Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

INTRODUCTION COVID-19 became a global pandemic partially as a result of the lack of easily deployable, broad-spectrum oral antivirals, which complicated its containment. Even endemically, and with effective vaccinations, it will continue to cause acute disease, death, and long-term sequelae globally unless there are accessible treatments. COVID-19 is not an isolated event but instead is the latest example of a viral pandemic threat to human health. Therefore, antiviral discovery and development should be a key pillar of pandemic preparedness efforts. RATIONALE One route to accelerate antiviral drug discovery is the establishment of open knowledge bases, the development of effective technology infrastructures, and the discovery of multiple potent antivirals suitable as starting points for the development of therapeutics. In this work, we report the results of the COVID Moonshot—a fully open science, crowdsourced, and structure-enabled drug discovery campaign—against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). This collaboration may serve as a roadmap for the potential development of future antivirals. RESULTS On the basis of the results of a crystallographic fragment screen, we crowdsourced design ideas to progress from fragment to lead compounds. The crowdsourcing strategy yielded several key compounds along the optimization trajectory, including the starting compound of what became the primary lead series. Three additional chemically distinct lead series were also explored, spanning a diversity of chemotypes. The collaborative and highly automated nature of the COVID Moonshot Consortium resulted in >18,000 compound designs, >2400 synthesized compounds, >490 ligand-bound x-ray structures, >22,000 alchemical free-energy calculations, and >10,000 biochemical measurements—all of which were made publicly available in real time. The recently approved antiviral ensitrelvir was identified in part based on crystallographic data from the COVID Moonshot Consortium. This campaign led to the discovery of a potent [median inhibitory concentration (IC50) = 37 ± 2 nM] and differentiated (noncovalent and nonpeptidic) lead compound that also exhibited potent cellular activity, with a median effective concentration (EC50) of 64 nM in A549-ACE2-TMPRSS2 cells and 126 nM in HeLa-ACE2 cells without measurable cytotoxicity. Although the pharmacokinetics of the reported compound is not yet optimal for therapeutic development, it is a promising starting point for further antiviral discovery and development. CONCLUSION The success of the COVID Moonshot project in producing potent antivirals, building open knowledge bases, accelerating external discovery efforts, and functioning as a useful information-exchange hub is an example of the potential effectiveness of open science antiviral discovery programs. The open science, patent-free nature of the project enabled a large number of collaborators to provide in-kind support, including synthesis, assays, and in vitro and in vivo experiments. By making all data immediately available and ensuring that all compounds are purchasable from Enamine without the need for materials transfer agreements, we aim to accelerate research globally along parallel tracks. In the process, we generated a detailed map of the structural plasticity of Mpro, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data to spur further research into antivirals and discovery methodologies. We hope that this can serve as an alternative model for antiviral discovery and future pandemic preparedness. Further, the project also showcases the role of machine learning, computational chemistry, and high-throughput structural biology as force multipliers in drug design. Artificial intelligence and machine learning algorithms help accelerate chemical synthesis while balancing multiple competing molecular properties. The design-make-test-analyze cycle was accelerated by these algorithms combined with planetary-scale biomolecular simulations of protein-ligand interactions and rapid structure determination

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression, and replication, which depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate an unprecedented 0.1 seconds of the viral proteome. Our simulations capture dramatic opening of the apo Spike complex, far beyond that seen experimentally, which explains and successfully predicts the existence of ‘cryptic’ epitopes. Different Spike homologues modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also observe dramatic conformational changes across the proteome, which reveal over 50 ‘cryptic’ pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas

SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids

This work was supported by grants of the German Research Foundation (DFG: KR 4073/11-1; SFBTRR219, 322900939; and CRU344, 428857858, and CRU5011 InteraKD 445703531), a grant of the European Research Council (ERC-StG 677448), the Federal Ministry of Research and Education (BMBF NUM-COVID19, Organo-Strat 01KX2021), the Dutch Kidney Foundation (DKF) TASK FORCE consortium (CP1805), the Else Kroener Fresenius Foundation (2017_A144), and the ERA-CVD MENDAGE consortium (BMBF 01KL1907) all to R.K.; DFG (CRU 344, Z to I.G.C and CRU344 P2 to R.K.S.); and the BMBF eMed Consortium Fibromap (to V.G.P, R.K., R.K.S., and I.G.C.). R.K.S received support from the KWF Kankerbestrijding (11031/2017–1, Bas Mulder Award) and a grant by the ERC (deFiber; ERC-StG 757339). J.J. is supported by the Netherlands Organisation for Scientific Research (NWO Veni grant no: 091 501 61 81 01 36) and the DKF (grant no. 19OK005). B.S. is supported by the DKF (grant: 14A3D104) and the NWO (VIDI grant: 016.156.363). R.P.V.R. and G.J.O. are supported by the NWO VICI (grant: 16.VICI.170.090). P.B. is supported by the BMBF (DEFEAT PANDEMIcs, 01KX2021), the Federal Ministry of Health (German Registry for COVID-19 Autopsies-DeRegCOVID, www.DeRegCOVID.ukaachen.de; ZMVI1-2520COR201), and the German Research Foundation (DFG; SFB/TRR219 Project-IDs 322900939 and 454024652). S.D. received DFG support (DJ100/1-1) as well as support from VGP and TBH (SFB1192). M.d.B,R.R., N.S., and A.A. are supported by an ERC Advanced Investigator grant (H2020-ERC-2017-ADV-788982-COLMIN) to N.S. A.A. is supported by the NWO (VI.Veni.192.094). We thank Saskia de Wildt, Jeanne Pertijs (Radboudumc, Department of Pharmacology), and Robert M. Verdijk (Erasmus Medical Center, Department of Pathology) for providing tissue controls (Erasmus MC Tissue Bank) and Christian Drosten (Charite´ Universitatsmedizin Berlin, Institute of € Virology) and Bart Haagmans (Erasmus Medical Center, Rotterdam) for providing the SARS-CoV-2 isolate. We thank Kioa L. Wijnsma (Department of Pediatric Nephrology, Radboud Institute for Molecular Life Sciences, Amalia Children’s Hospital, Radboud University Medical Center) for support with statistical analysis regarding the COVID-19 patient cohort.Peer reviewedPublisher PD