This study not only proposes an efficient protocol to investigate structural consequences related to cancer-associated protein variants with the support of cutting-edge artificial intelligence tools (i.e., AF2) but also highlights a few mutations that could more likely negatively modulate the binding of SASH1-Sam1 to EphA2-Sam and that can be thus prioritized in experimental studies. This evidence concerns the gene EPHA2 and cancer.