SARS-CoV-2 3CLpro mutations selected in a VSV-based system confer resistance to nirmatrelvir, ensitrelvir, and GC376.

Protease inhibitors are among the most powerful antiviral drugs. Nirmatrelvir is the first protease inhibitor against the SARS-CoV-2 protease 3CLpro that has been licensed for clinical use. To identify mutations that confer resistance to this protease inhibitor, we engineered a chimeric vesicular stomatitis virus (VSV) that expressed a polyprotein composed of the VSV glycoprotein G, the SARS-CoV-2 3CLpro, and the VSV polymerase L. Viral replication was thus dependent on the autocatalytic processing of this precursor protein by 3CLpro and release of the functional viral polymerase L, and replication of this chimeric VSV was effectively inhibited by nirmatrelvir. Using this system, we applied nirmatrelvir to select for resistance mutations. Resistance was confirmed by retesting nirmatrelvir against the selected mutations in an additional VSV-based systems, in an independently developed cellular system, in a biochemical assay, and in a recombinant SARS-CoV-2 system. We demonstrate that some mutants are cross-resistant to ensitrelvir and GC376, whereas others are less resistant to these compounds. Furthermore, we found that most of these resistance mutations already existed in SARS-CoV-2 sequences that have been deposited in the NCBI and GISAID databases, indicating that these mutations were present in circulating SARS-CoV-2 strains.

A VSV-based assay quantifies coronavirus Mpro/3CLpro/Nsp5 main protease activity and chemical inhibition.

Protease inhibitors are among the most powerful antiviral drugs. However, for SARS-CoV-2 only a small number of protease inhibitors have been identified thus far and there is still a great need for assays that efficiently report protease activity and inhibition in living cells. Here, we engineer a safe VSV-based system to report both gain- and loss-of-function of coronavirus main protease (Mpro/3CLpro/Nsp5) activity in living cells. We use SARS-CoV-2 3CLpro in this system to confirm susceptibility to known inhibitors (boceprevir, GC376, PF-00835231, and PF-07321332/nirmatrelvir) and reevaluate other reported inhibitors (baicalein, ebselen, carmofur, ethacridine, ivermectin, masitinib, darunavir, and atazanavir). Moreover, we show that the system can be adapted to report both the function and the chemical inhibition of proteases from different coronavirus species as well as from distantly related viruses. Together with the fact that live cell assays also reflect compound permeability and toxicity, we anticipate that this system will be useful for both identification and optimization of additional coronavirus protease inhibitors.

Crystallographic models of SARS-CoV-2 3CLpro: in-depth assessment of structure quality and validation.

The appearance at the end of 2019 of the new SARS-CoV-2 coronavirus led to an unprecedented response by the structural biology community, resulting in the rapid determination of many hundreds of structures of proteins encoded by the virus. As part of an effort to analyze and, if necessary, remediate these structures as deposited in the Protein Data Bank (PDB), this work presents a detailed analysis of 81 crystal structures of the main protease 3CLpro, an important target for the design of drugs against COVID-19. The structures of the unliganded enzyme and its complexes with a number of inhibitors were determined by multiple research groups using different experimental approaches and conditions; the resulting structures span 13 different polymorphs representing seven space groups. The structures of the enzyme itself, all determined by molecular replacement, are highly similar, with the exception of one polymorph with a different inter-domain orientation. However, a number of complexes with bound inhibitors were found to pose significant problems. Some of these could be traced to faulty definitions of geometrical restraints for ligands and to the general problem of a lack of such information in the PDB depositions. Several problems with ligand definition in the PDB itself were also noted. In several cases extensive corrections to the models were necessary to adhere to the evidence of the electron-density maps. Taken together, this analysis of a large number of structures of a single, medically important protein, all determined within less than a year using modern experimental tools, should be useful in future studies of other systems of high interest to the biomedical community.

Rapid response to emerging biomedical challenges and threats.

As part of the global mobilization to combat the present pandemic, almost 100 000 COVID-19-related papers have been published and nearly a thousand models of macromolecules encoded by SARS-CoV-2 have been deposited in the Protein Data Bank within less than a year. The avalanche of new structural data has given rise to multiple resources dedicated to assessing the correctness and quality of structural data and models. Here, an approach to evaluate the massive amounts of such data using the resource https://covid19.bioreproducibility.org is described, which offers a template that could be used in large-scale initiatives undertaken in response to future biomedical crises. Broader use of the described methodology could considerably curtail information noise and significantly improve the reproducibility of biomedical research.

Covid-19.bioreproducibility.org: A web resource for SARS-CoV-2-related structural models.

The COVID-19 pandemic has triggered numerous scientific activities aimed at understanding the SARS-CoV-2 virus and ultimately developing treatments. Structural biologists have already determined hundreds of experimental X-ray, cryo-EM, and NMR structures of proteins and nucleic acids related to this coronavirus, and this number is still growing. To help biomedical researchers, who may not necessarily be experts in structural biology, navigate through the flood of structural models, we have created an online resource, covid19.bioreproducibility.org, that aggregates expert-verified information about SARS-CoV-2-related macromolecular models. In this article, we describe this web resource along with the suite of tools and methodologies used for assessing the structures presented therein.