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The order of appearance in the reverse transcriptase gene of four mutations implicated in the development of resistance to zidovudine was investigated by selective polymerase chain reaction. Serial human immunodeficiency virus isolates were studied from 18 initially asymptomatic individuals who had been treated with zidovudine for 2 years. Most subjects had similar patterns. The first mutation occurred transiently at codon 70; its disappearance was paralleled by the appearance of a mutation at codon 215. Subsequently, in some individuals, the mutation at codon 70 reappeared. During the 2 years of treatment, no mutations developed at codon 219 and only one at codon 67, suggesting that most individuals developed only partly resistant virus. This was confirmed by plaque-reduction assay. Six subjects progressed to AIDS within the 2-year study period, confirming that the development of highly resistant isolates is not required for progression in treated individuals. No clear temporal relationship was found between the development of partial resistance and progression. [ABSTRACT FROM AUTHOR]

The reverse transcriptase (RT) of HIV is an important target for chemotherapy as demonstrated by the effective treatment of AIDS patients with zidovudine, a potent inhibitor of RT. Structural studies of HIV RT were therefore undertaken with a view to designing more effective inhibitors. To obtain sufficient quantities of enzyme for these studies the reverse transcriptase gene of HIV was cloned into a high level expression plasmid yielding reverse transcriptase at a level of 10% of the total Escherichia coli proteins. Monoclonal antibodies to RT were raised in mice and have been used to purify the enzyme by immunoaffinity chromatography. Crystallization of the enzyme has been achieved and studies are underway to determine its three-dimensional structure. In addition, carboxy-terminal truncated mutants were prepared by inserting stop codons into the gene at appropriate sites. The proteins expressed were analysed for RT and RNase H activity and used for mapping RT epitopes. This, together with previous data on site-directed mutagenesis of conserved regions of HIV RT has helped to map some of the structural and functional regions of the enzyme. [ABSTRACT FROM PUBLISHER]

The results of genotypic HIV drug-resistance testing are, typically, 60-65% predictive of response to combination antiretroviral therapy (ART) and have proven valuable for guiding treatment changes. However, genotyping is not available in many resource-limited settings (RLS). The purpose of this study was to develop computational models that can predict response to ART without a genotype and evaluate their potential as a treatment support tool in RLS. Random forest models were trained to predict the probability of response to ART (<400 copies HIV RNA/ml) using the following data from 14,891 cases of ART change following virological failure in well-resourced countries: viral load and CD4 count prior to treatment change, treatment history, drugs in the new regimen, time to follow-up and follow-up viral load. The models were assessed during cross-validation, with an independent set of 800 cases, with 231 cases from RLS in Southern Africa, 206 from India and 375 from Romania. The area under the ROC curve (AUC) was the main outcome measure of the accuracy of the model's predictions. The models were used to identify alternative regimens for those cases where the salvage regimen initiated in the clinic failed. Finally, annual therapy costs were used to determine the potential cost effectiveness of this strategy for the Indian cases. The models achieved an AUC of 0.74-0.81 during cross validation and 0.76-0.77 with the 800 test TCEs. They achieved an AUC of 0.59-0.65 with cases from Southern Africa, 0.64 for India and 0.73 for Romania. The models identified alternative, locally available drug regimens that were predicted to result in virological response for 97% of cases where the salvage regimen failed in Southern Africa, 98% of those in Romania and 100% in India. Cost-neutral or cost-saving regimens that were predicted to be effective were identified for 88% of the Indian salvage failures with a mean saving of $638 per year. We developed computational models that predict virological response to ART without a genotype with comparable accuracy to genotyping with rules-based interpretation. The models were able to identify alternative regimens that were predicted to be effective for the great majority of cases where the new regimen prescribed in the clinic failed. The models were also able to identify cost-saving alternatives for most cases of failure in India. These models are now freely available over the internet as part of the HIV Treatment Response Predictions System (HIV-TRePS), which has the potential to help optimise antiretroviral therapy in countries with limited resources where genotyping is not generally available. [ABSTRACT FROM AUTHOR]