Abstract
Genetic variation in alpha-1 antitrypsin (AAT) causes AAT deficiency (AATD) through liver aggregation-associated gain-of-toxic pathology and/or insufficient AAT activity in the lung manifesting as chronic obstructive pulmonary disease (COPD). Here, we utilize 71 AATD-associated variants as input through Gaussian process (GP)-based machine learning to study the correction of AAT folding and function at a residue-by-residue level by pharmacological activation of the ATF6 arm of the unfolded protein response (UPR). We show that ATF6 activators increase AAT neutrophil elastase (NE) inhibitory activity, while reducing polymer accumulation for the majority of AATD variants, including the prominent Z variant. GP-based profiling of the residue-by-residue response to ATF6 activators captures an unexpected role of the "gate" area in managing AAT-specific activity. Our work establishes a new spatial covariant (SCV) understanding of the convertible state of the protein fold in response to genetic perturbation and active environmental management by proteostasis enhancement for precision medicine.