γ-Secretase produces β-amyloid (Aβ) within its presenilin (PS1) subunit, mutations in which cause Alzheimer's disease, and current therapies thus seek to modulate its activity. While the general structure is known from recent electron microscopy studies, direct loop and membrane interactions and explicit dynamics relevant to substrate processing remain unknown. We report a modeled structure utilizing the optimal multitemplate information available, including loops and missing side chains, account of maturation cleavage, and explicit all-atom molecular dynamics in the membrane. We observe three distinct conformations of γ-secretase (open, semiopen, and closed) that remarkably differ by tilting of helices 2 and 3 of PS1, directly controlling active site availability. The large hydrophilic loop of PS1 where maturation occurs reveals a new helix segment that parallels the likely helix character of other substrates. The semiopen conformation consistently shows the best fit of Aβ peptides, that is, longer residence before release and by inference more trimming. In contrast, the closed, hydrophobic conformation is largely inactive and the open conformation is active but provides fewer optimal interactions and induces shorter residence time and by inference releases Aβ peptides of longer lengths. Our simulations thus provide a molecular basis for substrate processing and changes in the Aβ/Aβ ratio. Accordingly, selective binding to protect the semiopen "innocent" conformation provides a molecular recipe for effective γ-secretase modulators; we provide the full atomic structures for these states that may play a key role in developing selective γ-secretase modulators for treatment of Alzheimer's disease.

We studied the dynamics of Aβ40 , involved in Alzheimer's disease, by using 21 methods combined from Amber03, Amber99sb-ILDN, Charmm27, Charmm22*, OPLS-2001, OPLS-2006, OPLS-2008, Gromos96-43a1, Gromos96-53a6, Gromos96-54a7, and the water models SPC, TIP3P, TIP4P. Major differences in the structural ensembles were systematized: Amber03, Charmm27, and Gromos96-54a7 stabilize the helices; Gromos96-43a1 and Gromos53a6 favor the β-strands (with Charmm22* and Amber99sb-ILDN in between), and OPLS produces unstructured ensembles. The accuracy of the NMR chemical shifts was in the order: Charmm22*>Amber99sb-ILDN>OPLS-2008≈Gromos96-43a1>Gromos96-54a7≈OPLS-2001>OPLS-2006>Gromos96-53a6>Charmm27>Amber03. The computed (3) JHNHα -coupling constants were sensitive to experiment type and Karplus parameterization. Overall, the ensembles of Charmm22* and Amber99sb-ILDN provided the best agreement with experimental NMR and circular dichroism data, providing a model for the real Aβ monomer ensemble. Also, the polar water model TIP3P significantly favored helix and compact conformations.

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Nearly 200 mutations in the gene coding for presenilin 1 (PSEN1) cause early-onset Alzheimer's disease, yet the molecular mechanism remains obscure. As a meta-analysis, we compiled available clinical and biochemical data for PSEN1 variants and correlated these to chemical properties of the mutants. We found statistically significant relationships between relative Ab 42 levels and clinical age of onset. We then computed chemical properties of the mutants from a variety of computational chemistry tools. Relative Ab 42 levels correlated significantly (95% confidence or more from p-values of linear regression) with loss of hydrophobicity for four different regression analyses (squared correlation coefficient of linear regression R 2 of 0.41À0.53) and with increased polarity (R 2 = 0.47, 0.59) and loss of protein stability (R 2 = 0.39, 0.63) for two independent data sets. Age of onset of patients carrying PSEN1 variants correlated with increased polarity (R 2 = 0.49, 0.40) and loss of stability (R 2 = 0.75, 0.44) of the protein for both data sets. These relations suggest that mutants impair the membrane-associated structural integrity of presenilin by reducing hydrophobic membrane association and overall protein stability. This explains why the many mutations that spread out across the protein and far from the catalytic aspartates can cause disease. The identified molecular determinants of clinical age of symptom onset may be relevant to future presenilinmodulating therapies specifically directed towards increasing the structural integrity and packing of the protein.

The cell wall of Mycobacterium tuberculosis is configured of bioactive lipid classes that are essential for virulence and potentially involved in the formation of foamy macrophages (FMs) and granulomas. Our recent work established crosstalk between M. tuberculosis cell wall lipids and the host lipid-sensing nuclear receptor TR4. In this study, we have characterized, identified, and adopted a heterologous ligand keto-mycolic acid from among M. tuberculosis lipid repertoire for the host orphan NR TR4. Crosstalk between cell wall lipids and TR4 was analyzed by transactivation and promoter reporter assays. Mycolic acid (MA) was found to transactivate TR4 significantly compared with other cell wall lipids. Among the MA, the oxygenated form, keto-MA, was responsible for transactivation, and the identity was validated by TR4 binding assays followed by TLC and nuclear magnetic resonance. Isothermal titration calorimetry revealed that keto-MA binding to TR4 is energetically favorable. This keto-MA–TR4 axis seems to be essential to this oxygenated MA induction of FMs and granuloma formation as evaluated by in vitro and in vivo model of granuloma formation. TR4 binding with keto-MA features a unique association of host nuclear receptor with a bacterial lipid and adds to the presently known ligand repertoire beyond dietary lipids. Pharmacologic modulation of this heterologous axis may hold promise as an adjunct therapy to frontline tuberculosis drugs.