{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T22:32:07Z","timestamp":1768516327064,"version":"3.49.0"},"posted":{"date-parts":[[2024,12,12]]},"group-title":"Biophysics","reference-count":0,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T00:00:00Z","timestamp":1733961600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"NIH\/NIGMS","award":["R01 GM083960 and P41 GM109824"],"award-info":[{"award-number":["R01 GM083960 and P41 GM109824"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,5,2]]},"abstract":"<jats:p>Building an accurate atomic structure model of a protein into a cryo-electron microscopy (cryo-EM) map at worse than 3 Angstrom resolution is difficult. To facilitate this task, we devised a method for assigning the amino acid residue sequence to the backbone fragments traced in an input cryo-EM map (EMSequenceFinder). EMSequenceFinder relies on a Bayesian scoring function for ranking 20 standard amino acid residue types at a given backbone position, based on the fit to a density map, map resolution, and secondary structure propensity. The fit to a density is quantified by a convolutional neural network that was trained on ~5.56 million amino acid residue densities extracted from cryo-EM maps at 3-10 Angstrom resolution and corresponding atomic structure models deposited in the Electron Microscopy Data Bank (EMDB). We benchmarked EMSequenceFinder by predicting the sequences of 58,044 distinct \u0251-helix and \u03b2-strand fragments, given the fragment backbone coordinates fitted in their density maps. EMSequenceFinder identifies the correct sequence as the best-scoring sequence in 77.8% of these cases. We also assessed EMSequenceFinder on separate datasets of cryo-EM maps at resolutions from 4 to 6 \u00c5. The accuracy of EMSequenceFinder (63.5%) was better than that of three tested state-of-the-art methods, including findMysequence (45%), ModelAngelo (27%), and sequence_from_map in Phenix (12.9%). We further illustrate EMSequenceFinder by threading the SARS-CoV-2 NSP2 sequence into eight cryo-EM maps at resolutions from 3.7 to 7.0 Angstrom. EMSequenceFinder is implemented in our open-source Integrative Modeling Platform (IMP) program. Thus, it is expected to be helpful for integrative structure modeling based on a cryo-EM map and other information, such as models of protein complex components and chemical crosslinks between them. EMSequenceFinder is available as part of our open source IMP distribution at https:\/\/integrativemodeling.org\/.<\/jats:p>","DOI":"10.1101\/2024.12.10.627859","type":"posted-content","created":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T23:21:08Z","timestamp":1734045668000},"source":"Crossref","is-referenced-by-count":0,"title":["Recognizing amino acid sidechains in a medium resolution cryo-electron density map"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5047-6985","authenticated-orcid":false,"given":"Dibyendu","family":"Mondal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7578-7467","authenticated-orcid":false,"given":"Vipul","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2780-1572","authenticated-orcid":false,"given":"Tadej","family":"Satler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7196-5078","authenticated-orcid":false,"given":"Rakesh","family":"Ramachandran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Saltzberg","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilan","family":"Chemmama","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8327-1687","authenticated-orcid":false,"given":"Kala Bharath","family":"Pilla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4717-1467","authenticated-orcid":false,"given":"Ignacia","family":"Echeverria","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benjamin M.","family":"Webb","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7432-3211","authenticated-orcid":false,"given":"Meghna","family":"Gupta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2238-8590","authenticated-orcid":false,"given":"Kliment A","family":"Verba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0435-6197","authenticated-orcid":false,"given":"Andrej","family":"Sali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1101\/2024.12.10.627859","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T07:39:50Z","timestamp":1768462790000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.1101\/2024.12.10.627859"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,12]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1101\/2024.12.10.627859","relation":{"is-preprint-of":[{"id-type":"doi","id":"10.1002\/pro.70217","asserted-by":"subject"}]},"subject":[],"published":{"date-parts":[[2024,12,12]]},"subtype":"preprint"}}