Significance: The majority of the drugs which target membrane-embedded protease γ-secretase show an unusual biphasic activation–inhibition dose-response in cells, model animals, and humans. Semagacestat and avagacestat are two biphasic drugs that can facilitate cognitive decline in patients with Alzheimer’s disease. Initial mechanistic studies showed that the biphasic drugs, and pathogenic mutations, can produce the same type of changes in γ-secretase activity. Results: DAPT, semagacestat LY-411,575, and avagacestat are four drugs that show different binding constants, and a biphasic activation–inhibition dose-response for amyloid-β-40 products in SH-SY5 cells. Multiscale molecular dynamics studies have shown that all four drugs bind to the most mobile parts in the presenilin structure, at different ends of the 29 Å long active site tunnel. The biphasic dose-response assays are a result of the modulation of γ-secretase activity by the concurrent binding of multiple drug molecules at each end of the active site tunnel. The drugs activate γ-secretase by facilitating the opening of the active site tunnel, when the rate-limiting step is the tunnel opening, and the formation of the enzyme–substrate complex. The drugs inhibit γ-secretase as uncompetitive inhibitors by binding next to the substrate, to dynamic enzyme structures which regulate processive catalysis. The drugs can modulate the production of different amyloid-β catalytic intermediates by penetration into the active site tunnel, to different depths, with different flexibility and different binding affinity. Conclusions: Biphasic drugs and pathogenic mutations can affect the same dynamic protein structures that control processive catalysis. Successful drug-design strategies must incorporate transient changes in the γ-secretase structure in the development of specific modulators of its catalytic activity.
BackgroundWe use our earlier experimental studies of the catalytic mechanism of DNA methyltransferases to prepare in silico a family of novel mechanism-based inhibitors of human Dnmt1. Highly specific inhibitors of DNA methylation can be used for analysis of human epigenome and for the creation of iPS cells.ResultsWe describe a set of adenosyl-1-methyl-pyrimidin-2-one derivatives as novel mechanism-based inhibitors of mammalian DNA methyltransferase Dnmt1. The inhibitors have been designed to bind simultaneously in the active site and the cofactor site and thus act as transition-state analogues. Molecular dynamics studies showed that the lead compound can form between 6 to 9 binding interactions with Dnmt1. QM/MM analysis showed that the upon binding to Dnmt1 the inhibitor can form a covalent adduct with active site Cys1226 and thus act as a mechanism-based suicide-inhibitor. The inhibitor can target DNA-bond and DNA-free form of Dnmt1, however the suicide-inhibition step is more likely to happen when DNA is bound to Dnmt1. The validity of presented analysis is described in detail using 69 modifications in the lead compound structure. In total 18 of the presented 69 modifications can be used to prepare a family of highly specific inhibitors that can differentiate even between closely related enzymes such as Dnmt1 and Dnmt3a DNA methyltransferases.ConclusionsPresented results can be used for preparation of some highly specific and potent inhibitors of mammalian DNA methylation with specific pharmacological properties.
Flow at the molecular level induces shear-induced unfolding of single proteins and can drive their assembly, the mechanisms of which are not completely understood. To be able to analyze the role of flow on molecules, we present uniformflow molecular dynamics simulations at atomic level. The pull module of the GRoningen MAchine for Chemical Simulations package was extended to be able to force-group atoms within a defined layer of the simulation box. Application of this external enforcement to explicit water molecules, together with the coupling to a thermostat, led to a uniform terminal velocity of the solvent water molecules. We monitored the density of the whole system to establish the conditions under which the simulated flow is well-behaved. A maximal velocity of 1.3 m/s can be generated if a pull slice of 8 nm is used, and high velocities would require larger pull slices to still maintain a stable density. As expected, the target velocity increases linearly with the total external force applied. Finally, we suggest an appropriate setup to stretch a protein by uniform flow, in which protein extensions depend on the flow conditions. Our implementation provides an efficient computational tool to investigate the effect of the flow at the molecular level.
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