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SHIVA - a web application for drug resistance and tropism testing in HIV

BACKGROUND: Drug 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 in...

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Autores principales: Riemenschneider, Mona, Hummel, Thomas, Heider, Dominik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994198/
https://www.ncbi.nlm.nih.gov/pubmed/27549230
http://dx.doi.org/10.1186/s12859-016-1179-2
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author Riemenschneider, Mona
Hummel, Thomas
Heider, Dominik
author_facet Riemenschneider, Mona
Hummel, Thomas
Heider, Dominik
author_sort Riemenschneider, Mona
collection PubMed
description BACKGROUND: Drug 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. RESULTS: 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), 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. CONCLUSIONS: SHIVA 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.
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spelling pubmed-49941982016-08-31 SHIVA - a web application for drug resistance and tropism testing in HIV Riemenschneider, Mona Hummel, Thomas Heider, Dominik BMC Bioinformatics Software BACKGROUND: Drug 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. RESULTS: 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), 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. CONCLUSIONS: SHIVA 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. BioMed Central 2016-08-22 /pmc/articles/PMC4994198/ /pubmed/27549230 http://dx.doi.org/10.1186/s12859-016-1179-2 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Riemenschneider, Mona
Hummel, Thomas
Heider, Dominik
SHIVA - a web application for drug resistance and tropism testing in HIV
title SHIVA - a web application for drug resistance and tropism testing in HIV
title_full SHIVA - a web application for drug resistance and tropism testing in HIV
title_fullStr SHIVA - a web application for drug resistance and tropism testing in HIV
title_full_unstemmed SHIVA - a web application for drug resistance and tropism testing in HIV
title_short SHIVA - a web application for drug resistance and tropism testing in HIV
title_sort shiva - a web application for drug resistance and tropism testing in hiv
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4994198/
https://www.ncbi.nlm.nih.gov/pubmed/27549230
http://dx.doi.org/10.1186/s12859-016-1179-2
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