Update of the Drug Resistance Mutations in HIV-1: 2004
Since 2000, the International AIDS Society-USA (IAS-USA) Drug Resistance Mutations Group has worked as an independent entity and forged a collaborative process to identify key HIV-1 drug resistance mutations. The goal of the group is to quickly deliver accurate and unbiased information to clinical practitioners on HIV-1 resistance. This April 2005 version of the IAS-USA Drug Resistance Mutations Figures replaces the version published in this journal in October 2004. The IAS-USA Drug Resistance Mutations Figures are designed for use in identifying mutations associated with viral resistance to antiretroviral drugs and in making therapeutic decisions. Care should be taken when using this list of mutations for surveillance or epidemilogic studies of transmission of drug-resistant virus. A number of amino acid substitutions, particularly minor mutations, represent polymorphisms that, in isolation, may not reflect prior drug selective pressure or reduced drug susceptibility.
Available from: Majid Masso
- "The first approach makes use of the entire residual profile (EC scores at all 99 PR or 543 RT positions, All) for each mutant. Next, we consider mutant feature vectors whose components consist of the EC scores only at PR or RT positions for which residue substitutions occur that, according to an expert panel (International Antiviral Society - USA, IAS), are associated with drug resistance [4,30]. Finally, we evaluate the utility of mutant feature vectors whose components consist of the EC scores at PR or RT positions for which residue substitutions occur that are significantly more common in treated versus untreated individuals (nonpolymorphic treatment-selected mutations, TSM) . "
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Successful management of chronic human immunodeficiency virus type 1 (HIV-1) infection with a cocktail of antiretroviral medications can be negatively affected by the presence of drug resistant mutations in the viral targets. These targets include the HIV-1 protease (PR) and reverse transcriptase (RT) proteins, for which a number of inhibitors are available on the market and routinely prescribed. Protein mutational patterns are associated with varying degrees of resistance to their respective inhibitors, with extremes that can range from continued susceptibility to cross-resistance across all drugs.
Here we implement statistical learning algorithms to develop structure- and sequence-based models for systematically predicting the effects of mutations in the PR and RT proteins on resistance to each of eight and eleven inhibitors, respectively. Employing a four-body statistical potential, mutant proteins are represented as feature vectors whose components quantify relative environmental perturbations at amino acid residue positions in the respective target structures upon mutation. Two approaches are implemented in developing sequence-based models, based on use of either relative frequencies or counts of n-grams, to generate vectors for representing mutant proteins. To the best of our knowledge, this is the first reported study on structure- and sequence-based predictive models of HIV-1 PR and RT drug resistance developed by implementing a four-body statistical potential and n-grams, respectively, to generate mutant attribute vectors. Performance of the learning methods is evaluated on the basis of tenfold cross-validation, using previously assayed and publicly available in vitro data relating mutational patterns in the targets to quantified inhibitor susceptibility changes.
Overall performance results are competitive with those of a previously published study utilizing a sequence-based strategy, while our structure- and sequence-based models provide orthogonal and complementary prediction methodologies, respectively. In a novel application, we describe a technique for identifying every possible pair of RT inhibitors as either potentially effective together as part of a cocktail, or a combination that is to be avoided.
BMC Genomics 10/2013; 4(Suppl 4):S3. DOI:10.1186/1471-2164-14-S4-S3 · 3.99 Impact Factor
Available from: Jürgen Rockstroh
- "HIV protease mutation of Val82 to Ala, Phe, Thr, or Ser has previously been implicated in resistance to PIs. However, this is the fi rst description of a Leu substitution at the V82 position (Johnson et al 2005). "
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ABSTRACT: Highly active antiretroviral therapy (HAART) has dramatically improved the prognosis of patients with HIV. Low adherence and toxicity among HIV-positive patients starting HAART, however, can lead to discontinuation of therapy and limit long-term treatment success. Moreover, increasing prevalence of primary resistance (>10%) as well as the accumulation of mutations resulting from continued selection pressure exerted by ongoing antiretroviral treatment in patients failing virologically, mean that new compounds are needed that retain antiretroviral activity against resistant strains. Tipranavir (Aptivus((R))) is a novel protease inhibitor (NPPI), which is characterized by a unique genetic resistance profile that allows it to remain active against HIV strains resistant to currently licensed protease inhibitors (PIs). Tipranavir was approved and licensed in the US and Europe in 2005 for treatment-experienced patients. This review summarizes the currently available data and studies on tipranavir and discusses the possible position of tipranavir in the currently available armamentarium of antiretroviral drugs.
Therapeutics and Clinical Risk Management 09/2007; 3(4):641-51. · 1.47 Impact Factor
Available from: Theodorus P. Sloots
- "However, Sturmer and colleagues reported some inconsistencies in the interpretation between nine different resistance interpretation systems (Sturmer et al., 2003). Therefore, before selecting an interpretation system, it is essential to find out how the system is managed and, in particular, how often the system is updated and whether references for individual mutations are available (Johnson et al., 2005). Unlike HIV, patients infected with HBV often only receive monotherapy. "
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ABSTRACT: The diagnosis of infectious diseases has been revolutionized by the development of molecular techniques, foremost with the applications of the polymerase chain reaction (PCR). The achievable high sensitivity and ease with which the method can be used to detect any known genetic sequence have led to its wide application in the life sciences. More recently, real-time PCR assays have provided additional major contributions, with the inclusion of an additional fluorescent probe detection system resulting in an increase in sensitivity over conventional PCR, the ability to confirm the amplification product and to quantitate the target concentration. Further, nucleotide sequence analysis of the amplification products has facilitated epidemiological studies of infectious disease outbreaks, and the monitoring of treatment outcomes for infections, in particular with viruses which mutate at high frequency. This review discusses the applications of qualitative and quantitative real-time PCR, nested PCR, multiplex PCR, nucleotide sequence analysis of amplified products and quality assurance with nucleic acid testing (NAT) in diagnostic laboratories.
Current issues in molecular biology 08/2007; 9(2):87-102. · 5.75 Impact Factor
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