{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T15:23:13Z","timestamp":1784733793405,"version":"3.55.0"},"reference-count":37,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2008,9,5]],"date-time":"2008-09-05T00:00:00Z","timestamp":1220572800000},"content-version":"vor","delay-in-days":1343,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biotechnology Progress"],"published-print":{"date-parts":[[2005,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A novel neural\u2010network\u2010based model has been developed for the prediction of <jats:italic>N<\/jats:italic>\u2010linked glycosylation characteristics related to glycosylation site\u2010occupancy. Intracellular oligosaccharide transfer to a polypeptide is known to be either robust or dependent upon culture conditions during pharmaceutical production. This glycan attachment is classified by the model as <jats:italic>robust<\/jats:italic> or <jats:italic>variable<\/jats:italic> and is based on an input of the polypeptide primary sequence around the site of glycosylation. The glycosylation model utilizes multiple recurrent neural networks followed by a perceptron classifier. The input length of the polypeptide chain around the site of glycosylation (glycosylation window) was optimized through multiple independent training sessions. Incorporation of five residues prior (<jats:italic>n<\/jats:italic> \u2013 5) to the site of glycosylation (<jats:italic>n<\/jats:italic>) and four residues beyond (<jats:italic>n<\/jats:italic> + 4) the glycan attachment site led to optimal network performance. The size of the glycosylation window for site\u2010occupancy determination is much larger than has been previously reported. This model was developed to evaluate the effects of theoretical polypeptide mutations on glycosylation site\u2010occupancy characteristics. Following correct prediction of the model testing data set, 20 independent networks were used to predict site\u2010occupancy characteristics of wild\u2010type and mutants of the rabies virus glycoprotein (rgp). Simulation results strongly correlated with previously published experimental results (Kasturi, L.; Hegang, C.; Shakin\u2010Eshleman, S. H. Regulation of N\u2010linked core glycosylation: use of a site\u2010directed mutagenesis approach to identify Asn\u2010Xaa\u2010Ser\/Thr sequons that are poor oligosacchride acceptors. <jats:italic>Biochem. J.<\/jats:italic><jats:bold>1997<\/jats:bold>, <jats:italic>323<\/jats:italic>, 415\u2013419. Mellquist, J. L.; Kasturi, L.; Spitalnik, S. L.; Shakin\u2010Eshleman, S. H. The amino acid following an Asn\u2010X\u2010Ser\/Thr sequon is an important determinant of N\u2010linked core glycosylation efficiency. <jats:italic>Biochemistry<\/jats:italic> <jats:bold>1998<\/jats:bold>, , 6833\u20136837). Further simulations on purely theoretical sequences suggested that influences of charged residues were a subset of multiple mechanisms in the determination of glycosylation site\u2010occupancy.<\/jats:p>","DOI":"10.1021\/bp0502375","type":"journal-article","created":{"date-parts":[[2005,12,2]],"date-time":"2005-12-02T00:20:48Z","timestamp":1133482848000},"page":"1653-1662","source":"Crossref","is-referenced-by-count":19,"title":["Variable Site\u2010Occupancy Classification of <i>N<\/i>\u2010Linked Glycosylation Using Artificial Neural Networks"],"prefix":"10.1002","volume":"21","author":[{"given":"Ryan