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Azouz, L. R.

Publications and source records attributed to Azouz, L. R..

3 recordsLinked to original sources

Massively parallel, computationally-guided design of a pro-enzyme

Confining the activity of a designed protein to a specific microenvironment would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as inactive zymogens that can be activated by proteolysis, it has been challenging to re-design any chosen enzyme to be similarly stimulus-responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for pro-enzyme design. As a model system, we employ carboxypeptidase G2 (CPG2), a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug toxicity. Detailed kinetic characterization of the most effective designed variants shows that they are inhibited by approximately 80% compared to the unmodified protein, and their activity is fully restored following incubation with site-specific proteases. Introducing disulfide bonds between the pro-and catalytic domains based on the design models increases the degree of inhibition to 98%, but decreases the degree of restoration of activity by proteolysis. A selected disulfide-containing pro-enzyme exhibits significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization provides detailed insights into the pro-domain binding and inhibition mechanisms. The described methodology is general and could enable the design of a variety of pro-proteins with precise spatial regulation. SignificanceProteins have shown promise as therapeutics and diagnostics, but their effectiveness is limited by our inability to spatially target their activity. To overcome this limitation, we developed a computationally-guided method to design inactive "pro-enzymes" or "zymogens," which are activated through cleavage by a protease. Since proteases are differentially expressed in various tissues and disease states, including cancer, these pro-enzymes could be targeted to the desired microenvironment. We tested our method on the therapeutically-relevant protein, carboxypeptidase G2 (CPG2). We designed Pro-CPG2s that are inhibited by 80-98% and are partially to fully re-activatable following protease treatment. The developed methodology, with further refinements, could pave the way for routinely designing protease-activated protein-based therapeutics and diagnostics that act in a spatially controlled manner.

biophysics↗

Identification of a conserved neutralizing epitope present on spike proteins from highly pathogenic coronaviruses

Three pathogenic human coronaviruses have emerged within the last 20 years, with SARS-CoV-2 causing a global pandemic. Although therapeutic antibodies targeting the SARS-CoV-2 spike currently focus on the poorly conserved receptor-binding domain, targeting essential neutralizing epitopes on the more conserved S2 domain may provide broader protection. We report an antibody binding an epitope conserved in the pre-fusion core of MERS-CoV, SARS-CoV and SARS-CoV-2 spike S2 domains. Antibody 3A3 binds a conformational epitope with ~2.5 nM affinity and neutralizes spike from SARS-CoV, SARS-CoV-2 and variants of concern in in vitro pseudovirus assays. Hydrogen-deuterium exchange mass spectrometry identified residues 980-1006 in the flexible hinge region at the S2 apex as the 3A3 epitope, suggesting 3A3 prevents the S2 conformational rearrangements required for conversion to the spike post-fusion state and virus-host cell fusion. This work defines a conserved vulnerable site on the SARS-CoV-2 S2 domain and guides the design of pan-protective spike immunogens.

biochemistry↗

Impact of initial protein stability on local fitness landscapes

It is incompletely understood how biophysical properties like protein stability impact molecular evolution and epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. By contrast, nonspecific epistasis results when a mutation is influenced by a large number of non-local mutations. As most mutations are pleiotropic, the in vivo folding probability - governed by basal protein stability - is thought to determine activity-enhancing mutational tolerance, which implies that nonspecific epistasis is dominant. However, evidence exists for both specific and nonspecific epistasis as the prevalent factor, with limited comprehensive datasets to validate either claim. Using deep mutational scanning we probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE in which catalytic efficiencies are statistically indistinguishable but the enzyme variants have lower probabilities of folding in vivo. Local fitness landscapes show only slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific epistasis was predominant for the subset of mutations exhibiting positive sign epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon-dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes, and suggest that transcriptional-translational effects are an equally important determinant as stability in determining evolutionary outcomes.

evolutionary biology↗