{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T17:25:38Z","timestamp":1790875538585,"version":"4.1.0"},"reference-count":34,"publisher":"American Association for the Advancement of Science (AAAS)","issue":"633","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sci. Transl. Med."],"published-print":{"date-parts":[[2022,2,23]]},"abstract":"<jats:p>SARS-CoV-2 evolution threatens vaccine- and natural infection\u2013derived immunity and the efficacy of therapeutic antibodies. To improve public health preparedness, we sought to predict which existing amino acid mutations in SARS-CoV-2 might contribute to future variants of concern. We tested the predictive value of features comprising epidemiology, evolution, immunology, and neural network\u2013based protein sequence modeling and identified primary biological drivers of SARS-CoV-2 intrapandemic evolution. We found evidence that ACE2-mediated transmissibility and resistance to population-level host immunity has waxed and waned as a primary driver of SARS-CoV-2 evolution over time. We retroactively identified with high accuracy (area under the receiver operator characteristic curve = 0.92 to 0.97) mutations that will spread, at up to 4 months in advance, across different phases of the pandemic. The behavior of the model was consistent with a plausible causal structure where epidemiological covariates combine the effects of diverse and shifting drivers of viral fitness. We applied our model to forecast mutations that will spread in the future and characterize how these mutations affect the binding of therapeutic antibodies. These findings demonstrate that it is possible to forecast the driver mutations that could appear in emerging SARS-CoV-2 variants of concern. We validated this result against Omicron, showing elevated predictive scores for its component mutations before emergence and rapid score increase across daily forecasts during emergence. This modeling approach may be applied to any rapidly evolving pathogens with sufficiently dense genomic surveillance data, such as influenza, and unknown future pandemic viruses.<\/jats:p>","DOI":"10.1126\/scitranslmed.abk3445","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T09:57:32Z","timestamp":1641895052000},"source":"Crossref","is-referenced-by-count":168,"title":["Predicting the mutational drivers of future SARS-CoV-2 variants of concern"],"prefix":"10.1126","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6666-3574","authenticated-orcid":true,"given":"M. Cyrus","family":"Maher","sequence":"first","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3360-1999","authenticated-orcid":true,"given":"Istvan","family":"Bartha","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6931-7191","authenticated-orcid":true,"given":"Steven","family":"Weaver","sequence":"additional","affiliation":[{"name":"Department of Biology, Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9343-127X","authenticated-orcid":true,"given":"Julia","family":"di Iulio","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8672-4733","authenticated-orcid":true,"given":"Elena","family":"Ferri","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5852-741X","authenticated-orcid":true,"given":"Leah","family":"Soriaga","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6103-8078","authenticated-orcid":true,"given":"Florian A.","family":"Lempp","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3224-8142","authenticated-orcid":true,"given":"Brian L.","family":"Hie","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."},{"name":"Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1716-6712","authenticated-orcid":true,"given":"Bryan","family":"Bryson","sequence":"additional","affiliation":[{"name":"Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA."},{"name":"Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2724-7228","authenticated-orcid":true,"given":"Bonnie","family":"Berger","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."},{"name":"Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6338-0221","authenticated-orcid":true,"given":"David L.","family":"Robertson","sequence":"additional","affiliation":[{"name":"MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow GS1 1QH, UK."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1475-659X","authenticated-orcid":true,"given":"Gyorgy","family":"Snell","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5797-1364","authenticated-orcid":true,"given":"Davide","family":"Corti","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8580-7628","authenticated-orcid":true,"given":"Herbert W.","family":"Virgin","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."},{"name":"Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA."},{"name":"Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4817-4029","authenticated-orcid":true,"given":"Sergei L.","family":"Kosakovsky Pond","sequence":"additional","affiliation":[{"name":"Department of Biology, Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6290-7677","authenticated-orcid":true,"given":"Amalio","family":"Telenti","sequence":"additional","affiliation":[{"name":"Vir Biotechnology, San Francisco, CA 94158, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2021.03.028"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1002\/gch2.1018"},{"key":"e_1_3_3_4_2","unstructured":"Centers for Disease Control and Prevention SARS-CoV-2 Variants of Concern; www.cdc.gov\/coronavirus\/2019-ncov\/cases-updates\/variant-surveillance\/variant-info.html."