S.","family":"Senger","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. Nazmul","family":"Karim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2008,9,5]]},"reference":[{"key":"e_1_2_6_2_2","doi-asserted-by":"publisher","DOI":"10.1042\/bj3230415"},{"key":"e_1_2_6_3_2","doi-asserted-by":"publisher","DOI":"10.1021\/bi972217k"},{"key":"e_1_2_6_4_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.bi.54.070185.003215"},{"key":"e_1_2_6_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4157(87)90018-9"},{"key":"e_1_2_6_6_2","doi-asserted-by":"publisher","DOI":"10.1096\/fasebj.10.8.8666161"},{"key":"e_1_2_6_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0962-8924(01)01925-0"},{"key":"e_1_2_6_8_2","doi-asserted-by":"publisher","DOI":"10.1093\/glycob\/12.4.43R"},{"key":"e_1_2_6_9_2","doi-asserted-by":"publisher","DOI":"10.1093\/glycob\/2.2.99"},{"key":"e_1_2_6_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0290(20001005)70:1<25::AID-BIT4>3.0.CO;2-Q"},{"key":"e_1_2_6_11_2","doi-asserted-by":"publisher","DOI":"10.1021\/bp025715f"},{"key":"e_1_2_6_12_2","doi-asserted-by":"publisher","DOI":"10.1021\/bi00469a021"},{"key":"e_1_2_6_13_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1016474026501"},{"key":"e_1_2_6_14_2","doi-asserted-by":"publisher","DOI":"10.1021\/bp034109x"},{"key":"e_1_2_6_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/0167-4838(85)90123-2"},{"key":"e_1_2_6_16_2","volume-title":"Biochemical Engineering","author":"Blanch H. W.","year":"1997"},{"key":"e_1_2_6_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/nbt0590-421"},{"key":"e_1_2_6_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/0268-9499(92)90070-X"},{"key":"e_1_2_6_19_2","doi-asserted-by":"publisher","DOI":"10.4052\/tigg.8.115"},{"key":"e_1_2_6_20_2","doi-asserted-by":"publisher","DOI":"10.1042\/0264-6021:3550245"},{"key":"e_1_2_6_21_2","doi-asserted-by":"publisher","DOI":"10.1093\/glycob\/cwh008"},{"key":"e_1_2_6_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(90)90154-E"},{"key":"e_1_2_6_23_2","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1993.1413"},{"key":"e_1_2_6_24_2","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1999.3091"},{"key":"e_1_2_6_25_2","first-page":"80","volume-title":"Sequence Learning, LNAI 1828","author":"Baldi P.","year":"2000"},{"key":"e_1_2_6_26_2","doi-asserted-by":"publisher","DOI":"10.1002\/prot.10082"},{"key":"e_1_2_6_27_2","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.2000.3741"},{"key":"e_1_2_6_28_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/18.1.213"},{"key":"e_1_2_6_29_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.252626399"},{"key":"e_1_2_6_30_2","first-page":"575","article-title":"The principled design of large\u2010scale recursive neural network architectures\u2010DAG\u2010RNNs and the protein structure prediction problem","volume":"4","author":"Baldi P.","year":"2003","journal-title":"Mach. Learn."},{"key":"e_1_2_6_31_2","doi-asserted-by":"publisher","DOI":"10.1002\/prot.10069"},{"key":"e_1_2_6_32_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/17.suppl_1.S234"},{"key":"e_1_2_6_33_2","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0134(19990815)36:3<340::AID-PROT8>3.0.CO;2-D"},{"key":"e_1_2_6_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-2836(02)00885-9"},{"key":"e_1_2_6_35_2","doi-asserted-by":"publisher","DOI":"10.1006\/jmbi.1995.0339"},{"key":"e_1_2_6_36_2","doi-asserted-by":"publisher","DOI":"10.1038\/299371a0"},{"key":"e_1_2_6_37_2","doi-asserted-by":"publisher","DOI":"10.1006\/jsbi.2001.4336"},{"key":"e_1_2_6_38_2","doi-asserted-by":"publisher","DOI":"10.1002\/prot.10051"}],"container-title":["Biotechnology Progress"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1021%2Fbp0502375","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aiche.onlinelibrary.wiley.com\/doi\/pdf\/10.1021\/bp0502375","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T23:58:50Z","timestamp":1760054330000},"score":1,"resource":{"primary":{"URL":"https:\/\/aiche.onlinelibrary.wiley.com\/doi\/10.1021\/bp0502375"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,1]]},"references-count":37,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2005,1]]}},"alternative-id":["10.1021\/bp0502375"],"URL":"https:\/\/doi.org\/10.1021\/bp0502375","archive":["Portico"],"relation":{},"ISSN":["8756-7938","1520-6033"],"issn-type":[{"value":"8756-7938","type":"print"},{"value":"1520-6033","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,1]]}}}