Protocol

Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2)

RMSE and correlation of predicted against experimental ddG on the Fireprot homologue-free split.

Overview

RMSE and correlation of predicted against experimental ddG on the Fireprot homologue-free split.

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

12 recorded evaluations, 36 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.

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Results

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All evaluations

12 evaluations · 36 results. Different protocols are not a single leaderboard.

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: ACDC-NN (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.57 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 ACDC-NN on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ACDC-NN', column 'Fireprot PCC'
Configuration: ACDC-NN (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	1.69 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source ACDC-NN on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ACDC-NN', column 'Fireprot RMSE (kcal/mol)'
Configuration: ACDC-NN (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.51 spearman-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 ACDC-NN on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ACDC-NN', column 'Fireprot SCC'
Configuration: ACDC-NN-Seq (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.54 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 ACDC-NN-Seq on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ACDC-NN-Seq', column 'Fireprot PCC'
Configuration: ACDC-NN-Seq (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	1.71 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source ACDC-NN-Seq on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ACDC-NN-Seq', column 'Fireprot RMSE (kcal/mol)'
Configuration: ACDC-NN-Seq (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.48 spearman-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 ACDC-NN-Seq on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ACDC-NN-Seq', column 'Fireprot SCC'
Configuration: FoldX (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.43 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 FoldX on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'FoldX', column 'Fireprot PCC'
Configuration: FoldX (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	2.77 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source FoldX on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'FoldX', column 'Fireprot RMSE (kcal/mol)'
Configuration: FoldX (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.57 spearman-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 FoldX on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'FoldX', column 'Fireprot SCC'
Configuration: MAESTRO (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.62 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 MAESTRO on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'MAESTRO', column 'Fireprot PCC'
Configuration: MAESTRO (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	1.49 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MAESTRO on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'MAESTRO', column 'Fireprot RMSE (kcal/mol)'
Configuration: MAESTRO (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.6 spearman-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 MAESTRO on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'MAESTRO', column 'Fireprot SCC'
Configuration: mCSM (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.59 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 mCSM on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'mCSM', column 'Fireprot PCC'
Configuration: mCSM (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	1.53 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source mCSM on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'mCSM', column 'Fireprot RMSE (kcal/mol)'
Configuration: mCSM (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.57 spearman-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 mCSM on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'mCSM', column 'Fireprot SCC'
Configuration: MUPRO (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.58 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 MUPRO on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'MUPRO', column 'Fireprot PCC'
Configuration: MUPRO (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	1.54 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MUPRO on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'MUPRO', column 'Fireprot RMSE (kcal/mol)'
Configuration: MUPRO (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.57 spearman-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 MUPRO on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'MUPRO', column 'Fireprot SCC'
Configuration: PROSTATA (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.59 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 PROSTATA on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'PROSTATA †', column 'Fireprot PCC'
Configuration: PROSTATA (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	1.68 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source PROSTATA on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'PROSTATA †', column 'Fireprot RMSE (kcal/mol)'
Configuration: PROSTATA (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.55 spearman-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 PROSTATA on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'PROSTATA †', column 'Fireprot SCC'
Configuration: ProteinMPNN (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.41 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 ProteinMPNN on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ProteinMPNN', column 'Fireprot PCC'
Configuration: ProteinMPNN (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	2.14 root-mean-squared-error kilocalorie-per-mole · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source ProteinMPNN on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ProteinMPNN', column 'Fireprot RMSE (kcal/mol)'
Configuration: ProteinMPNN (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.49 spearman-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 ProteinMPNN on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'ProteinMPNN', column 'Fireprot SCC'
Configuration: RaSP (Dieckhaus et al. 2024)	Protocol: Fireprot homologue-free split ddG prediction (Dieckhaus et al. 2024 Table 2) Dataset: FireProtDB homologue-free split with experimental structures	0.47 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 RaSP on Fireprot homologue-free split (Dieckhaus et al. 2024) protein-stability-20261009-protocol-dieckhaus2024-fireprot Aggregation: Not reported Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Table 2, row 'RaSP †', column 'Fireprot PCC'

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Author-reported evaluations: 1
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Transfer learning to leverage larger datasets for improved prediction of protein stability changes · Original source · PNAS 121(6):e2314853121, published 2024-01-29; PMC10861915 full-text XML

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Technical metadata and extraction receipts

Stable ID: protein-stability-20261009-protocol-dieckhaus2024-fireprot

areas: proteins-complexes
contexts: research
protocol: Predicted ddG compared with experimental ddG in kcal/mol; PCC Pearson and SCC Spearman correlation.
version: Table 2
metric: pearson-correlation
limitations: Developer comparison (ThermoMPNN authors).; Values marked * may be inflated because those methods' training sets contain close homologues of Fireprot proteins (Table 2 footnote).; 85 of 100 Fireprot proteins have fewer than 50 measurements; the three proteins with more than 250 were kept in training, and the homologue-free split has 89 proteins and 2,578 mutations.; No uncertainty is printed.
source locator: Table 2; Methods 'Datasets'

Related records

uses data: FireProtDB homologue-free split with experimental structures
assessment: ACDC-NN on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: ACDC-NN-Seq on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: FoldX on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: MAESTRO on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: mCSM on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: MUPRO on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: PROSTATA on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: ProteinMPNN on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: RaSP on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: Rosetta on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: ThermoMPNN on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessment: ThermoNet on Fireprot homologue-free split (Dieckhaus et al. 2024)
assessed by: Assess methods for protein stability experiments

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