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Ligand-gated ion channels are an ionotropic receptor subtype characterized by the binding of an extracellular ligand, followed by the transient passage of ions through a transmembrane pore. Ligand-gated ion channels are commonly subcategorized into three superfamilies: purinoreceptors, glutamate receptors, and Cys-loop receptors. This classification is based on the differing topographical morphology of the receptors, which in turn confers functional differences. Ligand-gated ion channels have a diverse spatial and temporal expression which implicate them in key cellular processes. Given that the transcellular electrochemical gradient is finely tuned in eukaryotic cells, any disruption in this homeostasis can contribute to aberrancies, including altering the activity of pro-tumorigenic molecular pathways, such as the MAPK/ERK, RAS, and mTOR pathways. Ligand-gated ion channels therefore serve as a potential targetable system for cancer therapeutics. In this review, we analyze the role that each of the three ligand-gated ion channel superfamilies has concerning tumor proliferation and as a target for the treatment of cancer symptomatology. [ABSTRACT FROM AUTHOR]

A major challenge of targeted molecular imaging and drug delivery in cancer is establishing a functional combination of ligand-directed cargo with a triggered release system. Here we develop a hydrogelbased nanotechnology platform that integrates tumor targeting, photon-to-heat conversion, and triggered drug delivery within a single nanostructure to enable multimodal imaging and controlled release of therapeutic cargo. In proof-of-concept experiments, we showa broad range of ligand peptide-based applications with phage particles, heat-sensitive liposomes, or mesoporous silica nanoparticles that self-assemble into a hydrogel for tumor-targeted drug delivery. Because nanoparticles pack densely within the nanocarrier, their surface plasmon resonance shifts to near-infrared, thereby enabling a laser-mediated photothermal mechanism of cargo release. We demonstrate both noninvasive imaging and targeted drug delivery in preclinical mouse models of breast and prostate cancer. Finally, we applied mathematical modeling to predict and confirm tumor targeting and drug delivery. These results are meaningful steps toward the design and initial translation of an enabling nanotechnology platform with potential for broad clinical application.s [ABSTRACT FROM AUTHOR]

Diffusion-based communication is one of the most dominating forms in the micrometer and nanoscale communications. Generally, information is coded in molecules that are released by a transmitter nanomachine, propagated via a diffusion-based channel, and then received by a receiving nanomachine (called receiver). The receiver considered in this paper is equipped with multiple ligand receptors. The molecular communication system in this paper is single hop and SISO. Namely, there is only a channel connecting a pair of transmitter and receiver. While most literature considers either the channel or the receptors, this paper proposes a channel model that takes into account both the diffusion-based channel and the ligand-based receiver. The channel capacity under such model is analyzed, which studies the impact of different parameters at both channel and the receiver on the performance of the molecular communication system. We establish a digital channel model based on the on-off keying and time slot scheme. A capacity expression is derived with consideration of the effects of the channel memory and ligand-receptor binding mechanisms. The numerical results show that the overall channel capacity is restricted by the physical parameters of diffusion channel and ligand receptors. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Substrate-binding proteins (SBP) are associated with a wide variety of protein complexes. The proteins are part of ATP-binding cassette transporters for substrate uptake, ion gradient driven transporters, DNA-binding proteins, as well as channels and receptors from both pro- and eukaryotes. A wealth of structural and functional data is available on SBPs, with over 120 unique entries in the Protein Data Bank (PDB). Over a decade ago these proteins were divided into three structural classes, but based on the currently available wealth of structural data, we propose a new classification into six clusters, based on features of their three-dimensional structure. [Copyright &y& Elsevier]