Data for "Peptide Assembly Design Algorithm: A User-Friendly Computational Tool for Discovering Amyloid-forming Peptides"

Data for publication: "Peptide Assembly Design Algorithm: A User-Friendly Computational Tool for Discovering Amyloid-forming Peptides" Contents: Section4.1: Complete PepAD design results for five independent runs and DMD/PRIME20 simulation results for five top-scoring peptides from each PepAD run Section4.2: Complete PepAD design results for five independent runs and DMD/PRIME20 simulation results for six top-scoring peptides from each PepAD run. Section4.3: Complete PepAD design results for four design conditions, with five independent runs performed for each condition. Section4.4: PepAD design results under varied aggregation prepensity weight (λ) and analysis notebook for evaluating the effect of λ on Metropolis acceptance and rejection. Section4.5: PepAD design results under varied temperature factor (kBT) and analysis notebook for evaluating the effect of kBT on peptide design. Section4.6: PepAD design results for ten independent runs with each being performed for 15000 step and analysis notebook for evaluating the PepAD convergence. SI_Redesign_Conf1_Conf2: PepAD peptide-redesign results obtained using the Conf-1 and Conf-2 initial structures reported by Sarma et al. (10.1002/pro.5102). SI_Relationship_between_score_and_Self-assembly: PepAD design results and DMD/PRIME20 simulations results for 14-mer peptides with single-site positional constraints, used to analyze the relationship between PepAD score and self-assembly.