Fig. 4: MD simulations of β-catenin bound with the four experimentally tested peptides. | Nature Communications

Fig. 4: MD simulations of β-catenin bound with the four experimentally tested peptides.

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

Fig. 4

a Workflow of our N-terminal extension design process. b MM/GBSA results of the top 10 Rosetta FlexPepDock-scored peptide extensions. Error bars represent standard deviations (from left to right in kcal/mol: 8.5, 5.9, 3, 8.2, 6.7, 8.9, 8.5, 5.4, 8.1, 2). The green horizontal line denotes the threshold cutoff of −40 kcal/mol. c Ending pose of the best N-terminally extended peptide NAL-9 bound to β-catenin after 500 ns of MD simulation. d Initial and final structures along with their superimposition of the best peptide NAL-9 bound to β-catenin during the MD simulation. e Initial and final structures along with their superimposition of the worst peptide NAL-10 bound to β-catenin during the MD simulation. Extension residues and β-catenin residues crucial to binding are labeled and represented in stick. In (b), whiskers indicate standard deviations for triplet measurements. Source data are provided as a Source Data file.

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