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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21253148

RESUMO

Public health experts emphasize the need for quick, point-of-care SARS-CoV-2 detection as an effective strategy for controlling virus spread. To this end, many "antigen" detection devices were developed and commercialized. These devices are mostly based on detecting SARS-CoV-2s nucleocapsid protein. Recently, alerts issued by both the FDA and the CDC raised concerns regarding the devices tendency to exhibit false positive results. In this work we developed a novel alternative spike-based antigen assay, comprised of four high-affinity, specific monoclonal antibodies, directed against different epitopes on the spikes S1 subunit. The assays performance was evaluated for COVID-19 detection from nasopharyngeal swabs, compared to an in-house nucleocapsid-based assay, composed of antibodies directed against the nucleocapsid. Detection of COVID-19 was carried out in a cohort of 284 qRT-PCR positive and negative nasopharyngeal swab samples. The time resolved fluorescence (TRF) ELISA spike-assay displayed very high specificity (99%) accompanied with a somewhat lower sensitivity (66% for Ct<25), compared to the nucleocapsid ELISA assay which was more sensitive (85% for Ct<25) while less specific (87% specificity). Despite being out-performed by qRT-PCR, we suggest that there is room for such tests in the clinical setting, as cheap and rapid pre-screening tools. Our results further suggest that when applying antigen detection, one must consider its intended application (sensitivity vs specificity), taking into consideration that the nucleocapsid might not be the optimal target. In this regard, we propose that a combination of both antigens might contribute to the validity of the results. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/21253148v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@2cdc04org.highwire.dtl.DTLVardef@12090daorg.highwire.dtl.DTLVardef@10603dforg.highwire.dtl.DTLVardef@1e84cfa_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphic abstractSchematic representation of sample collection and analysis. The figure was created using BioRender.com

2.
- The COVID Moonshot Initiative; Hagit Achdout; Anthony Aimon; Elad Bar-David; Haim Barr; Amir Ben-Shmuel; James Bennett; Vitaliy A. Bilenko; Vitaliy A. Bilenko; Melissa L. Boby; Bruce Borden; Gregory R. Bowman; Juliane Brun; Sarma BVNBS; Mark Calmiano; Anna Carbery; Daniel Carney; Emma Cattermole; Edcon Chang; Eugene Chernyshenko; John D. Chodera; Austin Clyde; Joseph E. Coffland; Galit Cohen; Jason Cole; Alessandro Contini; Lisa Cox; Milan Cvitkovic; Alex Dias; Kim Donckers; David L. Dotson; Alice Douangamath; Shirly Duberstein; Tim Dudgeon; Louise Dunnett; Peter K. Eastman; Noam Erez; Charles J. Eyermann; Mike Fairhead; Gwen Fate; Daren Fearon; Oleg Fedorov; Matteo Ferla; Rafaela S. Fernandes; Lori Ferrins; Richard Foster; Holly Foster; Ronen Gabizon; Adolfo Garcia-Sastre; Victor O. Gawriljuk; Paul Gehrtz; Carina Gileadi; Charline Giroud; William G. Glass; Robert Glen; Itai Glinert; Andre S. Godoy; Marian Gorichko; Tyler Gorrie-Stone; Ed J. Griffen; Storm Hassell Hart; Jag Heer; Michael Henry; Michelle Hill; Sam Horrell; Victor D. Huliak; Matthew F.D. Hurley; Tomer Israely; Andrew Jajack; Jitske Jansen; Eric Jnoff; Dirk Jochmans; Tobias John; Steven De Jonghe; Anastassia L. Kantsadi; Peter W. Kenny; J. L. Kiappes; Serhii O. Kinakh; Lizbe Koekemoer; Boris Kovar; Tobias Krojer; Alpha Lee; Bruce A. Lefker; Haim Levy; Ivan G. Logvinenko; Nir London; Petra Lukacik; Hannah Bruce Macdonald; Beth MacLean; Tika R. Malla; Tatiana Matviiuk; Willam McCorkindale; Briana L. McGovern; Sharon Melamed; Kostiantyn P. Melnykov; Oleg Michurin; Halina Mikolajek; Bruce F. Milne; Aaron Morris; Garrett M. Morris; Melody Jane Morwitzer; Demetri Moustakas; Aline M. Nakamura; Jose Brandao Neto; Johan Neyts; Luong Nguyen; Gabriela D. Noske; Vladas Oleinikovas; Glaucius Oliva; Gijs J. Overheul; David Owen; Ruby Pai; Jin Pan; Nir Paran; Benjamin Perry; Maneesh Pingle; Jakir Pinjari; Boaz Politi; Ailsa Powell; Vladimir Psenak; Reut Puni; Victor L. Rangel; Rambabu N. Reddi; St Patrick Reid; Efrat Resnick; Emily Grace Ripka; Matthew C. Robinson; Ralph P. Robinson; Jaime Rodriguez-Guerra; Romel Rosales; Dominic Rufa; Kadi Saar; Kumar Singh Saikatendu; Chris Schofield; Mikhail Shafeev; Aarif Shaikh; Jiye Shi; Khriesto Shurrush; Sukrit Singh; Assa Sittner; Rachael Skyner; Adam Smalley; Bart Smeets; Mihaela D. Smilova; Leonardo J. Solmesky; John Spencer; Claire Strain-Damerell; Vishwanath Swamy; Hadas Tamir; Rachael Tennant; Warren Thompson; Andrew Thompson; Susana Tomasio; Igor S. Tsurupa; Anthony Tumber; Ioannis Vakonakis; Ronald P. van Rij; Laura Vangeel; Finny S. Varghese; Mariana Vaschetto; Einat B. Vitner; Vincent Voelz; Andrea Volkamer; Frank von Delft; Annette von Delft; Martin Walsh; Walter Ward; Charlie Weatherall; Shay Weiss; Kris M. White; Conor Francis Wild; Matthew Wittmann; Nathan Wright; Yfat Yahalom-Ronen; Daniel Zaidmann; Hadeer Zidane; Nicole Zitzmann.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-339317

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.

3.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-160655

RESUMO

The COVID-19 pandemic caused by SARS-CoV-2 that emerged in December 2019 in China resulted in over 7.8 million infections and over 430,000 deaths worldwide, imposing an urgent need for rapid development of an efficient and cost-effective vaccine, suitable for mass immunization. Here, we generated a replication competent recombinant VSV-{Delta}G-spike vaccine, in which the glycoprotein of VSV was replaced by the spike protein of the SARS-CoV-2. In vitro characterization of the recombinant VSV-{Delta}G-spike indicated expression and presentation of the spike protein on the viral membrane with antigenic similarity to SARS-CoV-2. A golden Syrian hamster in vivo model for COVID-19 was implemented. We show that vaccination of hamsters with recombinant VSV-{Delta}G-spike results in rapid and potent induction of neutralizing antibodies against SARS-CoV-2. Importantly, single-dose vaccination was able to protect hamsters against SARS-CoV-2 challenge, as demonstrated by the abrogation of body weight loss of the immunized hamsters compared to unvaccinated hamsters. Furthermore, whereas lungs of infected hamsters displayed extensive tissue damage and high viral titers, immunized hamsters lungs showed only minor lung pathology, and no viral load. Taken together, we suggest recombinant VSV-{Delta}G-spike as a safe, efficacious and protective vaccine against SARS-CoV-2 infection.

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