},{"key":"e_1_3_3_5_2","doi-asserted-by":"crossref","unstructured":"A. Adiga L. Wang B. Hurt A. Peddireddy P. Porebski S. Venkatramanan B. Lewis M. Marathe All models are useful: Bayesian ensembling for robust high resolution COVID-19 forecasting. Medrxiv 2021.03.12.21253495 (2021); https:\/\/doi.org\/10.1101\/2021.03.12.21253495.","DOI":"10.1101\/2021.03.12.21253495"},{"key":"e_1_3_3_6_2","doi-asserted-by":"crossref","first-page":"e0250110","DOI":"10.1371\/journal.pone.0250110","article-title":"COVID-19: Short term prediction model using daily incidence data","volume":"16","author":"Zhao H.","year":"2021","unstructured":"H. Zhao, N. N. Merchant, A. McNulty, T. A. Radcliff, M. J. Cote, R. S. B. Fischer, H. Sang, M. G. Ory, COVID-19: Short term prediction model using daily incidence data. PLOS ONE 16, e0250110 (2021).","journal-title":"PLOS ONE"},{"key":"e_1_3_3_7_2","doi-asserted-by":"crossref","unstructured":"E. L. Ray N. Wattanachit J. Niemi A. H. Kanji K. House E. Y. Cramer J. Bracher A. Zheng T. K. Yamana X. Xiong S. Woody Y. Wang L. Wang R. L. Walraven V. Tomar K. Sherratt D. Sheldon R. C. Reiner B. A. Prakash D. Osthus M. L. Li E. C. Lee U. Koyluoglu P. Keskinocak Y. Gu Q. Gu G. E. George G. Espa\u00f1a S. Corsetti J. Chhatwal S. Cavany H. Biegel M. Ben-Nun J. Walker R. Slayton V. Lopez M. Biggerstaff M. A. Johansson N. G. Reich Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S.. Medrxiv 2020.08.19.20177493 (2020); https:\/\/doi.org\/10.1101\/2020.08.19.20177493.","DOI":"10.1101\/2020.08.19.20177493"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.nmni.2021.100877"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.ppat.1009499"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.advms.2021.03.005"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2021.03.055"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03412-7"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.xcrm.2021.100255"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2020.08.012"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abf9302"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1126\/sciimmunol.abg6461"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.xcrm.2021.100355"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abd7331"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1093\/molbev\/msi105"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1093\/molbev\/msz197"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2021.09.003"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.abh2644"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.2174\/156802608786786624"},{"key":"e_1_3_3_24_2","unstructured":"U. H. Security SARS-CoV-2 Variants of Concern and Variants Under Investigation in England: Technical Briefing 27 (2021); https:\/\/assets.publishing.service.gov.uk\/government\/uploads\/system\/uploads\/attachment_data\/file\/1029715\/technical-briefing-27.pdf."},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyw328"},{"key":"e_1_3_3_26_2","doi-asserted-by":"crossref","unstructured":"A. L. Cathcart C. Havenar-Daughton F. A. Lempp D. Ma M. A. Schmid M. L. Agostini B. Guarino J. D. Iulio L. E. Rosen H. Tucker J. Dillen S. Subramanian B. Sloan S. Bianchi D. Pinto C. Saliba J. A. Wojcechowskyj J. Noack J. Zhou H. Kaiser A. Chase M. Montiel-Ruiz E. Dellota A. Park R. Spreafico A. Sahakyan E. J. Lauron N. Czudnochowski E. Cameroni S. Ledoux A. Werts C. Colas L. Soriaga A. Telenti L. A. Purcell S. Hwang G. Snell H. W. Virgin D. Corti C. M. Hebner The dual function monoclonal antibodies VIR-7831 and VIR-7832 demonstrate potent in vitro and in vivo activity against SARS-CoV-2. biorxiv 2021.03.09.434607 [ Preprint ] (2021); https:\/\/doi.org\/10.1101\/2021.03.09.434607.","DOI":"10.1101\/2021.03.09.434607"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03807-6"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbrc.2020.11.075"},{"key":"e_1_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41421-021-00268-z"},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2020.108185"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1473-3099(17)30238-4"},{"key":"e_1_3_3_32_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1002764"},{"key":"e_1_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkaa1053"},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.xcrm.2021.100204"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chom.2020.11.007"}],"container-title":["Science Translational Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.science.org\/doi\/pdf\/10.1126\/scitranslmed.abk3445","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,16]],"date-time":"2024-01-16T13:43:50Z","timestamp":1705412630000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.science.org\/doi\/10.1126\/scitranslmed.abk3445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,23]]},"references-count":34,"journal-issue":{"issue":"633","published-print":{"date-parts":[[2022,2,23]]}},"alternative-id":["10.1126\/scitranslmed.abk3445"],"URL":"https:\/\/doi.org\/10.1126\/scitranslmed.abk3445","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.06.21.21259286","asserted-by":"object"}]},"ISSN":["1946-6234","1946-6242"],"issn-type":[{"value":"1946-6234","type":"print"},{"value":"1946-6242","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,23]]},"article-number":"eabk3445"}}