Allosteric regulation and crystallographic fragment screening of SARS-CoV-2 NSP15 endoribonuclease (preprint)

SARS-CoV-2 is the causative agent of COVID-19. The highly conserved viral NSP15 endoribonuclease, NendoU, is a key enzyme involved in viral immune evasion, and a promising target for the development of new classes antivirals. Yet, the broad variety of recognition sequences, complex assembly and kinetics, and lack of structural complexes hamper the development of new competitive or allosteric inhibitors for this target. In here, we performed enzymatic characterization of NendoU in its monomeric and hexameric form, showing that hexamers are allosteric enzymes with a positive cooperative index of 2. By using cryo-EM in distinct pH's combined with X-ray crystallography and structural analysis, we demonstrate the potential for NendoU to shift between open and closed states, and assembly in larger supramolecular entities, which might serve as a mechanism of self-regulation. Further, we report results from our large fragment screening campaign against NendoU, revealing multiple new allosteric sites for the development of new inhibitors.

Simultaneous identification of viruses and SARS-CoV-2 variants with programmable DNA nanobait (preprint)

Respiratory infections are the major cause of death from infectious disease worldwide. The clinical presentation of many respiratory viruses is indistinguishable; therefore, diagnostic approaches that can identify multiple pathogens are essential for patient management. We aimed to address this challenge with self-assembled DNA nanobait that can simultaneously identify multiple short RNA targets. The nanobait approach relies on specific target selection via toehold-mediated strand displacement and rapid read-out via nanopore sensing. Here, we show this platform can concurrently identify several common respiratory viruses, detecting a panel of short targets of viral nucleic acids from SARS-CoV-2, respiratory syncytial virus (RSV), rhinovirus, influenza, and parainfluenza. Our nanobait could be reprogrammed to discriminate viral variants, and we identified several key SARS-CoV-2 variants with single-nucleotide resolution. We increased assay specificity with bespoke nanobait that could identify numerous short RNA targets in the same viral sample in a complex background of the human transcriptome. Notably, we found that the sequence position in the viral RNA secondary structure is critical for nanobait design. Lastly, we show that nanobait could discriminate between samples extracted from oropharyngeal swabs from negative and positive SARS-CoV-2 patients using programmable target cleavage without pre-amplification. Our system allows for multiplexed identification of native RNA molecules, providing a new scalable approach for diagnostics of multiple respiratory viruses in a single assay.

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.

Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease (preprint)

COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments was progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.