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Inhibitors of the excision reaction catalysed by HIV-1 RT (reverse transcriptase) represent a promising approach in the fight against HIV, because these molecules would interfere with the main mechanism of resistance of this enzyme towards chain-terminating nucleotides. Only a limited number of compounds have been demonstrated to inhibit this reaction to date, including NNRTIs (non-nucleoside RT inhibitors) and certain pyrophosphate analogues. We have found previously that 2GP (2-O-galloylpunicalin), an antiviral compound extracted from the leaves of Terminalia triflora, was able to inhibit both the RT and the RNase H activities of HIV-1 RT without affecting cell proliferation or viability. In the present study, we show that 2GP also inhibited the ATP- and PPi-dependent phosphorolysis catalysed by wild-type and AZT (3′-azido-3′-deoxythymidine)-resistant enzymes at sub-micromolar concentrations. Kinetic and direct-binding analysis showed that 2GP was a non-competitive inhibitor against the nucleotide substrate, whereas it competed with the binding of RT to the template–primer (Kd=85 nM). As expected from its mechanism of action, 2GP was active against mutations conferring resistance to NNRTIs and AZT. The combination of AZT with 2GP was highly synergistic when tested in the presence of pyrophosphate, indicating that the inhibition of RT-catalysed phosphorolysis was responsible for the synergy found. Although other RT inhibitors that compete with the template–primer have been described, this is the first demonstration that these compounds can be used to block the excision of chain terminating nucleotides, providing a rationale for their combination with nucleoside analogues. [ABSTRACT FROM AUTHOR]

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer’s disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD. [ABSTRACT FROM AUTHOR]