{"doi":"10.15252/msb.202110426","title":"Machine learning identifies molecular regulators and therapeutics for targeting SARS‐CoV2‐induced cytokine release","abstract":"Although 15-20% of COVID-19 patients experience hyper-inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N-terminal domain (NTD) of the SARS-CoV-2 spike protein substantially induces multiple inflammatory molecules in myeloid cells and human PBMCs. Using a combination of phenotypic screening with machine learning-based modeling, we identified and experimentally validated several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD-induced cytokine production, implicating the role of multiple signaling pathways in cytokine release. Further, we found several FDA-approved drugs, including ponatinib, and cobimetinib as potent inhibitors of the NTD-mediated cytokine release. Treatment with ponatinib outperforms other drugs, including dexamethasone and baricitinib, inhibiting all cytokines in response to the NTD from SARS-CoV-2 and emerging variants. Finally, ponatinib treatment inhibits lipopolysaccharide-mediated cytokine release in myeloid cells in vitro and lung inflammation mouse model. Together, we propose that agents targeting multiple kinases required for SARS-CoV-2-mediated cytokine release, such as ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID-19.","journal":"Molecular Systems Biology","year":2021,"id":164671,"datarank":0.5495342469194471,"base_score":3.6635616461296463,"endowment":3.6635616461296463,"self_citation_contribution":0.5495342469194471,"citation_network_contribution":0.0,"self_endowment_contribution":0.5495342469194471,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":38,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.963,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":416999,"name":"Siddharth Vijay","orcid":null,"position":1,"is_corresponding":false},{"id":686693,"name":"John McNevin","orcid":"0000-0002-9893-9256","position":2,"is_corresponding":false},{"id":52019,"name":"M. Juliana McElrath","orcid":"0000-0003-2276-7117","position":3,"is_corresponding":false},{"id":226433,"name":"Eric C. Holland","orcid":"0000-0002-3792-7120","position":4,"is_corresponding":false},{"id":375811,"name":"Taranjit S. Gujral","orcid":"0000-0002-4453-3031","position":5,"is_corresponding":false},{"id":377456,"name":"Marina Chan","orcid":null,"position":0,"is_corresponding":true}],"reference_count":37,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:45:32.226038Z","pmid":"34486798","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}