Substrate secondary structure is associated with proteasomal cleavage propensity.

Why does the proteasome cleave proteins at some peptide bonds but not others? Prior work has emphasized sequence motifs, amino acid properties, and proteasome isoform, but the role of local secondary-structure context remains unclear. Here, we evaluate whether helix, strand, and coil context help explain proteasomal cleavage and whether such information can improve cleavage-site prediction. By mining a human and viral PDB structure corpus, we found that high-confidence predicted cleavage sites are enriched in beta-strand extended conformations and depleted in coil-like regions. We then trained a machine learning model using only secondary-structure labels, and benchmarked its performance against a sequence-aware baseline, other well-known predictors, and ensemble approaches using hybrid position-specific scoring matrices (PSSMs). Our proof-of-concept SSO-8 model was trained on secondary structure features predicted by NetSurfP-3.0 for 8-mer sequences derived from a diverse experimental digestion dataset of 20 substrate proteins. SSO-8 reached AUC = 0.649 on a held-out benchmark constitutive dataset and AUC = 0.737 on a held-out immunoproteasome dataset. A same-protocol sequence-only model reached AUC of 0.674 and 0.736, respectively, and paired peptide/protein-level tests found no evidence of a significant SSO-8-vs-sequence difference. Our model was also competitive with other sequence-based proteasomal prediction methods, using different training sets and architectures. Therefore, secondary-structure-only information captured substantial cleavage signal despite using much less input information than full substrate sequence, with the clearest support in the immunoproteasome dataset and hybrid PSSM analyses. These results extend the known preference for extended active-site geometry by showing an association between local substrate backbone conformation and proteasomal cleavage propensities, particularly in the context of the immunoproteasome, and suggest the use of sequence-encoded secondary-structure propensities as a measurable feature of proteasomal cleavage preferences.