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Schierz, A. C. and King, R. D., 2009. Drugs and Drug-like compounds: Discriminating Approved Pharmaceuticals from Screening-Library Compounds. In: Pattern Recognition in Bioinformatics. Berlin/Heidelberg: Springer, pp. 331-343.
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DOI: 10.1007/978-3-642-04031-3_29
Abstract
Compounds in drug screening-libraries should resemble pharmaceuticals. To operationally test this, we analysed the compounds in terms of known drug-like filters and developed a novel machine learning method to discriminate approved pharmaceuticals from “drug-like” compounds. This method uses both structural features and molecular properties for discrimination. The method has an estimated accuracy of 91% in discriminating between the Maybridge HitFinder library and approved pharmaceuticals, and 99% between the NATDiverse collection (from Analyticon Discovery) and approved pharmaceuticals. These results show that Lipinski’s Rule of 5 for oral absorption is not sufficient to describe “drug-likeness” and be the main basis of screening-library design.
| Item Type: | Book Section |
|---|---|
| ISBN: | 978-3-642-04030-6 |
| Series Name: | Lecture Notes in Computer Science |
| Number: | 5780/2 |
| Series Name: | Lecture Notes in Computer Science |
| Additional Information: | Paper given at 4th IAPR International Conference on Pattern Recognition in Bioinformatics, 7-9 September 2009 |
| Subjects: | Generalities > Computer Science and Informatics > Artificial Intelligence Science > Chemistry |
| Group: | School of Design, Engineering & Computing > Smart Technology Research Centre |
| ID Code: | 13335 |
| Deposited By: | Dr Amanda C. Schierz LEFT |
| Deposited On: | 21 Mar 2010 19:32 |
| Last Modified: | 07 Mar 2013 15:23 |
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