Strengths and considerations
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Configuration
DeepProSite
DeepProSite as evaluated in the cited study. Paper-specific predictor and its documented input information
Sources
Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 3 (Tab3), row 4 DeepProSite, column 2: SJC test split RecallOverview
Key specifications have not been extracted for this record. See the linked evaluation and sources for the reported setup.
limited source coverage · Automated source review, 2026-09-17. All specifications and missing details
Evaluations and results
2 evaluations · 8 results. Different protocols are not a single leaderboard.
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| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: DeepProSite | Protocol: UniProtSMB test split (protein-small molecule binding-site prediction) Dataset: UniProtSMB test split | 0.490 ± 0.013 Recall unitless · higher Uncertainty: printed: 0.013; value: 0.013; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepProSite: UniProtSMB test split Residue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 4 (Tab4), row 4 DeepProSite, column 2: UniProtSMB test split Recall |
| Configuration: DeepProSite | Protocol: SJC test split (protein-small molecule binding-site prediction) Dataset: SJC test split | 0.458 ± 0.022 Recall unitless · higher Uncertainty: printed: 0.022; value: 0.022; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceResidue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 3 (Tab3), row 4 DeepProSite, column 2: SJC test split Recall |
| Configuration: DeepProSite | Protocol: SJC test split (protein-small molecule binding-site prediction) Dataset: SJC test split | 0.926 ± 0.002 AUROC unitless · higher Uncertainty: printed: 0.002; value: 0.002; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceResidue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 3 (Tab3), row 4 DeepProSite, column 5: SJC test split AUROC |
| Configuration: DeepProSite | Protocol: UniProtSMB test split (protein-small molecule binding-site prediction) Dataset: UniProtSMB test split | 0.756 ± 0.005 Precision unitless · higher Uncertainty: printed: 0.005; value: 0.005; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepProSite: UniProtSMB test split Residue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 4 (Tab4), row 4 DeepProSite, column 3: UniProtSMB test split Precision |
| Configuration: DeepProSite | Protocol: UniProtSMB test split (protein-small molecule binding-site prediction) Dataset: UniProtSMB test split | 0.598 ± 0.006 MCC unitless · higher Uncertainty: printed: 0.006; value: 0.006; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepProSite: UniProtSMB test split Residue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 4 (Tab4), row 4 DeepProSite, column 4: UniProtSMB test split MCC |
| Configuration: DeepProSite | Protocol: SJC test split (protein-small molecule binding-site prediction) Dataset: SJC test split | 0.524 ± 0.015 MCC unitless · higher Uncertainty: printed: 0.015; value: 0.015; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceResidue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 3 (Tab3), row 4 DeepProSite, column 4: SJC test split MCC |
| Configuration: DeepProSite | Protocol: UniProtSMB test split (protein-small molecule binding-site prediction) Dataset: UniProtSMB test split | 0.965 ± 0.001 AUROC unitless · higher Uncertainty: printed: 0.001; value: 0.001; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDeepProSite: UniProtSMB test split Residue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 4 (Tab4), row 4 DeepProSite, column 5: UniProtSMB test split AUROC |
| Configuration: DeepProSite | Protocol: SJC test split (protein-small molecule binding-site prediction) Dataset: SJC test split | 0.644 ± 0.011 Precision unitless · higher Uncertainty: printed: 0.011; value: 0.011; type: not explicitly identified in inspected table or caption Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceResidue-level small-molecule binding-site classification. 80/10/10 train/validation/test partition of nonredundant sequences. Aggregation: Not reported Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 3 (Tab3), row 4 DeepProSite, column 3: SJC test split Precision |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
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Evaluation in this paper
Paper-specific predictor and its documented input information
Sources
Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Table 3 (Tab3), row 4 DeepProSite, column 2: SJC test split RecallStrengths, limitations and unresolved questions
Strengths and limitations
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Stable record: paper-model-f0cf54fd450ed319efSpecifications
Inputs, training, access and other details
Explanatory profile: limited source coverage · Automated source review, 2026-09-17. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
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Evidence
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Evidence table
Inspect claims, sources and review details
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2 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Evaluation in this paper Paper-specific predictor and its documented input information Individual claims | Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning Table 3 (Tab3), row 4 DeepProSite, column 2: SJC test split Recall Version: version of record | source checked automated source review · 2026-09-17 Audit detailsPrimary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Introduction DeepProSite as evaluated in the cited study. Paper-specific predictor and its documented input information Individual claims | Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning Table 3 (Tab3), row 4 DeepProSite, column 2: SJC test split Recall Version: version of record | source checked automated source review · 2026-09-17 Audit detailsPrimary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
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Release 2026-09-29-06401fd5b220 · Record review: needs review
1 source records and release history
- Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning · Original source · version of record
Technical metadata and extraction receipts
Stable ID: paper-model-f0cf54fd450ed319ef
- areas
- proteins-complexes
- tasks
- protein-small molecule binding-site prediction
- entity level
- method
- configuration type
- reported_configuration
- version
- Paper-specific predictor and its documented input information
- 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: clape-smb-2024; source locator: Table 3 (Tab3), row 4 DeepProSite, column 2: SJC test split Recall; 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.