We also evaluated the effects of incorporating structural insights from Modi & Dunbrack's MSA on model performance through padding and trimming. The application of both procedures did not yield significant improvements in F1-score or AUROC between the original and modified embeddings (Table and Supp. Tables S2 and S3), and while trimming appeared to affect PFI across different SNA conditions and data splits, these results were not confirmed by pairwise comparisons (Supp. Tables and). Ultimately, our results suggest that while padding and trimming modify structural representations within the embeddings, they do not conclusively enhance the predictive performance of the ML models.