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State of the art prediction of HIV-1 protease cleavage sites
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Biochemial structure and function.
2015 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 31, no 8, 1204-1210 p.Article in journal (Refereed) Published
Abstract [en]

Motivation: Understanding the substrate specificity of human immunodeficiency virus (HIV)-1 protease is important when designing effective HIV-1 protease inhibitors. Furthermore, characterizing and predicting the cleavage profile of HIV-1 protease is essential to generate and test hypotheses of how HIV-1 affects proteins of the human host. Currently available tools for predicting cleavage by HIV-1 protease can be improved.

Results: The linear support vector machine with orthogonal encoding is shown to be the best predictor for HIV-1 protease cleavage. It is considerably better than current publicly available predictor services. It is also found that schemes using physicochemical properties do not improve over the standard orthogonal encoding scheme. Some issues with the currently available data are discussed.

Place, publisher, year, edition, pages
2015. Vol. 31, no 8, 1204-1210 p.
National Category
Other Medical Sciences not elsewhere specified
URN: urn:nbn:se:uu:diva-256139DOI: 10.1093/bioinformatics/btu810ISI: 000354453700007PubMedID: 25504647OAI: oai:DiVA.org:uu-256139DiVA: diva2:824750
Available from: 2015-06-22 Created: 2015-06-22 Last updated: 2015-08-04Bibliographically approved

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