Remodeling the Proteostasis Network to Rescue Glucocerebrosidase Variants by Inhibiting ER-Associated Degradation and Enhancing ER Folding

Gaucher’s disease (GD) is characterized by loss of lysosomal glucocerebrosidase (GC) activity. Mutations in the gene encoding GC destabilize the protein’s native folding leading to ER-associated degradation (ERAD) of the misfolded enzyme. Enhancing the cellular folding capacity by remodeling the proteostasis network promotes native folding and lysosomal activity of mutated GC variants. However, proteostasis modulators reported so far, including ERAD inhibitors, trigger cellular stress and lead to induction of apoptosis. We show herein that lacidipine, an L-type Ca2+ channel blocker that also inhibits ryanodine receptors on the ER membrane, enhances folding, trafficking and lysosomal activity of the most severely destabilized GC variant achieved via ERAD inhibition in fibroblasts derived from patients with GD. Interestingly, reprogramming the proteostasis network by combining modulation of Ca2+ homeostasis and ERAD inhibition remodels the unfolded protein response and dramatically lowers apoptosis induction typically associated with ERAD inhibition

Calculation of the Free Energy and Cooperativity of Protein Folding

Calculation of the free energy of protein folding and delineation of its pre-organization are of foremost importance for understanding, predicting and designing biological macromolecules. Here, we introduce an energy smoothing variant of parallel tempering replica exchange Monte Carlo (REMS) that allows for efficient configurational sampling of flexible solutes under the conditions of molecular hydration. Its usage to calculate the thermal stability of a model globular protein, Trp cage TC5b, achieves excellent agreement with experimental measurements. We find that the stability of TC5b is attained through the coupled formation of local and non-local interactions. Remarkably, many of these structures persist at high temperature, concomitant with the origin of native-like configurations and mesostates in an otherwise macroscopically disordered unfolded state. Graph manifold learning reveals that the conversion of these mesostates to the native state is structurally heterogeneous, and that the cooperativity of their formation is encoded largely by the unfolded state ensemble. In all, these studies establish the extent of thermodynamic and structural pre-organization of folding of this model globular protein, and achieve the calculation of macromolecular stability ab initio, as required for ab initio structure prediction, genome annotation, and drug design