Discovery of SARS-CoV-2 Mpro Peptide Inhibitors from Modelling Substrate and Ligand Binding (preprint)

The main protease (Mpro) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural Mpro substrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural Mpro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to Mpro, reveal new opportunities for inhibition. Building on our initial Mpro-substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit Mpro competitively. The combined results provide new insight useful for the development of Mpro inhibitors.

COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning (preprint)

Herein we provide a living summary of the data generated during the COVID Moonshot project focused on the development of SARS-CoV-2 main protease (Mpro) inhibitors. Our approach uniquely combines crowdsourced medicinal chemistry insights with high throughput crystallography, exascale computational chemistry infrastructure for simulations, and machine learning in triaging designs and predicting synthetic routes. This manuscript describes our methodologies leading to both covalent and non-covalent inhibitors displaying protease IC50 values under 150 nM and viral inhibition under 5 uM in multiple different viral replication assays. Furthermore, we provide over 200 crystal structures of fragment-like and lead-like molecules in complex with the main protease. Over 1000 synthesized and ordered compounds are also reported with the corresponding activity in Mpro enzymatic assays using two different experimental setups. The data referenced in this document will be continually updated to reflect the current experimental progress of the COVID Moonshot project, and serves as a citable reference for ensuing publications. All of the generated data is open to other researchers who may find it of use.

A cell-free antibody engineering platform rapidly generates SARS-CoV-2 neutralizing antibodies (preprint)

Antibody engineering technologies face increasing demands for speed, reliability and scale. We developed CeVICA, a cell-free antibody engineering platform that integrates a novel generation method and design for camelid heavy-chain antibody VHH domain-based synthetic libraries, optimized in vitro selection based on ribosome display and a computational pipeline for binder prediction based on CDR-directed clustering. We applied CeVICA to engineer antibodies against the Receptor Binding Domain (RBD) of the SARS-CoV-2 spike proteins and identified >800 predicted binder families. Among 14 experimentally-tested binders, 6 showed inhibition of pseudotyped virus infection. Antibody affinity maturation further increased binding affinity and potency of inhibition. Additionally, the unique capability of CeVICA for efficient and comprehensive binder prediction allowed retrospective validation of the fitness of our synthetic VHH library design and revealed direction for future refinement. CeVICA offers an integrated solution to rapid generation of divergent synthetic antibodies with tunable affinities in vitro and may serve as the basis for automated and highly parallel antibody generation.

PRAK-03202: A triple antigen VLP vaccine candidate against SARS CoV-2 (preprint)

The rapid development of safe and effective vaccines against SARS CoV-2 is the need of the hour for the coronavirus outbreak. Here, we have developed PRAK-03202, the world's first triple antigen VLP vaccine candidate in a highly characterized S. cerevisiae-based D-Crypt platform, which induced SARS CoV-2 specific neutralizing antibodies in BALB/c mice. Immunizations using three different doses of PRAK-03202 induces antigen specific (Spike, envelope and membrane proteins) humoral response and neutralizing potential. PBMCs from convalescent patients, when exposed to PRAK-03202, showed lymphocyte proliferation and elevated IFN-{gamma} levels suggestive of conservation of epitopes and induction of T helper 1 (Th1)-biased cellular immune responses. These data support the clinical development and testing of PRAK-03202 for use in humans.

Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses (preprint)

Seasonal coronaviruses (OC43, 229E, NL63 and HKU1) are endemic to the human population, regularly infecting and reinfecting humans while typically causing asymptomatic to mild respiratory infections. It is not known to what extent reinfection by these viruses is due to waning immune memory or antigenic drift of the viruses. Here, we address the influence of antigenic drift on immune evasion of seasonal coronaviruses. We provide evidence that at least two of these viruses, OC43 and 229E, are undergoing adaptive evolution in regions of the viral spike protein that are exposed to human humoral immunity. This suggests that reinfection may be due, in part, to positively-selected genetic changes in these viruses that enable them to escape recognition by the immune system. It is possible that, as with seasonal influenza, these adaptive changes in antigenic regions of the virus would necessitate continual reformulation of a vaccine made against them.

Characterisation of the SARS-CoV-2 ExoN (nsp14ExoN-nsp10) complex: implications for its role in viral genome stability and inhibitor identification (preprint)

The SARS-CoV-2 coronavirus (CoV) causes COVID-19, a current global pandemic. SARS-CoV-2 belongs to an order of Nidovirales with very large RNA genomes. It is proposed that the fidelity of CoV genome replication is aided by an RNA nuclease complex, formed of non-structural proteins 14 and 10 (nsp14-nsp10), an attractive target for antiviral inhibition. Here, we confirm that the SARS-CoV-2 nsp14-nsp10 complex is an RNase. Detailed functional characterisation reveals nsp14-nsp10 is a highly versatile nuclease capable of digesting a wide variety of RNA structures, including those with a blocked 3-terminus. We propose that the role of nsp14-nsp10 in maintaining replication fidelity goes beyond classical proofreading and purges the nascent replicating RNA strand of a range of potentially replication terminating aberrations. Using the developed assays, we identify a series of drug and drug-like molecules that potently inhibit nsp14-nsp10, including the known Sars-Cov-2 major protease (Mpro) inhibitor ebselen and the HIV integrase inhibitor raltegravir, revealing the potential for bifunctional inhibitors in the treatment of COVID-19.