12 pags., 4 figs., 3 tabs.SARS-CoV-2 (SCoV2) and its variants of concern pose serious challenges to the public health. The variants increased challenges to vaccines, thus necessitating for development of new intervention strategies including anti-virals. Within the international Covid19-NMR consortium, we have identified binders targeting the RNA genome of SCoV2. We established protocols for the production and NMR characterization of more than 80 % of all SCoV2 proteins. Here, we performed an NMR screening using a fragment library for binding to 25 SCoV2 proteins and identified hits also against previously unexplored SCoV2 proteins. Computational mapping was used to predict binding sites and identify functional moieties (chemotypes) of the ligands occupying these pockets. Striking consensus was observed between NMR-detected binding sites of the main protease and the computational procedure. Our investigation provides novel structural and chemical space for structure-based drug design against the SCoV2 proteome.Work at BMRZ is supported by the state of Hesse. Work in Covid19-NMR
was supported by the Goethe Corona Funds, by the IWBEFRE-program 20007375 of state of Hesse, the DFG
through CRC902: “Molecular Principles of RNA-based regulation.” and through infrastructure funds (project
numbers: 277478796, 277479031, 392682309, 452632086, 70653611) and by European Union’s Horizon 2020 research and innovation program iNEXT-discovery under grant agreement No 871037. BY-COVID receives funding from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement number 101046203. “INSPIRED” (MIS 5002550) project, implemented under the Action “Reinforcement of the Research and Innovation Infrastructure,” funded by the Operational
Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the EU (European Regional Development Fund) and the FP7 REGPOT CT-2011-285950—“SEE-DRUG” project (purchase of UPAT’s 700 MHz NMR equipment). The support of the CERM/CIRMMP center of Instruct-ERIC is gratefully acknowledged. This work has been funded in part by a grant of the Italian Ministry of University and Research (FISR2020IP_02112, ID-COVID) and by Fondazione CR
Firenze. A.S. is supported by the Deutsche Forschungsgemeinschaft [SFB902/B16, SCHL2062/2-1] and the Johanna Quandt Young Academy at Goethe [2019/AS01]. M.H. and C.F. thank SFB902 and the Stiftung Polytechnische Gesellschaft for the Scholarship. L.L. work was supported by the French National Research Agency (ANR, NMR-SCoV2-ORF8), the Fondation de la Recherche Médicale (FRM, NMR-SCoV2-ORF8), FINOVI and the IR-RMN-THC Fr3050 CNRS. Work at UConn Health was supported by grants from the US National Institutes of Health (R01 GM135592 to B.H., P41 GM111135 and R01 GM123249 to J.C.H.) and the US National Science Foundation (DBI 2030601 to J.C.H.). Latvian Council of Science Grant No. VPP-COVID-2020/1-0014. National Science Foundation EAGER MCB-2031269. This work was supported by the grant Krebsliga KFS-4903-08-2019 and SNF-311030_192646 to J.O. P.G. (ITMP) The EOSC Future project is co-funded by the European Union Horizon Programme call INFRAEOSC-03-2020—Grant Agreement
Number 101017536. Open Access funding enabled and organized by Projekt DEALPeer reviewe