Mapping pathogenic patterns in membrane transporters from the GLUT transporter family

Abstract

Significance Missense mutations can lead to pathological effects in human cells. Predictive methods that account for structural context, such as AlphaMissense, can provide pathogenicity scores. The accumulation of pathogenicity hotspots can reveal important structural features within individual proteins of protein families, such as GLUT transporters. Mapping pathogenicity scores onto the structure can thus provide a mechanistic explanation of the protein function necessary for its role in the cell. Abstract Non-synonymous amino acid substitutions (missense mutations) are common in the general population; some are causative of serious disease. Depending on their structural context, they can disrupt protein function, folding, or dynamics. Computational predictive methods developed in recent years, such as AlphaMissense, provide new insights into how missense mutations affect protein structure by predicting and mapping their pathogenicity across each amino acid in the human proteome. In this study, we identify recurring patterns of pathogenicity prediction across the GLUT family membrane transporters encoded by genes SLC2A1-14. Within the GLUT transporter family, we observe higher pathogenicity profiles in the transmembrane domains, particularly in pore-lining and binding-site residues. Predicted missense pathogenicity is elevated throughout residues assigned to the central cavity, suggesting sensitivity of the transport pathway. Another finding shows higher pathogenicity in specific transmembrane helices of the protein, with the same pattern across all proteins. On the other hand, we observed lower pathogenicity values in some representatives of the GLUT family. We validated these predictions against clinically observed missense variants from ClinVar and benchmarked three prediction methods. AlphaMissense showed the strongest concordance with clinical classifications (AUC = 0.88), and the structural distribution of clinically reported pathogenic variants broadly recapitulated the predicted pathogenicity landscape. On the other hand, we observed lower pathogenicity values in some representatives of the GLUT family, and in select cases, clinical and predicted data diverged, suggesting more localized functional constraint than genome-wide prediction alone would indicate. These findings show that the pathogenicity of glucose transport within the GLUT family may be shaped by functional redundancy and physiological essentiality across GLUT groups, supported by convergent evidence from structural, computational, and clinical variant data.