The sequence-based design of AMPs benefits from both simpler models and advanced algorithms, yet their outputs often converge on well-established determinants of membrane activity, such as cationicity and hydrophobicity . While simpler models often arrive at peptide sequences similar to already known AMPs, global approaches like the one of Das et al. demonstrate greater novelty by leveraging large unlabeled datasets. Effective AMP design often pairs basic physicochemical properties (e.g., hydrophobicity, net charge) with structural motifs and positional information. For instance, Fjell et al. achieved strong performance using computationally derived QSAR descriptors , with model accuracy largely unaffected by input 3D structures.