Research Highlights

An isothermal calorimetry assay for determining steady state kinetic and Ensitrelvir inhibition parameters for SARS-CoV-2 3CL-protease

This manuscript details the application of Isothermal Titration Calorimetry (ITC) to characterize the kinetics of 3CL^pro, the main protease from the Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2), and its inhibition by Ensitrelvir, a known non-covalent inhibitor. 3CL^pro is essential for producing the proteins necessary for viral infection, which led to the COVID-19 pandemic. The ITC-based assay provided rapid and reliable measurements of 3CL^pro activity, allowing for the direct derivation of the kinetic enzymatic constants K_M and k_cat by monitoring the thermal power required to maintain a constant temperature as the substrate is consumed.

Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data 

Recent advances in molecular modeling of protein structures are changing the field of structural biology. AlphaFold-2 (AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy. Since AF2 was trained on X-ray crystal and cryoEM structures, we assessed how accurately AF2 can model small, monomeric, solution protein NMR structures which (i) were not used in the AF2 training data set, and (ii) did not have homologous structures in the Protein Data Bank at the time of AF2 training.  In most of the cases investigated, the AF2 models fit the NMR data nearly as well, or sometimes better than, the corresponding NMR structure models previously deposited in the Protein Data Bank. These results provide benchmark NMR data for assessing new NMR data analysis and protein structure prediction methods.