Biology subjects

Skiba, M. A.

Publications and source records attributed to Skiba, M. A..

3 recordsLinked to original sources

bioRxiv2022

A Fusion Protein Platform for Analyzing Tethered Agonism in the Adhesion Family of G Protein-Coupled Receptors

Adhesion G Protein-Coupled Receptor (aGPCR) signaling influences development and homeostasis in a wide range of tissues. In the current model for aGPCR signaling, ligand binding liberates or unmasks a highly conserved tethered agonist (TA) that acts as an intramolecular ligand to stimulate G protein coupling. However, a systematic, comprehensive examination of signaling has not been performed for all aGPCR family members. Here, we report a platform for profiling TA-dependent activities of aGPCRs in several different assays and apply it to all 33 human family members. Activity profiling identified a heterogeneity of responses among these aGPCRs, with only [~]50% showing robust, TA-dependent signals. AlphaFold2 predictions assessing TA engagement in the predicted intramolecular binding pocket aligned with the TA-dependence of the cellular responses. The signaling information in this dataset is a comprehensive resource relevant for the investigation of all human aGPCRs and for targeting aGPCRs therapeutically.

biochemistry↗

bioRxiv2022

Metal cofactor stabilization by a partner protein is a widespread strategy employed for amidase activation

Construction and remodeling of the bacterial peptidoglycan (PG) cell wall must be carefully coordinated with cell growth and division. Central to cell wall construction are hydrolases that cleave bonds in peptidoglycan. These enzymes also represent potential new antibiotic targets. One such hydrolase, the amidase LytH in Staphylococcus aureus, acts to remove stem peptides from PG, controlling where substrates are available for insertion of new PG strands and consequently regulating cell size. When it is absent, cells grow excessively large and have division defects. For activity, LytH requires a protein partner, ActH, that consists of an intracellular domain, a large rhomboid protease domain, and three extracellular tetratricopeptide repeats (TPRs). Here we demonstrate that the amidase-activating function of ActH is entirely contained in its extracellular TPRs. We show that ActH binding stabilizes metals in the LytH active site, and that LytH metal binding in turn is needed for stable complexation with ActH. We further present a structure of a complex of the extracellular domains of LytH and ActH. Our findings suggest that metal cofactor stabilization is a general strategy used by amidase activators and that ActH houses multiple functions within a single protein. SIGNIFICANCE STATEMENTThe Gram-positive pathogen Staphylococcus aureus is a leading cause of antibiotic resistance-associated death in the United States. Many antibiotics used to treat S. aureus, including the beta-lactams, target biogenesis of the essential peptidoglycan (PG) cell wall. Some hydrolases play important roles in cell wall construction and are potential antibiotic targets. The amidase LytH, which requires a protein partner, ActH, for activity, is one such hydrolase. Here, we uncover how the extracellular domain of ActH binds to LytH to stabilize metals in the active site for catalysis. This work advances our understanding of how hydrolase activity is controlled to contribute productively to cell wall synthesis.

microbiology↗

bioRxiv2022

An in silico method to assess antibody fragment polyreactivity

Antibodies are essential biological research tools and important therapeutic agents, but some exhibit non-specific binding to off-target proteins and other biomolecules. Such polyreactive antibodies compromise screening pipelines, lead to incorrect and irreproducible experimental results, and are generally intractable for clinical development. We designed a set of experiments using a diverse naive synthetic camelid antibody fragment ( nanobody) library to enable machine learning models to accurately assess polyreactivity from protein sequence (AUC > 0.8). Moreover, our models provide quantitative scoring metrics that predict the effect of amino acid substitutions on polyreactivity. We experimentally tested our models performance on three independent nanobody scaffolds, where over 90% of predicted substitutions successfully reduced polyreactivity. Importantly, the model allowed us to diminish the polyreactivity of an angiotensin II type I receptor antagonist nanobody, without compromising its pharmacological properties. We provide a companion web-server that offers a straightforward means of predicting polyreactivity and polyreactivity-reducing mutations for any given nanobody sequence.

pharmacology and toxicology↗