{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T18:28:35Z","timestamp":1760984915396},"reference-count":10,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Mass spectrometry is being increasingly used in the structural elucidation of mega-Dalton protein complexes in an approach termed MS3D, referring to the application of MS to the study of macromolecular structures. This involves the identification of cross-linked residues in the constituent proteins of chemically cross-linked multi-subunit complexes. AnchorMS was developed to simplify MS3D studies by identifying cross-linked peptides in complex peptide mixtures, and to determine the specific residues involved in each cross-link. When identifying cross-linked peptide pairs (CLPP), AnchorMS implements a mathematical model to exclude false positives by using a dynamic score threshold to estimate the number of false-positive peak matches expected in an MS\/MS spectrum. This model was derived from CLPPs with randomly generated sequences. AnchorMS does not require specific sample labeling or pre-treatment, and AnchorMS is especially suited for discriminating between CLPPs that differ only in the cross-linked residue pairs.<\/jats:p>\n               <jats:p>Availability: AnchorMS was coded in Python, and is available as a free web service at cbio.ufs.ac.za\/AnchorMS.<\/jats:p>\n               <jats:p>Contact: \u00a0patterh@ufs.ac.za<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt617","type":"journal-article","created":{"date-parts":[[2013,11,1]],"date-time":"2013-11-01T06:53:15Z","timestamp":1383288795000},"page":"125-126","source":"Crossref","is-referenced-by-count":2,"title":["AnchorMS: a bioinformatics tool to derive structural information from the mass spectra of cross-linked protein complexes"],"prefix":"10.1093","volume":"30","author":[{"given":"Shannon L.N.","family":"Mayne","sequence":"first","affiliation":[{"name":"Advanced Biomolecular Research Cluster, University of the Free State, P.O. Box 339, Bloemfontein 9300, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hugh-G.","family":"Patterton","sequence":"additional","affiliation":[{"name":"Advanced Biomolecular Research Cluster, University of the Free State, P.O. Box 339, Bloemfontein 9300, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,10,30]]},"reference":[{"key":"2023012710375454500_btt617-B1","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1038\/nbt1240","article-title":"A probability-based approach for high-throughput protein phosphorylation analysis and site localization","volume":"24","author":"Beausoleil","year":"2006","journal-title":"Nat. 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