Derivatization and Isotope Labeling of Amphotericin B Aiming at Elucidation of the Ion-Channel Structure

ChemInform ◽  
2006 ◽  
Vol 37 (42) ◽  
Author(s):  
Nobuaki Matsumori ◽  
Tohru Oishi ◽  
Michio Murata
Author(s):  
Karin Abarca-Heidemann ◽  
Elke Duchardt-Ferner ◽  
Jens Woehnert ◽  
Brad S. Rothberg

Biochemistry ◽  
2014 ◽  
Vol 53 (19) ◽  
pp. 3088-3094 ◽  
Author(s):  
Yasuo Nakagawa ◽  
Yuichi Umegawa ◽  
Tetsuro Takano ◽  
Hiroshi Tsuchikawa ◽  
Nobuaki Matsumori ◽  
...  

2020 ◽  
Vol 55 (S3) ◽  
pp. 14-45

Although ion channels are crucial in many physiological processes and constitute an important class of drug targets, much is still unclear about their function and possible malfunctions that lead to diseases. In recent years, computational methods have evolved into important and invaluable approaches for studying ion channels and their functions. This is mainly due to their demanding mechanism of action where a static picture of an ion channel structure is often insufficient to fully understand the underlying mechanism. Therefore, the use of computational methods is as important as chemical-biological based experimental methods for a better understanding of ion channels. This review provides an overview on a variety of computational methods and software specific to the field of ion-channels. Artificial intelligence (or more precisely machine learning) approaches are applied for the sequence-based prediction of ion channel family, or topology of the transmembrane region. In case sufficient data on ion channel modulators is available, these methods can also be applied for quantitative structureactivity relationship (QSAR) analysis. Molecular dynamics (MD) simulations combined with computational molecular design methods such as docking can be used for analysing the function of ion channels including ion conductance, different conformational states, binding sites and ligand interactions, and the influence of mutations on their function. In the absence of a three-dimensional protein structure, homology modelling can be applied to create a model of your ion channel structure of interest. Besides highlighting a wide range of successful applications, we will also provide a basic introduction to the most important computational methods and discuss best practices to get a rough idea of possible applications and risks.


1998 ◽  
Vol 18 (6) ◽  
pp. 299-312 ◽  
Author(s):  
Parvez I. Haris

Potassium channels are a diverse class of transmembrane proteins that are responsible for diffusion of potassium ion across cell membranes. The lack of large quantities of these proteins from natural sources, is a major hindrance in their structural characterization using biophysical techniques. Synthetic peptide fragments corresponding to functionally important domains of these proteins provide an attractive approach towards characterizing the structural organization of these ion-channels. Conformational properties of peptides from three different potassium channels (Shaker, ROMK1 and minK) have been characterized in aqueous media, organic solvents and in phospholipid membranes. Techniques used for these studies include FTIR, CD and 2D-NMR spectroscopy. FTIR spectroscopy has been a particularly valuable tool for characterizing the folding of the ion-channel peptides in phospholipid membranes; the three different types of potassium channels all share a common transmembrane folding pattern that is composed of a predominantly α-helical structure. There is no evidence to suggest the presence of any significant β-sheet structure. These results are in excellent agreement with the crystal structure of a bacterial potassium channel (Doyle, D. A. et al. (1998) Science280:69–77), and suggest that all potassium channel proteins may share a common folding motif where the ion-channel structure is constructed entirely from α-helices.


2007 ◽  
Vol 48 (19) ◽  
pp. 3393-3396 ◽  
Author(s):  
Yuichi Umegawa ◽  
Nobuaki Matsumori ◽  
Tohru Oishi ◽  
Michio Murata
Keyword(s):  

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