Targeting protein kinases to manage or prevent Alzheimer’s disease

Due to the pressing need for new disease-modifying drugs for Alzheimer’s disease (AD), new treatment strategies and alternative drug targets are currently being heavily researched. One such strategy is to modulate protein kinases such as cyclin-dependent kinase 1 (CDK1), cyclin-dependent kinase 5 (CDK5), glycogen synthase kinase-3 (GSK-3α and GSK-3β), and the protein kinase RNA-like endoplasmic reticulum kinase (PERK). AD intervention by reduction of amyloid beta (Aβ) levels is also possible through development of protein kinase C-epsilon (PKC-ϵ) activators to recover α-secretase levels and decrease toxic Aβ levels, thereby restoring synaptogenesis and cognitive function. In this way, we aim to develop new AD drugs by targeting kinases that participate in AD pathophysiology. In our studies, comparative modeling was performed to construct 3D models for kinases whose crystal structures have not yet been identified. The information from structurally similar proteins was used to define the amino acid residues in the ATP binding site as well as other important sites and motifs. We searched for the comstructural motifs and domains of GSK-3β, CDK5 and PERK. Further, we identified the conserved water molecules in GSK-3β, CDK5 and PERK through calculation of the degree of water conservation. We investigated the protein-ligand interaction profiles of CDK1, CDK5, GSK-3α, GSK-3β and PERK based on molecular dynamics (MD) simulations, which provided a time-dependent demonstration of the interactions and contacts for each ligand. In addition, we explored the protein-protein interactions between CDK5 and p25. Small molecules which target this interaction may offer a prospective therapeutic benefit for AD. In order to identify new modulators for protein kinase targets in AD, we implemented three virtual screening protocols. The first protocol was a combined ligand- and protein structure-based approach to find new PERK inhibitors. In the second protocol, protein structure-based virtual screening was applied to find multiple-kinase inhibitors through parallel docking simulations into validated models of CDK1, CDK5 and GSK-3 kinases. In the third protocol, we searched for potential activators of PKC-ϵ based on the structure of its C1B domain

How do Wireless Chains Behave? The Impact of MAC Interactions

In a Multi-hop Wireless Networks (MHWN), packets are routed between source and destination using a chain of intermediate nodes; chains are a fundamental communication structure in MHWNs whose behavior must be understood to enable building effective protocols. The behavior of chains is determined by a number of complex and interdependent processes that arise as the sources of different chain hops compete to transmit their packets on the shared medium. In this paper, we show that MAC level interactions play the primary role in determining the behavior of chains. We evaluate the types of chains that occur based on the MAC interactions between different links using realistic propagation and packet forwarding models. We discover that the presence of destructive interactions, due to different forms of hidden terminals, does not impact the throughput of an isolated chain significantly. However, due to the increased number of retransmissions required, the amount of bandwidth consumed is significantly higher in chains exhibiting destructive interactions, substantially influencing the overall network performance. These results are validated by testbed experiments. We finally study how different types of chains interfere with each other and discover that well behaved chains in terms of self-interference are more resilient to interference from other chains

A Taxonomy of Free Network Sniffers for Teaching and Research

Today\u27s networking environment has become very complex. Networks have been growing in size rapidly and have come to support more complex applications. As result, troubleshooting and maintaining networks has become cumbersome and has created the need for new specialized tools such as Network Protocol Analyzers, better known as Network Sniffers .Network Sniffers have become critical tools in today\u27s networking management and troubleshooting processes. They enable network managers to evaluate and examine the data running through their network by troubleshooting network performance problems and identifying certain network faults. Network Sniffers can help identify network attacks and detect security threats; they can be used in intrusion detection systems.Besides their usage in the technical environment, network sniffers can be used for educational and research purposes. They can be used to help understand packets\u27 architecture and traffic patterns generated by common network applications. Network Sniffers can also be used to evaluate protocol performance and assist in protocol development. Despite their usefulness, network sniffers can be harmful when used by hackers. With network sniffers, hackers can capture data and steal information from targeted networks.This study consists of two major efforts. The first major effort entails researching and determining a set of criteria to use in evaluating and comparing network sniffers. The second major effort involves using the criteria to evaluate and compare three free network sniffers, thus building a taxonomy. The three free network sniffers used in this study were Ethereal, EtherSnoop and Packetyzer. Each of these three sniffers was evaluated and tested. Then their features and capabilities were compared

A novel optimal small cells deployment for next-generation cellular networks

Small-cell-deployments have pulled cellular operators to boost coverage and capacity in high-demand areas (for example, downtown hot spots). The location of these small cells (SCs) should be determined in order to achieve successful deployments. In this paper, we propose a new approach that optimizes small cells deployment in cellular networks to achieve three objectives: reduce the total cost of network installation, balancing the allocation of resources, i.e. placement of each SC and their transmitted power, and providing optimal coverage area with a lower amount of interference between adjacent stations. An accurate formula was obtained to determine the optimum number of SC deployment (NSC). Finally, we derive a mathematical expression to calculate the critical-handoff-point (CHP) for neighboring wireless stations

Apoptotic Potential of Artemsia sieberia Besser (Asteraceae) Fraction against Human Cancer Cell Lines

Purpose: To investigate the anti-proliferative and apoptotic activity of crude and dichloromethane fraction of A. sieberi against seven cancer cell lines (Colo20, HCT116, DLD, MCF7, Jurkat, HepG2 and L929).Methods: A. sieberi was extracted with methanol and further purification was carried out using liquidliquid extraction with hexane, dichloromethane and ethyl acetate. Each extract was assayed for cytotoxic potential against cancer cell lines using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium Bromide (MTT) assay. The morphology of the HepG2 cell nucleus was investigated by Hoechst 33342, DNA-binding dye. A Tali™ image-based cytometer was used to assess cell viability, death and apoptosis using annexin-v /pi (propidium iodide). A chromatographic fingerprint was constructed using high performance liquid chromatography (HPLC).Results: The most effective anticancer activity of the unrefined methanol extract was against HepG2 cell lines (LC50 = 161.5 μg/mL). The hexane and ethyl acetate fractions showed no antiproliferative activity. The dichloromethane fraction displayed higher cytotoxic activity (LC50 = 61.75 μg/mL) and also repressed the migration of the cells. About 50 % of HepG2 cells were apoptotic when treated for 24 h with the dichloromethane fraction at the concentration of 120 μg/mLConclusion: A. sieberi possesses apoptotic activity and inhibited the migration of the HepG2 cell lines.Keywords: Artemsia Sieberia, Apoptosiss, Cytotoxicity, Hoescht staining, HepG2 cell line

Computationally assisted lead optimization of novel potent and selective mao-b inhibitors

A series of dietary flavonoid acacetin 7-O-methyl ether derivatives were computationally designed aiming to improve the selectivity and potency profiles against monoamine oxidase (MAO) B. The designed compounds were evaluated for their potential to inhibit human MAO-A and-B. Compounds 1c, 2c, 3c, and 4c were the most potent with a Ki of 37 to 68 nM against MAO-B. Compounds 1c–4c displayed more than a thousand-fold selectivity index towards MAO-B compared with MAO-A. Moreover, compounds 1c and 2c showed reversible inhibition of MAO-B. These results provide a basis for further studies on the potential application of these modified flavonoids for the treatment of Parkinson’s Disease and other neurological disorders