Human basigin (CD147) does not directly interact with SARS-CoV-2 spike glycoprotein (preprint)

Basigin, or CD147, has been reported as a co-receptor used by SARS-CoV-2 to invade host cells. Basigin also has a well-established role in Plasmodium falciparum malaria infection of human erythrocytes where it is bound by one of the parasite’s invasion ligands, reticulocyte binding protein homolog 5 (RH5). Here, we sought to validate the claim that the receptor binding domain (RBD) of SARS-CoV-2 spike glycoprotein can form a complex with basigin, using RH5-basigin as a positive control. Using recombinantly expressed proteins, size exclusion chromatography and surface plasmon resonance, we show that neither RBD nor full-length spike glycoprotein bind to recombinant human basigin (either expressed in E. coli or mammalian cells). Given the immense interest in SARS-CoV-2 therapeutic targets, we would caution the inclusion of basigin in this list on the basis of its reported direct interaction with SARS-CoV-2 spike glycoprotein. Importance Reducing the mortality and morbidity associated with COVID-19 remains a global health priority. Critical to these efforts is the identification of host factors that are essential to viral entry and replication. Basigin, or CD147, was previously identified as a possible therapeutic target based on the observation that it may act as a co-receptor for SARS-COV-2, binding to the receptor binding domain of the spike protein. Here, we show that there is no direct interaction between the RBD and basigin, casting doubt on its role as a co-receptor and plausibility as a therapeutic target.

Analysis of SARS-CoV-2 spike glycosylation reveals shedding of a vaccine candidate (preprint)

Severe acute respiratory syndrome coronavirus 2 is the causative pathogen of the COVID-19 pandemic which as of Nov 15, 2020 has claimed 1,319,946 lives worldwide. Vaccine development focuses on the viral trimeric spike glycoprotein as the main target of the humoral immune response. Viral spikes carry glycans that facilitate immune evasion by shielding specific protein epitopes from antibody neutralisation. Immunogen integrity is therefore important for glycoprotein-based vaccine candidates. Here we show how site-specific glycosylation differs between virus-derived spikes and spike proteins derived from a viral vectored SARS-CoV-2 vaccine candidate. We show that their cellular secretion pathways are unique, resulting in different protein glycosylation and secretion, which may have implications for the resulting immune response and future vaccine design.

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.