{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T12:50:19Z","timestamp":1782910219300,"version":"3.54.5"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,2,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: We analysed 148 human drug target proteins and 3573 non-drug targets to identify differences in their properties and to predict new potential drug targets.<\/jats:p>\n               <jats:p>Results: Drug targets are rare in organelles; they are more likely to be enzymes, particularly oxidoreductases, transferases or lyases and not ligases; they are involved in binding, signalling and communication; they are secreted; and have long lifetimes, shown by lack of PEST signals and the presence of N-glycosylation. This can be summarized into eight key properties that are desirable in a human drug target, namely: high hydrophobicity, high length, SignalP motif present, no PEST motif, more than two N-glycosylated amino acids, not more than one O-glycosylated Ser, low pI and membrane location. The sequence features were used as inputs to a support vector machine (SVM), allowing the assignment of any sequence to the drug target or non-target classes with an accuracy in the training set of 96%. We identified 668 proteins (23%) in the non-target set that have target-like properties. We suggest that drug discovery programmes would be more likely to succeed if new targets are chosen from this set or their homologues.<\/jats:p>\n               <jats:p>Contact: \u00a0andrew.doig@manchester.ac.uk<\/jats:p>\n               <jats:p>Supplementary Information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp002","type":"journal-article","created":{"date-parts":[[2009,1,23]],"date-time":"2009-01-23T01:13:55Z","timestamp":1232673235000},"page":"451-457","source":"Crossref","is-referenced-by-count":290,"title":["Properties and identification of human protein drug targets"],"prefix":"10.1093","volume":"25","author":[{"given":"Tala M.","family":"Bakheet","sequence":"first","affiliation":[{"name":"1 Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT and 2Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew J.","family":"Doig","sequence":"additional","affiliation":[{"name":"1 Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT and 2Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2009,1,21]]},"reference":[{"key":"2023013110100633400_B1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene Ontology: tool for the unification of biology","volume":"25","author":"Ashburner","year":"2000","journal-title":"Nat. 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