The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to significant global morbidity and mortality. A crucial viral protein, the non-structural protein 14 (nsp14), catalyzes the methylation of viral RNA and plays a critical role in viral genome replication and transcription. Due to the low mutation rate in the nsp region among various SARS-CoV-2 variants, nsp14 has emerged as a promising therapeutic target. However, discovering potential inhibitors remains a challenge. In this work, we introduce a computational pipeline for the rapid and efficient identification of potential nsp14 inhibitors by leveraging virtual screening and the NCI open compound collection, which contains 250,000 freely available molecules for researchers worldwide. The introduced pipeline provides a cost-effective and efficient approach for early-stage drug discovery by allowing researchers to evaluate promising molecules without incurring synthesis expenses. Our pipeline successfully identified seven promising candidates after experimentally validating only 40 compounds. Notably, we discovered NSC620333, a compound that exhibits a strong binding affinity to nsp14 with a dissociation constant of 427 ± 84 nM. In addition, we gained new insights into the structure and function of this protein through molecular dynamics simulations. We identified new conformational states of the protein and determined that residues Phe367, Tyr368, and Gln354 within the binding pocket serve as stabilizing residues for novel ligand interactions. We also found that metal coordination complexes are crucial for the overall function of the binding pocket. Lastly, we present the solved crystal structure of the nsp14-MTase complexed with SS148 (PDB:8BWU), a potent inhibitor of methyltransferase activity at the nanomolar level (IC50 value of 70 ± 6 nM). Our computational pipeline accurately predicted the binding pose of SS148, demonstrating its effectiveness and potential in accelerating drug discovery efforts against SARS-CoV-2 and other emerging viruses.

Acceleration Consortium University of Toronto Toronto ON Canada

Canadian Institute for Advanced Research Toronto ON Canada

Chemical Physics Theory Group Department of Chemistry University of Toronto 80 St George St Toronto Ontario M5S 3H6 Canada

Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center

Current affiliation Stratingh Institute for Chemistry University of Groningen The Netherlands

Department of Biochemistry and Molecular Biophysics Kansas State University Manhattan KS 66506 USA

Department of Cancer Biology Dana Farber Cancer Institute Boston USA

Department of Chemical Engineering and Applied Chemistry University of Toronto Canada

Department of Chemistry Temple University Philadelphia PA 19122 USA

Department of Computer Science Stanford University

Department of Computer Science University of Toronto 40 St George St Toronto Ontario M5S 2E4 Canada

Department of Genetics Stanford University

Department of Materials Science and Engineering University of Toronto Canada

Department of Pharmacological Sciences and Oncological Sciences Mount Sinai Center for Therapeutics Discovery Tisch Cancer Institute Ichan School of Medicine at Mount Sinai New York NY USA

Department of Pharmacology and Toxicology University of Toronto Toronto Ontario M5S 1A8 Canada

Department of Physics Faculty of Arts and Sciences Harvard University Cambridge USA

Drug Discovery Program Ontario Institute for Cancer Research Toronto Ontario Canada

Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Prague Czech Republic

QBI COVID 19 Research Group San Francisco CA USA

St Jude Children's Research Hospital Department of Structural Biology Memphis TN USA

Structural Bioinformatics and Computational Biochemistry Department of Biochemistry University of Oxford South Parks Road Oxford OX1 3QU UK

Structural Genomics Consortium University of Toronto Toronto Ontario M5G 1L7 Canada

Vector Institute for Artificial Intelligence Toronto Canada

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