Recent advances in DAPYs and related analogues as HIV-1 NNRTIs.
ABSTRACT HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs) nowadays represent most promising anti-AIDS drugs that specifically inhibit HIV-1 reverse transcriptase (RT). They have a unique antiviral potency, high specificity and low cytotoxicity. However, to a great extent, the efficacy of HIV-1 NNRTIs is compounded by rapid emergence of drug resistant virus strains, which calls for continuous efforts to develop novel HIV-1 NNRTIs. Diarylpyrimidine (DAPY) derivatives, one family of NNRTIs with superior activity profiles against wild-type HIV-1 and mutant strains, have attracted considerable attention over the past few years. Among the potent lead DAPY compounds, etravirine was approved by FDA in January 2008, and its analogue rilpivirine (TMC278) has advanced to phase III clinical trials. The successful development of DAPYs results from a multidisciplinary approach involving traditional medicinal chemistry, structural biology, crystallography and computational chemistry. Recently, a number of novel characteristics of DAPYs including conformational flexibility, positional adaptability, key hydrogen bonds and specifically targeting conserved residues of RT, have been identified, providing valuable avenues for further optimization and development of new DAPY analogues as promising anti-HIV drug candidates. In this review, we first present a brief historical account of the medicinal chemistry of the DAPY NNRTIs, then focus on the extensive structural modifications, SAR studies, and binding mode analysis based on crystallographic and molecular modeling. Other structural related NNRTI scaffolds will also be reviewed.
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ABSTRACT: BACKGROUND: The recently approved anti-AIDS drug rilpivirine (TMC278, Edurant) is a nonnucleoside inhibitor (NNRTI) that binds to reverse transcriptase (RT) and allosterically blocks the chemical step of DNA synthesis. In contrast to earlier NNRTIs, rilpivirine retains potency against well-characterized, clinically relevant RT mutants. Many structural analogues of rilpivirine are described in the patent literature, but detailed analyses of their antiviral activities have not been published. This work addresses the ability of several of these analogues to inhibit the replication of wild-type (WT) and drug-resistant HIV-1. RESULTS: We used a combination of structure activity relationships and X-ray crystallography to examine NNRTIs that are structurally related to rilpivirine to determine their ability to inhibit WT RT and several clinically relevant RT mutants. Several analogues showed broad activity with only modest losses of potency when challenged with drug-resistant viruses. Structural analyses (crystallography or modeling) of several analogues whose potencies were reduced by RT mutations provide insight into why these compounds were less effective. CONCLUSIONS: Subtle variations between compounds can lead to profound differences in their activities and resistance profiles. Compounds with larger substitutions replacing the pyrimidine and benzonitrile groups of rilpivirine, which reorient pocket residues, tend to lose more activity against the mutants we tested. These results provide a deeper understanding of how rilpivirine and related compounds interact with the NNRTI binding pocket and should facilitate development of novel inhibitors.Retrovirology 12/2012; 9(1):99. · 5.66 Impact Factor
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ABSTRACT: The classical method of quantitative structure-activity relationships (QSAR) is enriched using non-linear models, as Thom's polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the "optimal molecular structural domains" and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted.International Journal of Molecular Sciences 01/2011; 12(12):9533-69. · 2.46 Impact Factor