Aggregation of M3 (E376D) variant of alpha1- antitrypsin

High-resolution characterization of ex vivo AAT polymers by solution-state NMR spectroscopy

Serpins, protease inhibitors whose regulated conformational instability renders them susceptible to mutations that cause misfolding, represent a system for the study of non-amyloid protein aggregation. The E342K "Z" variant of α-1-antitrypsin (AAT) undergoes oligomeric self-assembly into polymer chains that are associated with liver and lung pathologies in AAT deficiency. Structural characterization of polymers from human tissue has been limited by their heterogeneity and flexibility; here, we have studied their internal structure, which provides insights into the molecular linkage and the pathway by which they are formed. NMR spectra of heat-induced 13C-ILV-methyl-labeled polymers, and 1H-methyl spectra of liver-derived polymers, show equivalence to that of AAT in a post-protease-encounter conformation. This is corroborated by x-ray crystallography, which reveals a cryptic epitope recognized by the conformationally selective 2C1 antibody, common to both forms. These data definitively preclude most models of polymerization and are compatible with sequential intermolecular donation of the carboxyl terminus of one molecule into the next during polymer formation.

Making Proteins with Electricity

Ribosomes use multiple electrical forces to regulate new protein construction, to ensure efficient protein cotranslation, chaperoning, and folding. When these electrical regulatory forces are disrupted as in point charge mutations, specific disease occurs from aberrantly folded proteins. α1 antitrypsin deficiency is perhaps the best-known misfolded protein disease and is covered in some detail.

SARS-CoV-2 S protein harbors furin cleavage site located in a short loop between antiparallel β-strand

Furin cleavage site (FCS) of the SARS-CoV-2 S protein, which connects the S1/S2 junction, is essential for facilitating fusion with the host cells. Wild-type (Wt) SARS-CoV-2 S protein, PDB ID: 6yvb, lacks a sequence of amino acid residues, including the FCS that links the S1/S2 junction. For the first time, we demonstrated that a stretch of 14 amino acid residues (677QTNSPRRARSVASQ689) forms an antiparallel β-sheet comprising of PRRAR sequence in the FCS within a short loop. Upon comparing the loop content of the S1/S2 junction with that of Wt SARS-CoV-2 containing PRRAR in the FCS, we observed a decrease in antiparallel β-sheet content and an increase in loop content in the B.1.1.7 variant with HRRAR in the FCS. This short loop within antiparallel β-sheet can serve as a docking site for various proteases, including TMPRSS2 and α1AT. We performed a 300-ns simulation of the SARS-CoV-2 receptor binding domain (RBD) using several antibacterial and antiviral ligands commonly used to treat various infections. Our findings indicate that the receptor binding domain (RBD) comprising the receptor binding motif (RBM) utilizes β6 and a significant portion of the loop to bind with ligands, suggesting its potential for treating SARS-CoV-2 infections.

Computational Tools to Assist in Analyzing Effects of the SERPINA1 Gene Variation on Alpha-1 Antitrypsin (AAT)

In the rapidly advancing field of bioinformatics, the development and application of computational tools to predict the effects of single nucleotide variants (SNVs) are shedding light on the molecular mechanisms underlying disorders. Also, they hold promise for guiding therapeutic interventions and personalized medicine strategies in the future. A comprehensive understanding of the impact of SNVs in the SERPINA1 gene on alpha-1 antitrypsin (AAT) protein structure and function requires integrating bioinformatic approaches. Here, we provide a guide for clinicians to navigate through the field of computational analyses which can be applied to describe a novel genetic variant. Predicting the clinical significance of SERPINA1 variation allows clinicians to tailor treatment options for individuals with alpha-1 antitrypsin deficiency (AATD) and related conditions, ultimately improving the patient's outcome and quality of life. This paper explores the various bioinformatic methodologies and cutting-edge approaches dedicated to the assessment of molecular variants of genes and their product proteins using SERPINA1 and AAT as an example.

Improved NMR-data-compliant protein structure modeling captures context-dependent variations and expands the scope of functional inference

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state-of-the-art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph-based modeling approach, where we first build substructures from NMR-derived distance-geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance-geometry constraints. One-shot structure building is rarely undertaken for large and sparse data systems, but our data-driven bottom-up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state-of-art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein-folds covering 38-282 length structures shows minimal experimental-constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state-of-art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure-function. Our work is thus useful in building enhanced NMR-evidence-based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference.

Molecular characterization of PI * S hangzhou , a SERPINA1 allele from continental China encoding a defective alpha-1-antitrypsin

Alpha-1-antitrypsin deficiency (AATD) is a heritable condition that predisposes to respiratory and hepatic complications. Screenings in East Asia human populations for the AATD alleles most commonly found among Caucasians have yielded poor outcomes. Serum alpha-1-antitrypsin (AAT) levels, AAT phenotypes, and sequences of SERPINA1 gene were examined in a Chinese child with a moderate deficit of serum AAT, who had suffered several episodes of liver disease, as well as in his first-order relatives. Results allowed the identification of PI ^* S _hangzhou , a novel SERPINA1 defective allele, which has been characterized by a L276R substitution, found in a SERPINA1-M3 genetic background. Moreover, potential effects of PI ^* S _hangzhou mutation over the AAT structure were studied by 3D homology modeling. The presence of an arginine residue at position 276 could destabilize the tertiary structure of AAT, since it occurs at a highly conserved hydrophobic cavity in the protein surface, and very close to two positively-charged lysine residues. Attending to the frequency of R276 variant reported in databases for individuals of East Asian ancestry, the PI ^* S _hangzhou allele may explain the global prevalence of the PiS phenotype observed in China.