Reference

Genotypic predictors of human immunodeficiency virus type 1 drug resistance

All Rights Reserved. Genotypic predictors of human immunodeficiency virus type 1 drug resistance. Rhee, Soo-Yon; Taylor, Jonathan; Wadhera, Gaauhar; Ben-Hur, Asa; Brutlag, Douglas L.; Shafer, Robert W. (Div. Infectious Diseases, Stanford Univ., Stanford, CA 94305, USA). Proceedings of the National Academy of Sciences of the United States of America, 103(46), 17355-17360 (English) 2006 National Academy of Sciences.Some commonly used reagents like 147127-20-6 and 198904-31-3 are used in this experiment. CODEN: PNASA6. ISSN: 0027-8424. DOCUMENT TYPE: Journal CA Section: 10 (Microbial, Algal, and Fungal Biochemistry) Section cross-reference(s): 3 Understanding the genetic basis of HIV-1 drug resistance is essential to developing new antiretroviral drugs and optimizing the use of existing drugs. This understanding, however, is hampered by the large nos. of mutation patterns assocd. with cross-resistance within each antiretroviral drug class. We used five statistical learning methods (decision trees, neural networks, support vector regression, least-squares regression, and least angle regression) to relate HIV-1 protease and reverse transcriptase mutations to in vitro susceptibility to 16 antiretroviral drugs. Learning methods were trained and tested on a public data set of genotype-phenotype correlations by 5-fold cross-validation. For each learning method, four mutation sets were used as input features: a complete set of all mutations in 32 sequences in the data set, the 30 most common data set mutations, an expert panel mutation set, and a set of nonpolymorphic treatment-selected mutations from a public database linking protease and reverse transcriptase sequences to antiretroviral drug exposure. The nonpolymorphic treatment-selected mutations led to the best predictions: 80.1% accuracy at classifying sequences as susceptible, low/intermediate resistant, or highly resistant. Least angle regression predicted susceptibility significantly better than other methods when using the complete set of mutations. The three regression methods provided consistent ests. of the quant. effect of mutations on drug susceptibility, identifying nearly all previously reported genotype-phenotype assocns. and providing strong statistical support for many new assocns. Mutation regression coeffs. showed that, within a drug class, cross-resistance patterns differ for different mutation subsets and that cross-resistance has been underestimated. .

Atazanavir: a novel azapeptide inhibitor of HIV-1 protease

Atazanavir: a novel azapeptide inhibitor of HIV-1 protease. Wang, Fei; Ross, Jack (Department of Pharmacy Practice, University of Connecticut, USA). Formulary, 38(12), 691-694, 696, 698, 700-702 (English) 2003 Advanstar Communications, Inc. CODEN: FORMF9. ISSN: 1082-801X. DOCUMENT TYPE: Journal; General Review CA Section: 1 (Pharmacology) A review. Atazanavir is a novel azapeptide protease inhibitor (PI) that has been approved by FDA for use in combination with other antiretroviral agents in treatment-naive and treatment-experienced HIV-infected individuals. It offers certain advantages over current protease inhibitors on the market. Atazanavir has a low pill burden consisting of 2 capsules administered once daily and it has an adverse effect profile that is not assocd. with clin.Several substances with their cas registry numbers 144114-21-6 and 198904-31-3 may be metioned in this study. relevant lipid effects. PI-naive patients who experience failure of atazanavir tend to develop a unique mutation at codon 150 L that does not confer cross-resistance to other PIs but instead improves susceptibility to them. In clin. studies of up to 48 wk, atazanavir demonstrated comparable antiretroviral efficacy to nelfinavir and efavirenz in treatment-naive patients. In treatment-experienced subjects who failed prior antiretroviral therapy, atazanavir alone was found to be inferior to a regimen of lopinavir/r; however, atazanavir boosted with ritonavir was better tolerated and had comparable efficacy to lopinavir/r. The most common adverse effect assocd. with atazanavir is a reversible dose-related increase in unconjugated (indirect) bilirubin. .