Predictions from OrgNet+: towards robust protein stability prediction with convolutional neural networks
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1) Original Benchmarks (Non-augmented):Predictions for OrgNet+, OrgNet, and other structure-based methods on the S461 and S669 datasets, evaluated in direct and reverse mutation settings.OrgNet predictions are from Buyanov et al. (2025). Predictions from other methods are sourced from Iqbal et al. (2022, PROST). 2) Conformationally Augmented Benchmarks:Predictions for five conformational ensembles (Backrub, Boltz-2, iMod, MD, NOLB), reported per-ensemble for both direct and reverse settings.Evaluated models include: OrgNet+ (trained on the full augmented dataset), OrgNet+ (trained on individual S2648-derived ensembles), OrgNet, and RaSP.RaSP model and prediction scripts were obtained from: https://github.com/KULL-Centre/_2022_ML-ddG-Blaabjerg/



