This Article Full Text Full Text (PDF) An author's correction has been published Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by You, L. Articles by Rögnvaldsson, T. Search for Related Content PubMed PubMed Citation Articles by You, L. Articles by Rögnvaldsson, T.

Comprehensive Bioinformatic Analysis of the Specificity of Human Immunodeficiency Virus Type 1 Protease

School of Information Science, Computer and Electrical Engineering, Halmstad University, Halmstad, Sweden,¹ Division of Hematology and Transfusion Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden, and Division of Molecular Toxicology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden²

Received 28 November 2004/ Accepted 1 July 2005

Rapidly developing viral resistance to licensed human immunodeficiency virus type 1 (HIV-1) protease inhibitors is an increasing problem in the treatment of HIV-infected individuals and AIDS patients. A rational design of more effective protease inhibitors and discovery of potential biological substrates for the HIV-1 protease require accurate models for protease cleavage specificity. In this study, several popular bioinformatic machine learning methods, including support vector machines and artificial neural networks, were used to analyze the specificity of the HIV-1 protease. A new, extensive data set (746 peptides that have been experimentally tested for cleavage by the HIV-1 protease) was compiled, and the data were used to construct different classifiers that predicted whether the protease would cleave a given peptide substrate or not. The best predictor was a nonlinear predictor using two physicochemical parameters (hydrophobicity, or alternatively polarity, and size) for the amino acids, indicating that these properties are the key features recognized by the HIV-1 protease. The present in silico study provides new and important insights into the workings of the HIV-1 protease at the molecular level, supporting the recent hypothesis that the protease primarily recognizes a conformation rather than a specific amino acid sequence. Furthermore, we demonstrate that the presence of 1 to 2 lysine residues near the cleavage site of octameric peptide substrates seems to prevent cleavage efficiently, suggesting that this positively charged amino acid plays an important role in hindering the activity of the HIV-1 protease.

This article has been cited by other articles:

• Coren, L. V., Thomas, J. A., Chertova, E., Sowder, R. C. II, Gagliardi, T. D., Gorelick, R. J., Ott, D. E. (2007). Mutational Analysis of the C-Terminal Gag Cleavage Sites in Human Immunodeficiency Virus Type 1. J. Virol. 81: 10047-10054 [Abstract] [Full Text]