G-quadruplex (G4) is a noncanonical DNA secondary structure formed by Hoogsteen base pairing. It is recognized by various DNA helicases involved in DNA metabolism processes such as replication and transcription. Human Bloom syndrome protein (BLM), one of five human RecQ helicases, is a G4 helicase. While several studies revealed the mechanism of G4 binding and unfolding by the conserved RecQ C-terminal (RQC) domain of BLM, how RQC recognizes different G4 topologies is still unclear. Here, we investigated the interaction of Myc-22(14/23T) G4 from the c-Myc promoter and hTelo G4 from the telomeric sequence with RQC. Myc-22(14/23T) and hTelo form parallel and (3+1) hybrid topologies, respectively. Our circular dichroism (CD) spectroscopy data indicate that RQC can partially unfold the parallel G4, even with a short 3′ overhang, while it can only partially unfold the (3+1) hybrid G4 with a 3′ overhang of 6 nucleotides or longer. We found that the intrinsic thermal stability of G4 does not determine RQC-induced G4 unfolding by comparing T m of G4s. We also showed that both parallel and (3+1) hybrid G4s bind to the β-wing region of RQC. Thermodynamic analysis using isothermal titration calorimetry (ITC) showed that all interactions were endothermic and entropically driven. We suggest that RQC partially unfolds the parallel G4 more efficiently than the (3+1) hybrid G4 and binds to various G4 structures using its β-wing region. By this information, our research provides new insights into the influence of G4 structure on DNA metabolic processes involving BLM.
Current approaches to design monodisperse protein assemblies require rigid, tight, and symmetric interactions between oligomeric protein units.H erein, we introduce an ew multivalent-interaction-driven assembly strategy that allows flexible,s paced, and asymmetric assembly between protein oligomers.Wediscoveredthat two polygonal protein oligomers (ranging from triangle to hexagon) dominantly form adiscrete and stable two-layered protein prism nanostructure via multivalent interactions between fused binding pairs.W ed emonstrated that protein nano-prisms with long flexible peptide linkers (over 80 amino acids) between protein oligomer layers could be discretely formed. Oligomers with different structures could also be monodispersely assembled into two-layered but asymmetric protein nano-prisms.F urthermore,p roducing higher-order architectures with multiple oligomer layers,f or example,3-layeredn ano-prisms or nanotubes,w as also feasible.
Nature uses a wide range of well-defined biomolecular assemblies in diverse cellular processes, where proteins are major building blocks for these supramolecular assemblies. Inspired by their natural counterparts, artificial protein-based assemblies have attracted strong interest as new bio-nanostructures, and strategies to construct ordered protein assemblies have been rapidly expanding. In this review, we provide an overview of very recent studies in the field of artificial protein assemblies, with the particular aim of introducing major assembly methods and unique features of these assemblies. Computational de novo designs were used to build various assemblies with artificial protein building blocks, which are unrelated to natural proteins. Small chemical ligands and metal ions have also been extensively used for strong and bio-orthogonal protein linking. Here, in addition to protein assemblies with well-defined sizes, protein oligomeric and array structures with rather undefined sizes (but with definite repeat protein assembly units) also will be discussed in the context of well-defined protein nanostructures. Lastly, we will introduce multiple examples showing how protein assemblies can be effectively used in various fields such as therapeutics and vaccine development. We believe that structures and functions of artificial protein assemblies will be continuously evolved, particularly according to specific application goals.
Current approaches to design monodisperse protein assemblies require rigid, tight, and symmetric interactions between oligomeric protein units.H erein, we introduce an ew multivalent-interaction-driven assembly strategy that allows flexible,s paced, and asymmetric assembly between protein oligomers.Wediscoveredthat two polygonal protein oligomers (ranging from triangle to hexagon) dominantly form adiscrete and stable two-layered protein prism nanostructure via multivalent interactions between fused binding pairs.W ed emonstrated that protein nano-prisms with long flexible peptide linkers (over 80 amino acids) between protein oligomer layers could be discretely formed. Oligomers with different structures could also be monodispersely assembled into two-layered but asymmetric protein nano-prisms.F urthermore,p roducing higher-order architectures with multiple oligomer layers,f or example,3-layeredn ano-prisms or nanotubes,w as also feasible.
The anticancer activity of a methanolic extract from lemon leaves (MLL) was assessed in MCF-7-SC human breast cancer stem cells. MLL induced apoptosis in MCF-7-SC, as evidenced by increased apoptotic body formation, sub-G1 cell population, annexin V-positive cells, Bax/Bcl-2 ratio, as well as proteolytic activation of caspase-9 and caspase-3, and degradation of poly (ADP-ribose) polymerase (PARP) protein. Concomitantly, MLL induced the formation of acidic vesicular organelles, increased LC3-II accumulation, and reduced the activation of Akt, mTOR, and p70S6K, suggesting that MLL initiates an autophagic progression in MCF-7-SC via the Akt/mTOR pathway. Epithelialmesenchymal transition (EMT), a critical step in the acquisition of the metastatic state, is an attractive target for therapeutic interventions directed against tumor metastasis. At low concentrations, MLL induced anti-metastatic effects on MCF-7-SC by inhibiting the EMT process. Exposure to MLL also led to an increase in the epithelial marker E-cadherin, but decreased protein levels of the mesenchymal markers Snail and Slug. Collectively, this study provides evidence that lemon leaves possess cytotoxicity and antimetastatic properties. Therefore, MLL may prove to be beneficial as a medicinal plant for alternative novel anticancer drugs and nutraceutical products. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons. org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
No abstract
The main purpose of this research is to develop a better algorithm that would both enhance the quality of the final MRI image and decrease the amount of time taken to produce it. In this paper, different Gaussian filters were proposed and tested on the human brain to reduce the size of original full frequency domain, which is relatively huge in k-space. The size of original full frequency matrix is 557x365 and, the data are obtained from a patient using 12 coils in a lab. All the Gaussian filters used on the brain show their distinct features. The Gaussian functions, or exponential functions, reduced ringing artifact in every image they produced, compared to those produced by the Square functions. However, present study shows that not all the Gaussian functions show better images in resolution, compared to those produced by the Square functions.According to the proposed Gaussian function in this paper, y=1-exp[-(w^2)/h^2)], where w=k-L/2, k=[0,M], L=2*7*N/40, and N=500, the size of frequency matrix (M,N), the resolution of the resulting image shows differed based on choosing the variable h. As the variable h is increased from 0 to 200, the filter can capture more data in k-space data since the Gaussian filter becomes wider, and the best image is shown when p= 60. For the higher values of p, the resolutions are not much different from those produced when p=60. REFERENCES[1] Zhuo J, Gullapalli RP. AAPM/RSNA physics tutorial for residents: MR artifacts, safety, and quality control. Radiographics 2006; 26(1):275-97.[2] Stark DD, Bradley WG. Magnetic Resonance Imaging. 3rd edition. C V Mosby, 1999.[3] Mezrich R. A perspective on K-space. Radiology 1995; 195(2):297-315.[4] Twieg DB. The k-trajectory formulation of the NMR imaging process with applications in analysis and synthesis of imaging methods. Med Phys 1983; 10(5):610-21.
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