Drug substance degradation kinetics in solid dosage forms is rarely mechanistically modeled due to several potential micro-environmental and manufacturing related effects that need to be integrated into rate laws. The aim of our work was to construct a model capable of predicting individual degradation product concentrations, taking into account also formulation composition parameters. A comprehensive study was done on active film-coated tablets, manufactured by layering of the drug substance, a primary amine compound saxagliptin, onto inert tablet cores. Formulation variables like polyethylene glycol (PEG) 6000 amount and film-coat polymer composition are incorporated into the model, and are connected to saxagliptin degradation, via formation of reactive impurities. Derived reaction equations are based on mechanisms supported by ab initio calculations of individual reaction activation energies. Alongside temperature, relative humidity, and reactant concentration, the drug substance impurity profile is dependent on micro-environmental pH, altered by formation of acidic PEG degradation products. A consequence of pH lowering, due to formation of formic acid, is lower formation of main saxagliptin degradation product epi-cyclic amidine, a better resistance of formulation to high relative humidity conditions, and satisfactory tablet appearance. Discovered insights enhance the understanding of degradational behavior of similarly composed solid dosage forms on overall drug product quality and may be adopted by pharmaceutical scientists for the design of a stable formulation.

The G₄C₂ hexanucleotide repeat expansion in the c9orf72 gene is a major genetic cause of familial amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), with the formation of G-quadruplexes directly linked to the development of these diseases. Cations play a crucial role in the formation and structure of G-quadruplexes. In this study, we investigated the impact of biologically relevant potassium ions on G-quadruplex structures and utilized ¹⁵N-labeled ammonium cations as a substitute for K⁺ ions to gain further insights into cation binding and exchange dynamics. Through nuclear magnetic resonance spectroscopy and molecular dynamics simulations, we demonstrate that the single d(G₄C₂) repeat, in the presence of ¹⁵NH₄⁺ ions, adopts a tetramolecular G-quadruplex with an all-syn quartet at the 5′-end. The movement of ¹⁵NH₄⁺ ions through the central channel of the G-quadruplex, as well as to the bulk solution, is governed by the vacant cation binding site, in addition to the all-syn quartet at the 5′-end. Furthermore, the addition of K⁺ ions to G-quadruplexes folded in the presence of ¹⁵NH₄⁺ ions induces stacking of G-quadruplexes via their 5′-end G-quartets, leading to the formation of stable higher-ordered species.

The misfolding, aggregation, and the seeded spread of alpha synuclein (α-Syn) aggregates are linked to the pathogenesis of various neurodegenerative diseases, including Parkinson’s disease (PD). Understanding the mechanisms by which chaperone proteins prevent the production and seeding of α-Syn aggregates is crucial for developing effective therapeutic leads for tackling neurodegenerative diseases. We show that a catalytically inactive variant of the chaperone HtrA1 (HtrA1*) effectively inhibits both α-Syn monomer aggregation and templated fibril seeding, and demonstrate that this inhibition is mediated by synergistic interactions between its PDZ and Protease domains and α-Syn. Using biomolecular NMR, AFM and Rosetta-based computational analyses, we propose that the PDZ domain interacts with the C-terminal end of the monomer and the intrinsically disordered C-terminal domain of the α-Syn fibril. Furthermore, in agreement with sequence specificity calculations, the Protease domain cleaves in the aggregation-prone NAC domain at site T92/A93 in the monomer. Thus, through multi-pronged interactions and multi-site recognition of α-Syn, HtrA1* can effectively intervene at different stages along the α-Syn aggregation pathway, making it a robust inhibitor of α-Syn aggregation and templated seeding. Our studies illustrate, at high resolution, the crucial role of HtrA1 interactions with both the intrinsically disordered α-Syn monomers and with the dynamic flanking regions around the fibril core for inhibition of aggregation. This inhibition mechanism of the HtrA1 chaperone may provide a natural mechanistic blueprint for highly effective therapeutic agents against protein aggregation. Significance Statement PD and other synucleinopathies are marked by misfolding and aggregation of α-Syn, forming higher-order species that propagate aggregation in a prion-like manner. Understanding how chaperone proteins inhibit α-Syn aggregation and spread is essential for therapeutic development against neurodegeneration. Through an integrative approach of solution-based NMR, AFM, aggregation kinetics, and computational analysis, we reveal how a catalytically inactive variant of the chaperone HtrA1 effectively disrupts aggregation pathways. We find that the inactive Protease and PDZ domains of HtrA1 synergistically bind to key intrinsically disordered sites on both α-Syn monomers and fibrils, thereby effectively inhibiting both aggregation and templated seeding. Our work provides a natural and unique blueprint for designing inhibitors to prevent the formation and seeding of aggregates in neurodegenerative diseases.

The ongoing evolution of SARS-CoV-2 has given rise to variants with enhanced transmissibility and pathogenicity, many of which harbor mutations in the receptor-binding domain (RBD) of the viral spike protein. These mutations often confer increased viral fitness and immune evasion by modulating interactions with the human ACE2 receptor (hACE2) and escaping neutralizing antibodies. Accurate prediction of the functional consequences of such mutations—particularly their effects on receptor binding and antibody escape—is critical for assessing the public health threat posed by emerging variants. In this study, we apply a Mutation-dependent Biomacromolecular Quantitative Structure–Activity Relationship (MB-QSAR) framework to quantitatively model the biochemical phenotypes of RBD variants. Trained on comprehensive deep mutational scanning (DMS) datasets, our models exhibit strong predictive performance, achieving correlation coefficients (r²) exceeding 0.8 for hACE2 binding affinity and 0.7 for antibody neutralization escape. Importantly, the MB-QSAR approach generalizes well to multi-mutant variants and currently circulating lineages. Structural analysis based on model-derived interaction profiles offers mechanistic insights into key RBD–ACE2 and RBD–antibody interfaces, helping the rational design of broadly protective vaccines and therapeutics. This work establishes MB-QSAR as a rapid, accurate, and interpretable tool for the prediction of protein–protein interaction and forecasting viral adaptation, thereby facilitating early risk assessment of novel SARS-CoV-2 variants.