Model type
Structure-conditioned sequence model; this record is the paper-specific evaluated configuration.
Configuration
ProteinMPNN
This protein model is evaluated as a zero-shot mutation-effect scorer in ProteinGym.
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · ProteinGym benchmarks (paragraph 1); Introduction (paragraph 4)How it worksEvaluated procedure (conceptual)
Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings.
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1)At a glance
Biological inputs
Variant sequences and protein backbone structure
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · ProteinGym benchmarks/Mutation types (paragraph 1); ProteinGym benchmarks/Mutation types/Indels (paragraph 1)Outputs
Mutation-effect scores and ranked variants
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Appendix/A Appendix/A.4 Baselines/A.4.3 Clinical baselines (paragraph 1); Appendix/A Appendix/A.3 Datasets/A.3.2 Clinical datasets (paragraph 1)limited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Evaluations and results
Release 2026-09-17-d277315f7d76 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| ProteinMPNN: Zero-shot substitution mutation effects: stability Configuration: ProteinMPNNTask: Zero-shot substitution mutation effects: stabilityDataset: ProteinGym substitution DMS: stability assays Zero-shot mutation scores; average Spearman across stability-category assays. Independent external evaluation · Evaluation metadata: needs review | ||
| 0.566 Mean Spearman rho Unit: unitless · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Table A7, ProteinMPNN row, Stability column Source checking is not independent reproduction. |
How it works
How the evaluated method works
ProteinMPNN scores sequences conditional on an input protein backbone. ProteinGym treats it as an inverse-folding baseline, distinct from sequence-only language models.
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1)Underlying method and version boundaries
ProteinMPNN exposes full-backbone and Cα-only models with separate weights. It can score a sequence conditional on structure or generate sequences; these modes and backbone variants must remain explicit.
Sources
dauparas/ProteinMPNN README.md · README.md; introduction, model description, pretrained-model and usage sections at pinned revisionWhat was evaluated
The linked evaluation record identifies ProteinMPNN: Zero-shot substitution mutation effects: stability. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-018Strengths and limitations
Strengths and considerations
- Uses standardised evaluation across diverse experimental assays.
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Introduction (paragraph 2); Abstract (paragraph 1)
Limitations and conditions
- Different models receive different evolutionary/structural information; assay fitness, organismal fitness and clinical pathogenicity are not interchangeable endpoints.
Sources
ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · ProteinGym benchmarks (paragraph 1); Appendix/A Appendix/A.3 Datasets/A.3.1 DMS assays/Processing of large thermostability dataset (paragraph 2)
Profile review details
Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction.
Stable record: reported-model-e0443048c6e110Specifications
Inputs, training, access and other details
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Model type | Structure-conditioned sequence model; this record is the paper-specific evaluated configuration.Sourcesdauparas/ProteinMPNN README.md · README.md model description |
| Architecture / procedure | ProteinMPNN scores sequences conditional on an input protein backbone. ProteinGym treats it as an inverse-folding baseline, distinct from sequence-only language models.SourcesProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1) |
| Biological inputs | Variant sequences and protein backbone structureSourcesProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · ProteinGym benchmarks/Mutation types (paragraph 1); ProteinGym benchmarks/Mutation types/Indels (paragraph 1) |
| Outputs | Mutation-effect scores and ranked variantsSourcesProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Appendix/A Appendix/A.4 Baselines/A.4.3 Clinical baselines (paragraph 1); Appendix/A Appendix/A.3 Datasets/A.3.2 Clinical datasets (paragraph 1) |
| Parameters | An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction; dauparas/ProteinMPNN README.md · ProteinGym benchmarks/Model training regime; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision |
| Known versions / configuration | ProteinMPNN is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sourcesSourcesProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. |
| Training data / fitting | PDB structure training, as identified in ProteinGym’s inverse-folding baseline description.SourcesProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Appendix/A Appendix/A.3 Datasets/A.3.1 DMS assays/Selection and processing (paragraph 1); Appendix/A Appendix/A.3 Datasets/A.3.3 Access (paragraph 3) |
| Context limits | A maximum input/context length for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction; dauparas/ProteinMPNN README.md · ProteinGym benchmarks/Model training regime; inspected for explicit maximum input length (dataset lengths and family-wide limits are not substituted); README.md at pinned repository revision |
| Access | Official upstream implementation and usage documentation: https://github.com/dauparas/ProteinMPNN/blob/8907e6671bfbfc92303b5f79c4b5e6ce47cdef57/README.md. This pinned documentation revision is not automatically the evaluated weight revision.Sourcesdauparas/ProteinMPNN README.md · README.md; installation, model download and usage instructions |
| Code licence | MIT (upstream repository code at the cited revision; this does not establish every dependency or historical checkpoint licence).Sourcesdauparas/ProteinMPNN LICENSE · LICENSE; complete licence text |
| Weights licence | The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. · Not reported in inspected sourcesSourcesdauparas/ProteinMPNN README.md · README.md; checkpoint/access documentation and licence scope |
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.
