The transmembrane aspartates in presenilin 1 and 2 are obligatory for gamma-secretase activity and amyloid beta-protein generation

The discovery that a deficiency of presenilin 1 (PS1) decreases the production of amyloid beta-protein (Abeta) identified the presenilins as important mediators of the gamma-secretase cleavage of beta-amyloid precursor protein (APP). Recently, we found that two conserved transmembrane (TM) aspartates in PS1 are critical for Abeta production, providing evidence that PS1 either functions as a required diaspartyl cofactor for gamma-secretase or is itself gamma-secretase. Presenilin 2 (PS2) shares substantial sequence and possibly functional homology with PS1. Here, we show that the two TM aspartates in PS2 are also critical for gamma-secretase activity, providing further evidence that PS2 is functionally homologous to PS1. Cells stably co-expressing TM Asp --> Ala mutations in both PS1 and PS2 show further accumulation of the APP-derived gamma-secretase substrates, C83 and C99. The production of Abeta is reduced to undetectable levels in the conditioned media of these cells. Furthermore, endoproteolysis of the exogenous Asp mutant PS2 is absent, and endogenous PS1 C-terminal fragments are diminished to undetectable levels. Therefore, the co-expression of PS1 and PS2 TM Asp --> Ala mutants suppresses the formation of any detectable PS1 or PS2 heterodimeric fragments and essentially abolishes the production of Abeta. These results explain the residual Abeta production seen in PS1-deficient cells and demonstrate the absolute requirement of functional presenilins for Abeta generation. We conclude that presenilins, and their TM aspartates in particular, are attractive targets for lowering Abeta therapeutically to prevent Alzheimer's disease.     

Integration,visualization and analysis of human interactome

Data integration and visualization are crucial to obtain meaningful hypotheses from the diversity of ‘omics’ fields and the large volume of heterogeneous and distributed data sets. In this review we focus on network analysis as a key technique to integrate, visualize and extrapolate relevant information from diverse data. We first describe challenges in integrating different types of data and then focus on systematically exploring network properties to gain insight into network function. We also describe the relationship between network structures and function of elements that form it. Next, we highlight the role of the interactome in connecting data derived from different experiments, and we stress the importance of network analysis to recognize interaction context-specific features. Finally, we present an example integration to demonstrate the value of the network approach in cancer research, and highlight the importance of dynamic data in the specific context of signaling pathways.     

Angiogenic activity of mitochondria; beyond the sole bioenergetic organelle

Angiogenesis is a complex process that involves the expansion of the pre-existing vascular plexus to enhance oxygen and nutrient delivery and is stimulated by various factors, including hypoxia. Since the process of angiogenesis requires a lot of energy, mitochondria play an important role in regulating and promoting this phenomenon. Besides their roles as an oxidative metabolism base, mitochondria are potential bioenergetics organelles to maintain cellular homeostasis via sensing alteration in oxygen levels. Under hypoxic conditions, mitochondria can regulate angiogenesis through different factors. It has been indicated that unidirectional and bidirectional exchange of mitochondria or their related byproducts between the cells is orchestrated via different intercellular mechanisms such as tunneling nanotubes, extracellular vesicles, and gap junctions to maintain the cell homeostasis. Even though, the transfer of mitochondria is one possible mechanism by which cells can promote and regulate the process of angiogenesis under reperfusion/ischemia injury. Despite the existence of a close relationship between mitochondrial donation and angiogenic response in different cell types, the precise molecular mechanisms associated with this phenomenon remain unclear. Here, we aimed to highlight the possible role of mitochondria concerning angiogenesis, especially the role of mitochondrial transport and the possible relation of this transfer with autophagy, the housekeeping phenomenon of cells, and angiogenesis.     

Transition-state analogue inhibitors of gamma-secretase bind directly to presenilin-1

The beta-amyloid precursor protein (beta-APP), which is involved in the pathogenesis of Alzheimer's disease, and the Notch receptor, which is responsible for critical signalling events during development, both undergo unusual proteolysis within their transmembrane domains by unknown gamma-secretases. Here we show that an affinity reagent designed to interact with the active site of gamma-secretase binds directly and specifically to heterodimeric forms of presenilins, polytopic proteins that are mutated in hereditary Alzheimer's and are known mediators of gamma-secretase cleavage of both beta-APP and Notch. These results provide evidence that heterodimeric presenilins contain the active site of gamma-secretase, and validate presenilins as principal targets for the design of drugs to treat and prevent Alzheimer's disease.     

Modeling and structural analysis of human Guanine nucleotide-binding protein-like 3,nucleostemin

Human GNL3 (nucleostemin) is a recently discovered nucleolar protein with pivotal functions in maintaining genomic integrity and determining cell fates of various normal and cancerous stem cells. Recent reports suggest that targeting this GTP-binding protein may have therapeutic value in cancer. Although, sequence analyzing revealed that nucleostemin (NS) comprises 5 permuted GTP-binding motifs, a crystal structure for this protein is missing at Protein Data Bank (PDB). Obviously, any attempt for predicting of NS structure can further our knowledge on its functional sites and subsequently designing molecular inhibitors. Herein, we used bioinformatics tools and could model 262 amino acids of NS (132-393 aa). Initial models were built by MODELLER, refined with Scwrl4 program, and validated with ProsA and Jcsc databases as well as PSVS software. Then, the best quality model was chosen for motif and domain analyzing by Pfam, PROSITE and PRINTS. The final model was visualized by vmd program. This predicted model may pave the way for next studies regarding ligand binding states and interaction sites as well as screening of databases for potential inhibitors.