EuResist for CHAIN
The project CHAIN (Collaborative HIV and Anti-HIV Drug Resistance Network), funded by the European Commission within the 7th FP, begun on 1 April 2009 and involves 22 partners, among which EuResist Network GEIE.
CHAIN is a large scale integrating project aimed to effectively and durably combat new and existing anti-HIV drug resistance in clinical settings, with a special emphasis on Eastern Europe and in heavily affected resource-poor regions in Africa.
In such context, a specific effort is addressed to provide for a sustainable evidence base to better control the epidemic and management of infected individuals, through development of comprehensive macro and micro epidemiological bioinformatics tools that can be used to predict epidemiological trends and prevent accumulation of drug resistance.
In what follows, you will find a list of the main existing HIV resistance prediction systems and of our favorites tools for tropism prediction, subtyping and mutations extraction.
DRUG RESISTANCE PREDICTION TOOLS
1. Genotypic drug resistance prediction
REGA - The genotypic HIV resistance interpretation algorithm developed and maintained by the REGA Institute for Medical Research at Leuven, Belgium is another very popular system. The previous and current algorithms are available as pdf and xml files.
HIVdb - The Stanford University HIV Drug Resistance Database is the most comprehensive web site devoted to HIV drug resistance, providing a very popular and regularly updated genotypic resistance interpretation algorithm (HIVdb). The system accepts user-submitted protease (PR) and reverse transcriptase (RT) sequences and returns inferred levels of resistance to 19 PR and RT inhibitors. Its purpose is educational and as such it provides extensive comments and a highly transparent scoring system that is hyperlinked to data in the HIV Drug Resistance Database. Other relevant features include HIValg, a program to compare the most commonly used genotypic resistance algorithms and an expanding array of statistics and query pages on HIV drug resistance.
ANRS - The French ANRS (National Agency for AIDS Research) AC11 Resistance group provides HIV-1 genotypic drug resistance interpretation's algorithms in order to guide physicians in the choice of antiretroviral treatment. These algorithms are mainly based on correlation between drug resistance mutations and virological outcome from patients failing antiretroviral therapy. The rules are presented as tables listing mutations conferring genotypic resistance or possible genotypic resistance to anti-HIV drugs.
HIV-GRADE - HIV-GRADE (Genotypic Resistance-Algorithm Deutschland) has been developed in the context of other frequently used interpretation systems including the ANRS algorithm, the Stanford database and geno2pheno. Additionally, extensive databases including data of thousands of genotypes, pairs of genotypic and phenotypic data, therapy response, clinical experience of the participating experts and last but not least results from clinical trials have influenced the algorithm. It presents the prediction results of the other mentioned algorithms (all except EuResist) on one single page, allowing easy comparison.
2. Phenotypic drug resistance prediction
geno2pheno - Developed at the Max Planck Institute for Bioinformatics in Saarbrucken, geno2pheno is the only freely available data-driven system for estimating phenotypic drug resistance from HIV-1 genotype. On submitting an HIV-1 pol-gene DNA sequence you will obtain a sequence alignment to the reference strain HXB2, a list of mutations and different predictions of phenotypic resistance of the respective virus to 17 antiretroviral drugs. Clinical cut-offs can be accepted as defaulted by the system or set by the user.
3. Therapy combination resistance prediction
EuResist Prediction Engine - The system requests HIV genotype and optionally a set of clinical data and returns a prediction of response to common antiretroviral regimens. It has been trained and tested on a set of data derived from clinical practice records of more than 18,000 HIV patients collected in Europe. The internal validation showed a prediction accuracy of 76% when treatment success was defined as achieving a decrease of at least 2 log or an undetectable HIV RNA load at week 8 after treatment start. Ongoing analysis indicates that the same performance is obtained with 24-week prediction.
TROPISM PREDICTION TOOLS
geno2pheno[coreceptor] - geno2pheno[coreceptor] is a bioinformatics tool, currently based on support vector machines, that predicts HIV-1 coreceptor usage from the V3 region of the HIV envelope protein gp120. Very easy to use.
SUBTYPING TOOLS
Rega Subtyping tool Rega HIV-1 & HIV-2 Subtyping Tool (version 2.0) - The Rega HIV-1 & HIV-2 Subtyping tool is designed to use phylogenetic methods in order to identify the subtype or bootscanning methods to determine the recombinant form.
MUTATION EXTRACTOR:
MutExt - The MutExt tool is designed to provide a fast nucleotide sequence alignment, contamination control and customizable output, like list of mutations in CSV format.