22 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings. Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1) Version: PMC10723403.1 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Variant sequences and protein backbone structure","ProteinMPNN","Mutation-effect scores and ranked variants"] Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1) Version: PMC10723403.1 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Evaluated procedure (conceptual) Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1) Version: PMC10723403.1 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Model type Structure-conditioned sequence model; this record is the paper-specific evaluated configuration. Individual claims | dauparas/ProteinMPNN README.md README.md model description Version: 8907e6671bfbfc92303b5f79c4b5e6ce47cdef57 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Architecture / procedure ProteinMPNN scores sequences conditional on an input protein backbone. ProteinGym treats it as an inverse-folding baseline, distinct from sequence-only language models. Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1) Version: PMC10723403.1 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Weights licence The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. Individual claims | dauparas/ProteinMPNN README.md README.md; checkpoint/access documentation and licence scope Version: 8907e6671bfbfc92303b5f79c4b5e6ce47cdef57 | unreported automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Biological inputs Variant sequences and protein backbone structure Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction ProteinGym benchmarks/Mutation types (paragraph 1); ProteinGym benchmarks/Mutation types/Indels (paragraph 1) Version: PMC10723403.1 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Outputs Mutation-effect scores and ranked variants Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction Appendix/A Appendix/A.4 Baselines/A.4.3 Clinical baselines (paragraph 1); Appendix/A Appendix/A.3 Datasets/A.3.2 Clinical datasets (paragraph 1) Version: PMC10723403.1 | source checked automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | dauparas/ProteinMPNN README.md ProteinGym benchmarks/Model training regime; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 8907e6671bfbfc92303b5f79c4b5e6ce47cdef57 | unreported automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction ProteinGym benchmarks/Model training regime; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: PMC10723403.1 | unreported automated source review · 2026-09-16 Audit detailsPrimary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-09-17-d277315f7d76 · Record review: needs review
3 source records and release history
- ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction · Original source · PMC10723403.1
- dauparas/ProteinMPNN README.md · Original source · 8907e6671bfbfc92303b5f79c4b5e6ce47cdef57
- dauparas/ProteinMPNN LICENSE · Original source · 8907e6671bfbfc92303b5f79c4b5e6ce47cdef57
Technical metadata and extraction receipts
Stable ID: reported-model-e0443048c6e110
- areas
- proteins-complexes
- entity level
- method
- version
- Not reported
- reported name
- ProteinMPNN
- historical missing metadata
- version: not_reported_in_legacy_extract; checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: not_reported_in_legacy_extract
- metadata review scope
- historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
- legacy kinds
- model
- entity classification
- review date: 2026-09-17; rationale: This source-scoped entry preserves the method/configuration actually named in an evaluation. It is neither a global family identity nor proof of an immutable checkpoint; the linked evaluation retains adaptation, fitting and scoring details.; source ids: proteingym-2023; evidence-reported-base-proteinmpnn-readme-md; source locator: Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Inverse Folding models (paragraph 1); Appendix/A Appendix/A.4 Baselines/A.4.1 Zero-shot baselines/Protein language models (paragraph 1) | README.md model description | ProteinGym benchmarks (paragraph 1); Introduction (paragraph 4); ambiguities: Configuration means the source-labelled evaluated identity. It does not establish missing checkpoint hashes, default settings or equivalence to same-named records in other papers.