Protocol

PLABench KIBA, warm split

Affinity regression on KIBA, random partition (warm split) as established by MixingDTA; models retrained by the benchmark authors.

3 evaluations · 18 results

Overview

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3 recorded evaluations, 18 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

3 evaluations · 18 results. Different protocols are not a single leaderboard.

Protocol: PLABench KIBA, warm split · Dataset: KIBA warm test set (PLABench)

Sorted by Concordance index (PLABench KIBA-warm) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	Concordance index (PLABench KIBA-warm)	Modified squared correlation (PLABench KIBA-warm)	MSE (PLABench KIBA-warm)	Pearson (PLABench KIBA-warm)	RMSE (PLABench KIBA-warm)	Spearman (PLABench KIBA-warm)
LLF (retrained on Davis and KIBA, PLABench)Evaluation	0.883 (best in column)	0.768 (best in column)	0.155 (best in column)	0.882 (best in column)	0.394 (best in column)	0.873 (best in column)
MixingDTA (retrained on Davis and KIBA, PLABench)Evaluation	0.878	0.757	0.163	0.876	0.404	0.871
DeepDTA (retrained on Davis and KIBA, PLABench)Evaluation	0.831	0.657	0.23	0.818	0.479	0.798

All 18 result rows with coverage, uncertainty and sources

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: DeepDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.831 Concordance index (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'CI' (text-layer line 439)
Configuration: DeepDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.23 MSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'MSE' (text-layer line 439)
Configuration: DeepDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.818 Pearson (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'Pearson' (text-layer line 439)
Configuration: DeepDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.657 Modified squared correlation (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'rm2' (text-layer line 439)
Configuration: DeepDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.479 RMSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'RMSE' (text-layer line 439)
Configuration: DeepDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.798 Spearman (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DeepDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'DeepDTA', strategy 'Warm split', dataset 'KIBA', column 'Spearman' (text-layer line 439)
Configuration: LLF (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.883 Concordance index (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LLF on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'KIBA', column 'CI' (text-layer line 440)
Configuration: LLF (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.155 MSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LLF on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'KIBA', column 'MSE' (text-layer line 440)
Configuration: LLF (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.882 Pearson (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LLF on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'KIBA', column 'Pearson' (text-layer line 440)
Configuration: LLF (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.768 Modified squared correlation (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LLF on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'KIBA', column 'rm2' (text-layer line 440)
Configuration: LLF (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.394 RMSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LLF on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'KIBA', column 'RMSE' (text-layer line 440)
Configuration: LLF (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.873 Spearman (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LLF on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'LLF', strategy 'Warm split', dataset 'KIBA', column 'Spearman' (text-layer line 440)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.878 Concordance index (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'KIBA', column 'CI' (text-layer line 441)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.163 MSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'KIBA', column 'MSE' (text-layer line 441)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.876 Pearson (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'KIBA', column 'Pearson' (text-layer line 441)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.757 Modified squared correlation (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'KIBA', column 'rm2' (text-layer line 441)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.404 RMSE (PLABench KIBA-warm) unit-unreported · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'KIBA', column 'RMSE' (text-layer line 441)
Configuration: MixingDTA (retrained on Davis and KIBA, PLABench)	Protocol: PLABench KIBA, warm split Dataset: KIBA warm test set (PLABench)	0.871 Spearman (PLABench KIBA-warm) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MixingDTA on PLABench KIBA-warm lit-interactions-20261011-leakctl-protocol-kiba-warm Aggregation: Not reported Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Table 2, row 'MixingDTA', strategy 'Warm split', dataset 'KIBA', column 'Spearman' (text-layer line 441)

Source checking is not independent reproduction. Release 2026-10-23-5347695500ed.

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Leakage-controlled benchmarking reveals generalization limits of deep learning for protein-ligand binding affinity prediction · Original source · bioRxiv 10.64898/2026.09.17.752433v1 (posted 2026-09-23); 30-page PDF

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Technical metadata and extraction receipts

Stable ID: lit-interactions-20261011-leakctl-protocol-kiba-warm

areas: molecular-interactions
contexts: research
protocol: KIBA warm test set; MSE, RMSE, Pearson, Spearman, rm2 and CI as printed in Table 2
version: PLABench bioRxiv v1
limitations: Metrics are computed over all test pairs of the set (Methods, 'Evaluation metrics'); per-target averaging is not stated for these tables.; Only one value per cell is printed; no uncertainty is reported in Tables 2-4.; Only the three sequence-based models (DeepDTA, LLF, MixingDTA) were retrained on Davis and KIBA.
source locator: Table 2, 'KIBA' columns, strategy 'Warm split'

Related records

part of: PLABench
uses data: KIBA warm test set (PLABench)
assessment: DeepDTA on PLABench KIBA-warm
assessment: LLF on PLABench KIBA-warm
assessment: MixingDTA on PLABench KIBA-warm

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