RESUMEN
Massive parallel sequencing technologies are facilitating the faster identification of sequence variants with the consequent capability of untangling the molecular bases of many human genetic syndromes. However, it is not always easy to understand the impact of novel variants, especially for missense changes, which can lead to a spectrum of phenotypes. This study presents a custom-designed multistep methodology to evaluate the impact of novel variants aggregated in the genome aggregation database for the HBB, HBA2, and HBA1 genes, by testing and improving its performance with a dataset of previously described alterations affecting those same genes. This approach scored high sensitivity and specificity values and showed an overall better performance than sequence-derived predictors, highlighting the importance of protein conformation and interaction specific analyses in curating variant databases. This study also describes the strengths and limitations of these structural studies and allows identifying residues in the globin chains more prone to tolerate substitutions.