With the advent of AlphaFold2 (AF2) and its subsequent implementation in ColabFold , we could predict the tridimensional peptide structures of our benchmarking dataset. ColabFold batch mode allowed us to simultaneously predict the tridimensional structures for our 261 GRAMPA sequences. For each sequence, we picked the three best AF2 predictions with the highest pLDDT (local distancedependent transition) scores. These values reflect the reliability of the predictions made by the algorithm between protein structures. The pLDDT values range from 0 to 1, with higher values indicating more accurate AF2 predictions. We could observe pLDDT scores per residue and averaged across the entire peptide sequence. In order to compare our newly predicted AF2 structures to the protein secondary structure predictions, we submitted each selected AF2 structure to the STRIDE webserver and measured the 3-state secondary structures (H, E, C) of each structure. The selected 261 AF2 predictions, their pLDDT scores and corresponding STRIDE assessments were summarised in Table . In Figure , we depicted the AF2+STRIDE predictions (cyan) against experimental distributions (blue) across the three secondary structure states (H, E, C). The results indicated that AF2+STRIDE outperformed PEP2D with its predictions closer to the experimental distributions for the helical and stranded states (respective JSD values of 0.266 and 0.255). In contrast, all three PSSP methods accounted for better predictions of the coiled state than AF2+STRIDE (C: JSD = 0.255). Our results corroborate the recent findings by McDonald and co-workers regarding the performance of AlphaFold2 in predicting 588 peptide structures between 10 and 40 amino acids . The authors also reported that AF2 predicted helical (H) and stranded/β-sheets structures with high accuracy, but the program failed with segments presenting low pLDDT scores, often associated with coils (C). Our approach combining AlphaFold2 and STRIDE was more time-consuming and computerintensive than PSSP methods. Despite these shortcomings, the coupled method represents an excellent alternative to PEP2D, particularly for peptide sequences with 50 or more residues.