Human immunodeficiency virus (HIV) RNase H activity is essential for the synthesis of viral DNA by HIV reverse transcriptase (HIV-RT). RNA cleavage by RNase H requires the presence of divalent metal ions, but the role of metal ions in the mechanism of RNA cleavage has not been resolved. We measured HIV RNase H activity associated with HIV-RT protein in the presence of different concentrations of either Mg2+, Mn2+, Co2+ or a combination of these divalent metal ions. Polymerase-independent HIV RNase H was similar to or more active with Mn2+ and Co2+ compared with Mg2+. Activation of RNase H by these metal ions followed sigmoidal dose-response curves suggesting cooperative metal ion binding. Titration of Mg2+-bound HIV RNase H with Mn2+ or Co2+ ions generated bell-shaped activity dose-response curves. Higher activity could be achieved through simultaneous binding of more than one divalent metal ion at intermediate Mn2+ and Co2+ concentrations, and complete replacement of Mg2+ occurred at higher Mn2+ or Co2+ concentrations. These results are consistent with a two-metal ion mechanism of RNA cleavage as previously suggested for a number of polymerase-associated nucleases. In contrast, the structurally highly homologous RNase HI from Escherichia coli is most strongly activated by Mg2+, is significantly inhibited by submillimolar concentrations of Mn2+ and most probably cleaves RNA via a one-metal ion mechanism. Based on this difference in active site structure, a series of small molecule N-hydroxyimides was identified with significant enzyme inhibitory potency and selectivity for HIV RNase H.

Data from both our own and literature studies of the biochemistry and inhibition of influenza virus endonuclease was combined with data on the mechanism of action and the likely active site mechanism to propose a pharmacophore. The pharmacophore was used to design a novel structural class of inhibitors, some of which were found to have activities similar to that of known influenza endonuclease inhibitors and were also antiviral in cell culture.

A large-scale optimisation of density functional theory (DFT) conditions for computational NMR structure elucidation has been conducted by systematically screening the DFT functionals and statistical models. The extended PyDP4 workflow was tested on a diverse and challenging set of 42 biologically active and stereochemically rich compounds, including highly flexible molecules. MMFF/mPW1PW91/M06-2X in combination with a 2 Gaussian, 1 region statistical model was capable of identifying the correct diastereomer among up to an upper limit of 32 potential diastereomers. Overall a 2-fold reduction in structural uncertainty and a 7-fold reduction in model overconfidence have been achieved. Tools for rapid set-up and analysis of computational and experimental results, as well as for the statistical model generation, have been developed and are provided. All of this should facilitate rapid and reliable computational NMR structure elucidation, which has become a valuable tool to natural product chemists and synthetic chemists alike.

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