STRUCTURAL HOTSPOT MAPPING OF MISSENSE VARIANTS IN SERPINA1: AN IN-SILICO FRAMEWORK LINKING SEQUENCE VARIATION, PROTEIN STABILITY AND SERPIN DYSFUNCTION

Abstract

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality globally, the major inherited cause is alpha-1 antitrypsin deficiency (AATD) which is caused by pathogenic variants of a protein called alpha-1 antitrypsin that is the main inhibitor of neutrophil elastase in the lung. NGS has revealed a large number of rare variants of SERPINA1 that are still not understood and need to be characterized, especially missense variants that may affect AAT protein folding, stability, secretion, polymerization and protease inhibitory function, and thus impair the ability of AAT to protect lung tissue from elastase-mediated damage. This review addresses various computational approaches in the characterization of rare missense variants of SERPINA1, including sequence-based pathogenicity prediction, protein stability estimation, 3D structural modeling, computation of molecular dynamics, and molecular docking with neutrophil elastase. The complementarity of these methods and their respective limitations are evaluated, and the integration of these methods into a systematic framework for variant prioritization is discussed. Substitutions in structurally or functionally important areas may lead to changes in protein stability and conformation, as shown by the computational analysis, and molecular dynamics modeling can show dynamic effects that may not be apparent in static structural models. But interpretation is still limited due to the lack of experimental validation, population biases in variant databases, and methodological heterogeneity of prediction tools. Standardized, integrative computational workflows and experimental validation are thus required to enhance functional interpretation of rare SERPINA1 variants and to select those that may be relevant to AATD-associated COPD susceptibility.