Using these correlation coefficients it is possible to further characterise the ordering of the latent space and define directions along which interpolation should occur such that desirable characteristics will emerge from generated peptides. Each PC can be interpreted as a linear combination of the respective model's latent dimensions . From this interpretation it is possible to construct a direct relation between the latent dimensions of the model and the physicochemical properties investigated through the PCA mapping; we have made the PCA mappings themselves available on the project Github repository, .