Figure_GRO_files

The data provided here is the starting and final coordinate files of the 100 ns and 200 ns simulations in form of GRO files. They are readable with VMD and other molecular visualisation software.The input parameters for simulating these peptides are described in detail in the paper "Reshaping the discovery of self-assembling peptides with generative AI guided by hybrid deep learning", in the Methods section.The figures from the paper that use these simulations are as follows:<br>Figure 6 c) and d) used centred versions of files FMGIIF_c_0ns, FMGIIF_c_200, FATAAGGNNF_c_0ns, and FATAAGGNNF_c_200. The centred files are also added into a separate file Figure_6cd_GRO_files.Figure S1.8 c) and d) use all files in the "High SA propensity peptides" folder except FMGIIF and FATAAGGNNF and uses the same peptides from the "100 ns simulations" folder.Figure S1.9 uses the decapeptides present in the "Low SA propensity peptides" folder.<br>Figure S1.10 uses the hexapeptides present in the "Low SA propensity peptides" folder.<br><br>The data present in the paper was drawn from the exact simulations present in these folders. The main data was derived from the 200 ns simulations, while the 100 ns simulations were compared to the 200 ns ones in figure S1.8 a) and b).<br>