RESUMO
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.
RESUMO
The COVID-19 pandemic is a stark reminder that a barren global antiviral pipeline has grave humanitarian consequences. Future pandemics could be prevented by accessible, easily deployable broad-spectrum oral antivirals and open knowledge bases that derisk and accelerate novel antiviral discovery and development. Here, we report the results of the COVID Moonshot, a fully open-science structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a novel chemical scaffold that is differentiated from current clinical candidates in terms of toxicity, resistance, and pharmacokinetics liabilities, and developed it into noncovalent orally-bioavailable nanomolar inhibitors with clinical potential. Our approach leveraged crowdsourcing, high-throughput structural biology, machine learning, and exascale molecular simulations. In the process, we generated a detailed map of the structural plasticity of the main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. In a first for a structure-based drug discovery campaign, all compound designs (>18,000 designs), crystallographic data (>500 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.
RESUMO
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.
