γ-Secretase plays a central role in the generation of the Alzheimer disease-causing amyloid β-peptide (Aβ) from the β-amyloid precursor protein (APP) and is thus a major Alzheimer's disease drug target. As several other γ-secretase substrates including Notch1 and CD44 have crucial signaling functions, an understanding of the mechanism of substrate recognition and cleavage is key for the development of APP selective γ-secretase-targeting drugs. The γ-secretase active site domain in its catalytic subunit presenilin (PS) 1 has been implicated in substrate recognition/docking and cleavage. Highly critical in this process is its GxGD active site motif, whose invariant glycine residues cannot be replaced without causing severe functional losses in substrate selection and/or cleavage efficiency. Here, we have investigated the contribution of the less well characterized residue x of the motif (L383 in PS1) to this function. Extensive mutational analysis showed that processing of APP was overall well-tolerated over a wide range of hydrophobic and hydrophilic mutations. Interestingly, however, most L383 mutants gave rise to reduced levels of Aβ37-39 species, and several increased the pathogenic Aβ42/43 species. Several of the Aβ42/43 -increasing mutants severely impaired the cleavages of Notch1 and CD44 substrates, which were not affected by any other L383 mutation. Our data thus establish an important, but compared with the glycine residues of the motif, overall less critical functional role for L383. We suggest that L383 and the flanking glycine residues form a spatial arrangement in PS1 that is critical for docking and/or cleavage of different γ-secretase substrates.
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Acta Pharmacol Sin
January 2025
Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantially. This progress inspired the development of the first genome-wide small molecule targets scanning method.
View Article and Find Full Text PDFJ Neurointerv Surg
January 2025
Department of Neurology, UTHealth Houston McGovern Medical School, Houston, Texas, USA
Background: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction are required for these benefits remains incompletely characterized.
Methods: This analysis was conducted as a pre-planned post-hoc analysis of a randomized prospective clinical trial.
Arch Biochem Biophys
January 2025
Department of Biochemistry, University of Missouri, Columbia, Missouri 65211, United States; Department of Chemistry, University of Missouri, Columbia, Missouri 65211, United States. Electronic address:
The mitochondrial flavoenzymes proline dehydrogenase (PRODH) and hydroxyproline dehydrogenase (PRODH2) catalyze the first steps of proline and hydroxyproline catabolism, respectively. The enzymes are targets for chemical probe development because of their roles in cancer cell metabolism (PRODH) and primary hyperoxaluria (PRODH2). Mechanism-based inactivators of PRODH target the FAD by covalently modifying the N5 atom, with N-propargylglycine (NPPG) being the current best-in-class of this type of probe.
View Article and Find Full Text PDFIn the leucine (Leu) biosynthesis pathway, homeostasis is achieved through a feedback regulatory mechanism facilitated by the binding of the end-product Leu at the C-terminal regulatory domain of the first committed enzyme, isopropylmalate synthase (IPMS). In vitro studies have shown that removing the regulatory domain abolishes the feedback regulation on plant IPMS while retaining its catalytic activity. However, the physiological consequences and underlying molecular regulation on Leu flux upon removing the IPMS C-terminal domain remain to be explored in plants.
View Article and Find Full Text PDFAcc Chem Res
January 2025
The Department of Chemistry, State University of New York at Binghamton, Binghamton, New York 13902, United States.
ConspectusIn the search for efficient and selective electrocatalysts capable of converting greenhouse gases to value-added products, enzymes found in naturally existing bacteria provide the basis for most approaches toward electrocatalyst design. Ni,Fe-carbon monoxide dehydrogenase (Ni,Fe-CODH) is one such enzyme, with a nickel-iron-sulfur cluster named the C-cluster, where CO binds and is converted to CO at high rates near the thermodynamic potential. In this Account, we divide the enzyme's catalytic contributions into three categories based on location and function.
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