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Genotypic coreceptor analysis


Thielen,  Alexander
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

Lengauer,  Thomas
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Sierra, S., Kaiser, R., Thielen, A., & Lengauer, T. (2007). Genotypic coreceptor analysis. European Journal of Medical Research, 12(9), 453-462.

HIV infects target cells by binding of its envelope gp120 protein to CD4 and a coreceptor on the cell surface. In vivo, the different HIV-strains use either CCR5 or CXCR4 as coreceptor. CCR5-using strains are named R5 viruses, while CXCR4-using strains are named X4. X4 viruses usually occur in the later stages. Coreceptor usage is a marker for disease progression. Additionally interest on coreceptors continually raises as a consequence of the development of a new class of antiretroviral drugs, namely the coreceptor antagonists or blockers. These specific drugs block the CCR5 or the CXCR4 coreceptors. So far, the CXCR4 blockers are not allowed to be used in the clinical practice due to their severe side effects. On the other hand, CCR5 blockers are currently in clinical practice, although they can only be administered after a baseline determination of the coreceptor usage of the predominant viral strain. Most of the coreceptor analyses in clinical cohorts have been performed with commercially available phenotypic assays. As for resistance testing of NRTIs, NNRTIs and PIs, efforts have also been made to predict the coreceptor usage from the genotype of the viruses. Different rules have been published based on the amino acid sequence of the Env-V3 region of HIV-gp120, which is known to be the major determinant of coreceptor usage. Among these, the most widely used is the 11/25 rule. Recently, bioinformatics driven prediction systems have been developed. Three of the interpretation systems are freely available via internet: WetCat, WebPSSM, geno2pheno[coreceptor]. All three systems focus on the Env-V3 region and take the amino acid sequence only into account. They learn from phenotypic and corresponding genotypic data. So far, two cohorts have been analyzed with such a genotypic approach and provided frequencies of R5 virus strains that are within the range of those reported with phenotypic assays. For one of the systems, geno2pheno[coreceptor], additional clinical data (e.g. CD4+T-cell counts) or structural information can be used to improve the prediction. Such genotypic systems provide the possibility for rapid screening of patients who may be administered with CCR5 blockers like the recently licensed Maraviroc.