Supplements for "Multimodal Classification of Protein–Protein Interactions Reveals Regulatory Hierarchies in Oncogenic Signaling"

This supplementary file contains Table S1–S3 and Figure S1 related to the manuscript entitled “Multimodal Classification of Protein–Protein Interactions Reveals Regulatory Hierarchies in Oncogenic Signaling.” The study introduces a multimodal framework integrating AlphaFold3-predicted structural affinity, ClustalW-derived evolutionary distance, and catRAPID-predicted ncRNA interference to classify protein–protein interactions (PPIs) into physiological, pathological, and mutant categories. Table S1 summarizes structural and regulatory scores across 294 cancer-related PPIs.Table S2 presents detailed comparative data on Rb1–E2F1 vs Rb1–HPV16 E7 interactions.Table S3 provides affinity-distance correlation metrics.Figure S1 shows AlphaFold3-predicted 3D structures of the Rb1–E2F1 and Rb1–E7 complexes. These data support the central hypothesis that ncRNA-mediated regulatory buffering plays a critical role in stabilizing physiological PPIs while pathological ones escape control, contributing to oncogenic progression.