Abstract

Bioinformatics tools for coreceptor usage prediction for use of CCR5 antagonists

L.B. Arruda¹, C.R. Gonsalez², A.J.S. Duarte³, J. Casseb<sup>1

1</sup>Institute of Tropical Medicine/Unviversity of Sao Paulo, Laboratory of Investigation in Dermatology and Immunodeficiencies - LIM56, Sao Paulo, Brazil, ²Hospital of Clinics/School of Medicine/University of Sao Paulo, Out-clinic Ambulatory of Secondary Immunodeficiencies - ADEE3002, Sao Paulo, Brazil, ³School of Medicine/University of Sao Paulo, Laboratory of Investigation in Dermatology and Immunodeficiencies - LIM56, Sao Paulo, Brazil

Background: The clinical use of CCR5 antagonists requires the coreceptor usage determination of viral strains from the infected individual. The bioinformatics predictive programs could be a more accessible alternative for the screening of candidates for the use of CCR5 antagonists compared to the gold-standard assays to coreceptor usage determination.
Methods: DNA samples from 82 HIV infected subjects followed in our out-clinic (ADEE3002) were amplified by PCR for the V3 loop region and sequenced. The coreceptor usage was performed from the V3 loop sequences using nine predictive tests of bioinformatics platforms (WetCat, WebPSSM and geno2pheno[coreceptor]) and the net charge of the V3 sequences was calculated. Additionally, 79 V3 sequences with known coreceptor usage from the Los Alamos data base were tested using the same bioinformatics platforms aiming to evaluate the sensibility and specificity of the tests.
Results: 49/82 (59.8%) of patients sequences were discordant for at least one of the nine predictive tests. The assessing of the net charge showed that 9/49 (18.4%) of these discordant results had net charges < 4, suggesty these patients were not infected by X4 virus. Regarding the concordant results (33/82; 40.2%), 29/33 (87.9%) were predicted as being R5 strains and 4/33 (12.1%) were predicted as being X4. The evaluation of the 79 Los Alamos sequences revealed that the nine bioinformatics tests presented over 80% of sensitivity and specificity. The concordance between known and predicted coreceptor usage was over 88% for all tests used, and the SVM test (WetCat) had the best concordance rate (75/79; 95%).
Conclusions: Currently, the predictive systems for coreceptor usage determination cannot be used alone; it is necessary to confirm the results by a gold standard test. However, the prediction systems associated with net charge determination could represent a more accessible strategy to screening candidates to use the CCR5 antagonists.
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