Fig. 5: Rosetta FlexPepDock evaluation of C-terminal peptide extensions generated by the three fine-tune models in comparison with the Pretrain model. | Nature Communications

Fig. 5: Rosetta FlexPepDock evaluation of C-terminal peptide extensions generated by the three fine-tune models in comparison with the Pretrain model.

From: Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations

Fig. 5

a Workflow of the three fine-tune models for C-terminal extension, and comparisons of enrichment results analyzed by rank difference distributions for C-terminal extensions generated by various models. b Distributions of the three Rosetta FlexPepDock binding metric scores evolving during the fine-tuning process for YPEDILDKHLQRV-based extension. c Distributions of the three Rosetta FlexPepDock binding metric scores evolving during the fine-tuning process for YPEDILDKHLQRVIL-based extension. Only the top 10% Rosetta FlexPepDock scores are plotted. The green line represents a cutoff for selecting peptides subjected to MM/GBSA evaluation (rmsALL_if < −0.2 Å; I_sc < −6 REU; I_bsa > 250 Å2). Sample sizes in (a) for YPEDILDKHLQRVIL-based extension and YPEDILDKHLQRV-based extension are n = 1840 and n = 2480, respectively. Sample sizes in (b, c) are n = 400. Source data are provided as a Source Data file.

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