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We performed molecular dynamics simulations of Reteplase in the presence of different excipients to study the stabilizing mechanisms and to identify the role of excipients during freeze drying. To simulate the freeze-drying process, we divided the process into five distinct steps: (i) protein–excipient formulations at room temperature, (ii) the ice-growth process, (iii)–(iv) the partially solvated and fully dried formulations, and (v) the reconstitution. Furthermore, coarse-grained (CG) simulations were employed to explore the protein-aggregation process in the presence of arginine. By using a coarse-grained representation, we could observe the collective behavior and interactions between protein molecules during the aggregation process. The CG simulations revealed that the presence of arginine prevented intermolecular interactions of the catalytic domain of Reteplase, thus reducing the aggregation propensity. This suggests that arginine played a stabilizing role by interacting with protein-specific regions. From the freeze-drying simulations, we could identify several protein-specific events: (i) collapse of the domain structure, (ii) recovery of the drying-induced damages during reconstitution, and (iii) stabilization of the local aggregation-prone region via direct interactions with excipients. Complementary to the simulations, we employed nanoDSF, size-exclusion chromatography, and CD spectroscopy to investigate the effect of the freeze-drying process on the protein structure and stability.

Nirmatrelvir, which targets the SARS-CoV-2 main protease (Mpro), is the first-in-line drug for prevention and treatment of severe COVID-19, and additional Mpro inhibitors are in development. However, the risk of resistance development threatens the future efficacy of such direct-acting antivirals. To gain knowledge on viral correlates of resistance to Mpro inhibitors, we selected resistant SARS-CoV-2 under treatment with the nirmatrelvir-related protease inhibitor boceprevir. SARS-CoV-2 selected during five escape experiments in VeroE6 cells showed cross-resistance to nirmatrelvir with up to 7.3-fold increased half-maximal effective concentration compared to original SARS-CoV-2, determined in concentration-response experiments. Sequence analysis revealed that escape viruses harbored Mpro substitutions L50F and A173V. For reverse genetic studies, these substitutions were introduced into a cell-culture-infectious SARS-CoV-2 clone. Infectivity titration and analysis of genetic stability of cell-culture-derived engineered SARS-CoV-2 mutants showed that L50F rescued the fitness cost conferred by A173V. In the concentration-response experiments, A173V was the main driver of resistance to boceprevir and nirmatrelvir. Structural analysis of Mpro suggested that A173V can cause resistance by making boceprevir and nirmatrelvir binding less favorable. This study contributes to a comprehensive overview of the resistance profile of the first-in-line COVID-19 treatment nirmatrelvir and can thus inform population monitoring and contribute to pandemic preparedness.

Here, we propose an optimised protocol for controlling the initial water activity (aw) in organic reaction mixtures with soluble lipase to ensure reproducible and consistent enzyme activity measurements. Pre-equilibration above saturated salt solutions was used to set aw of the reaction media, where aw was tracked with a hygrometer. Consistent stirring of the suspension and volume correction to compensate for solvent evaporation were found to be critical. The protocol was tested on Candida antarctica lipase B (CALB) in soluble and immobilised forms in three organic solvents (acetonitrile, methyl tert-butyl ether, and hexane) at four different water activities ranging from 0.12 to 0.97. Soluble and immobilised CALB had similar aw-profiles and showed the highest enzyme activity in hexane. The optimised protocol expands the possibility to study enzyme kinetics from immobilised enzymes to soluble enzymes.

Therapeutic proteins can be challenging to develop due to their complexity and the requirement of an acceptable formulation to ensure patient safety and efficacy. To date, there is no universal formulation development strategy that can identify optimal formulation conditions for all types of proteins in a fast and reliable manner. In this work, high-throughput characterization, employing a toolbox of five techniques, was performed on 14 structurally different proteins formulated in 6 different buffer conditions and in the presence of 4 different excipients. Multivariate data analysis and chemometrics were used to analyze the data in an unbiased way. First, observed changes in stability were primarily determined by the individual protein. Second, pH and ionic strength are the two most important factors determining the physical stability of proteins, where there exists a significant statistical interaction between protein and pH/ionic strength. Additionally, we developed prediction methods by partial least-squares regression. Colloidal stability indicators are important for prediction of real-time stability, while conformational stability indicators are important for prediction of stability under accelerated stress conditions at 40 °C. In order to predict real-time storage stability, protein–protein repulsion and the initial monomer fraction are the most important properties to monitor.

We have performed a series of multiple molecular dynamics (MD) simulations of glucagon-like peptide-1 (GLP-1) and acylated GLP-1 analogues in complex with the endogenous receptor (GLP-1R) to obtain a molecular understanding of how fatty acid (FA) chain structure, acylation position on the peptide, and presence of a linker affect the binding. MD simulations were analysed to extract heatmaps of receptor–peptide interaction patterns and to determine the free energy of binding using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach. The extracted free energies from MM-PBSA calculations are in qualitative agreement with experimentally determined potencies. Furthermore, the interaction patterns seen in the receptor–GLP-1 complex simulations resemble previously reported binding interactions validating the simulations. Analysing the receptor–GLP-1 analogue complex simulations, we found that the major differences between the systems stem from FA interactions and positioning of acylation in the peptide. Hydrophobic interactions between the FA chain and a hydrophobic patch on the extracellular domain contribute significantly to the binding affinity. Acylation on Lys26 resulted in noticeably more interactions between the FA chain and the extracellular domain hydrophobic patch than found for acylation on Lys34 and Lys38, respectively. The presence of a charged linker between the peptide and FA chain can potentially stabilise the complex by forming hydrogen bonds to arginine residues in the linker region between the extracellular domain and the transmembrane domain. A molecular understanding of the fatty acid structure and its effect on binding provides important insights into designing acylated agonists for GLP-1R. Communicated by Ramaswamy H. Sarma.

The oral protease inhibitor nirmatrelvir is of key importance for prevention of severe coronavirus disease 2019 (COVID-19). To facilitate resistance monitoring, we studied severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) escape from nirmatrelvir in cell culture. Resistant variants harbored combinations of substitutions in the SARS-CoV-2 main protease (Mpro). Reverse genetics revealed that E166V and L50F + E166V conferred high resistance in infectious culture, replicon, and Mpro systems. While L50F, E166V, and L50F + E166V decreased replication and Mpro activity, L50F and L50F + E166V variants had high fitness in the infectious system. Naturally occurring L50F compensated for fitness cost of E166V and promoted viral escape. Molecular dynamics simulations revealed that E166V and L50F + E166V weakened nirmatrelvir-Mpro binding. Polymerase inhibitor remdesivir and monoclonal antibody bebtelovimab retained activity against nirmatrelvir-resistant variants, and combination with nirmatrelvir enhanced treatment efficacy compared to individual compounds. These findings have implications for monitoring and ensuring treatments with efficacy against SARS-CoV-2 and emerging sarbecoviruses.