Abstract
BackgroundDrug resistance testing is mandatory in antiretroviral therapy in human immunodeficiency virus (HIV) infected patients for successful treatment. The emergence of resistances against antiretroviral agents remains the major obstacle in inhibition of viral replication and thus to control infection. Due to the high mutation rate the virus is able to adapt rapidly under drug pressure leading to the evolution of resistant variants and finally to therapy failure.ResultsWe developed a web service for drug resistance prediction of commonly used drugs in antiretroviral therapy, i.e., protease inhibitors (PIs), reverse transcriptase inhibitors (NRTIs and NNRTIs), and integrase inhibitors (INIs), but also for the novel drug class of maturation inhibitors. Furthermore, co-receptor tropism (CCR5 or CXCR4) can be predicted as well, which is essential for treatment with entry inhibitors, such as Maraviroc. Currently, SHIVA provides 24 prediction models for several drug classes. SHIVA can be used with single RNA/DNA or amino acid sequences, but also with large amounts of next-generation sequencing data and allows prediction of a user specified selection of drugs simultaneously. Prediction results are provided as clinical reports which are sent via email to the user.ConclusionsSHIVA represents a novel high performing alternative for hitherto developed drug resistance testing approaches able to process data derived from next-generation sequencing technologies. SHIVA is publicly available via a user-friendly web interface.
Highlights
Drug resistance testing is mandatory in antiretroviral therapy in human immunodeficiency virus (HIV) infected patients for successful treatment
We developed a web service for HIV drug resistance prediction incorporating models for resistance testing of Protease inhibitor (PI), Non-nucleoside reverse transcriptase inhibitor (NNRTI), Nucleotide reverse transcriptase inhibitor (NRTI), Integrase inhibitor (INI), BVM, as well as co-receptor tropism prediction
Prediction results are provided as clinical reports presenting the results in a comprehensible and clearly presented way and sent via email to the user
Summary
We developed a web service for drug resistance prediction of commonly used drugs in antiretroviral therapy, i.e., protease inhibitors (PIs), reverse transcriptase inhibitors (NRTIs and NNRTIs), and integrase inhibitors (INIs), and for the novel drug class of maturation inhibitors. Co-receptor tropism (CCR5 or CXCR4) can be predicted as well, which is essential for treatment with entry inhibitors, such as Maraviroc. SHIVA provides 24 prediction models for several drug classes. SHIVA can be used with single RNA/DNA or amino acid sequences, and with large amounts of next-generation sequencing data and allows prediction of a user specified selection of drugs simultaneously. Prediction results are provided as clinical reports which are sent via email to the user
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