Synthesis of Two-Membrane Permeation Processes Using Residue Curve Maps and Node Classification

2013 ◽  
Vol 52 (41) ◽  
pp. 14637-14646
Author(s):  
Neil T. Stacey ◽  
Mark Peters ◽  
Diane Hildebrandt ◽  
David Glasser
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Koshi Nishida ◽  
Toshifumi Tojo ◽  
Takeshi Kondo ◽  
Makoto Yuasa

AbstractPorphyrin derivatives accumulate selectively in cancer cells and are can be used as carriers of drugs. Until now, the substituents that bind to porphyrins (mainly at the meso-position) have been actively investigated, but the effect of the functional porphyrin positions (β-, meso-position) on tumor accumulation has not been investigated. Therefore, we investigated the correlation between the functional position of substituents and the accumulation of porphyrins in cancer cells using cancer cells. We found that the meso-derivative showed higher accumulation in cancer cells than the β-derivative, and porphyrins with less bulky substituent actively accumulate in cancer cells. When evaluating the intracellular distribution of porphyrin, we found that porphyrin was internalized by endocytosis and direct membrane permeation. As factors involved in these two permeation mechanisms, we evaluated the affinity between porphyrin-protein (endocytosis) and the permeability to the phospholipid bilayer membrane (direct membrane permeation). We found that the binding position of porphyrin affects the factors involved in the transmembrane permeation mechanisms and impacts the accumulation in cancer cells.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weiwei Gu ◽  
Fei Gao ◽  
Xiaodan Lou ◽  
Jiang Zhang

AbstractIn this paper, we propose graph attention based network representation (GANR) which utilizes the graph attention architecture and takes graph structure as the supervised learning information. Compared with node classification based representations, GANR can be used to learn representation for any given graph. GANR is not only capable of learning high quality node representations that achieve a competitive performance on link prediction, network visualization and node classification but it can also extract meaningful attention weights that can be applied in node centrality measuring task. GANR can identify the leading venture capital investors, discover highly cited papers and find the most influential nodes in Susceptible Infected Recovered Model. We conclude that link structures in graphs are not limited on predicting linkage itself, it is capable of revealing latent node information in an unsupervised way once a appropriate learning algorithm, like GANR, is provided.


Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1461
Author(s):  
Nuno Mariz-Ponte ◽  
Laura Regalado ◽  
Emil Gimranov ◽  
Natália Tassi ◽  
Luísa Moura ◽  
...  

Pseudomonas syringae pv. actinidiae (Psa) is the pathogenic agent responsible for the bacterial canker of kiwifruit (BCK) leading to major losses in kiwifruit productions. No effective treatments and measures have yet been found to control this disease. Despite antimicrobial peptides (AMPs) having been successfully used for the control of several pathogenic bacteria, few studies have focused on the use of AMPs against Psa. In this study, the potential of six AMPs (BP100, RW-BP100, CA-M, 3.1, D4E1, and Dhvar-5) to control Psa was investigated. The minimal inhibitory and bactericidal concentrations (MIC and MBC) were determined and membrane damaging capacity was evaluated by flow cytometry analysis. Among the tested AMPs, the higher inhibitory and bactericidal capacity was observed for BP100 and CA-M with MIC of 3.4 and 3.4–6.2 µM, respectively and MBC 3.4–10 µM for both. Flow cytometry assays suggested a faster membrane permeation for peptide 3.1, in comparison with the other AMPs studied. Peptide mixtures were also tested, disclosing the high efficiency of BP100:3.1 at low concentration to reduce Psa viability. These results highlight the potential interest of AMP mixtures against Psa, and 3.1 as an antimicrobial molecule that can improve other treatments in synergic action.


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