDockQ2 on 110 post-cutoff antibody-antigen complexes (Fromm et al. 2026)

structural-20261009-protocol-fromm2026-abag-model-selection

Aggregation: Not reported

Evaluating deep learning based structure prediction methods on antibody-antigen complexes · Table 1, row 'pDockQ2', column '<R>'

Source checking is not independent reproduction. Release 2026-10-10-6e93f504adfc.

Evaluation procedure

structural-20261009-protocol-fromm2026-abag-model-selection

Configuration
AlphaFold3, 200 models per target, top model picked by pDockQ2 (Zhu et al. 2023) (Fromm et al. 2026)
Protocol
Picking the top AlphaFold3 model per antibody-antigen target with a confidence score
Dataset
Fromm et al. 2026 antibody-antigen benchmark: 110 complexes released after 30 September 2021
origin
Author-reported evaluation
configuration
Primary source as retrieved 2026-10-09
protocol id
structural-20261009-protocol-fromm2026-abag-model-selection
dataset version
110 complexes deposited after 30 September 2021
split
Temporal split at the AlphaFold3 training cutoff
population
110 antibody-antigen complexes
inputs
Sequences and MSAs; no templates of the complex
adaptation
None; selection among sampled models
metric implementation
DockQ (Basu and Wallner 2016; Mirabello and Wallner 2024)
aggregation
Mean over targets
budget
200 models per target

Metadata review: source checked. Unreported conditions prevent automatic comparisons.

Reproduction

Split
Temporal split at the AlphaFold3 training cutoff
Adaptation
None; selection among sampled models
Scoring implementation
DockQ (Basu and Wallner 2016; Mirabello and Wallner 2024)

No execution recipe has been verified for this exact configuration and evaluation. A benchmark's general instructions may use different inputs, splits or model settings.

Reproducing this published result requires matching its model configuration, data, split and scorer. Source checking or a successful smoke test does not establish score reproduction.

Evidence

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Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

19 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-10-6e93f504adfc
Property and statementOriginal source and locationReview and provenance
attributes.comparison.adaptation
None; selection among sampled models
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.adaptation

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.aggregation
Mean over targets
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.aggregation

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.budget
200 models per target
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.budget

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.dataset_version
110 complexes deposited after 30 September 2021
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.dataset_version

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.inputs
Sequences and MSAs; no templates of the complex
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.inputs

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.metric_implementation
DockQ (Basu and Wallner 2016; Mirabello and Wallner 2024)
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.metric_implementation

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.population
110 antibody-antigen complexes
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.population

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.protocol_id
structural-20261009-protocol-fromm2026-abag-model-selection
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.protocol_id

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.comparison.split
Temporal split at the AlphaFold3 training cutoff
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.comparison.split

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

attributes.limitations
2 values
  • pDockQ2 was developed by the same group as this source.
  • Run by authors who did not develop AlphaFold3.
Context-only references
Evaluating deep learning based structure prediction methods on antibody-antigen complexes

Original source ↗

Table 1, row 'pDockQ2'

Version: Bioinformatics 42(4):btag136, 2026; PMC13061134 full-text XML
Retrieved: 2026-10-09T21:21:58Z

not individually reviewed

No individual claim review recorded

author reported

Audit details

Field: attributes.limitations

Source artifact SHA-256: a7320667ed6f7d8df440d90275d976b91d2fe98411172a79c6a304eb3f02275d

Hash scope: JATS XML parse (xml.etree), by extract/extract_structural.py

Inspected artifact

Sources and history

Release 2026-10-10-6e93f504adfc · Record review: source checked

1 source records and release historyDownload this release (gzip)
Technical metadata and extraction receipts

Stable ID: structural-20261009-eval-fromm2026-af3-pdockq2

areas
proteins-complexes
contexts
research
origin
author_reported
protocol
structural-20261009-protocol-fromm2026-abag-model-selection
version
Primary source as retrieved 2026-10-09
comparison
protocol id: structural-20261009-protocol-fromm2026-abag-model-selection; dataset version: 110 complexes deposited after 30 September 2021; split: Temporal split at the AlphaFold3 training cutoff; population: 110 antibody-antigen complexes; inputs: Sequences and MSAs; no templates of the complex; adaptation: None; selection among sampled models; metric implementation: DockQ (Basu and Wallner 2016; Mirabello and Wallner 2024); aggregation: Mean over targets; budget: 200 models per target
source locator
Table 1, row 'pDockQ2'
limitations
pDockQ2 was developed by the same group as this source.; Run by authors who did not develop AlphaFold3.
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