scholarly journals Ion channel structure. Final technical report, April 1, 1993--March 31, 1997

1998 ◽  
Author(s):  
Keyword(s):  
Ion Channel ◽  
Channel Structure ◽  
Technical Report

scholarly journals Computational Ion Channel Research: from the Application of Artificial Intelligence to Molecular Dynamics Simulations.

2020 ◽  
Vol 55 (S3) ◽  
pp. 14-45
Keyword(s):  
Artificial Intelligence ◽  
Molecular Dynamics ◽  
Ion Channels ◽  
Ion Channel ◽  
Computational Methods ◽  
Homology Modelling ◽  
Channel Structure ◽  
Learning Approaches ◽  
Qsar Analysis ◽  
Wide Range

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.

Synthetic Peptide Fragments as Probes for Structure Determination of Potassium Ion-Channel Proteins

1998 ◽  
Vol 18 (6) ◽  
pp. 299-312 ◽  
Author(s):  
Parvez I. Haris
Keyword(s):  
Potassium Channels ◽  
Ion Channel ◽  
Potassium Channel ◽  
Synthetic Peptide ◽  
Potassium Ion ◽  
Channel Structure ◽  
Phospholipid Membranes ◽  
Peptide Fragments ◽  
2D Nmr Spectroscopy ◽  
Channel Proteins

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.

Development of a Novel Thiol Reagent for Probing Ion Channel Structure:  Studies in a Model System†

Biochemistry ◽  
1997 ◽  
Vol 36 (6) ◽  
pp. 1343-1348 ◽  
Author(s):  
Louise Y. Foong ◽  
Shaochun You ◽  
Dominic C. J. Jaikaran ◽  
Zhihua Zhang ◽  
Valentin Zunic ◽  
...  
Keyword(s):  
Ion Channel ◽  
Model System ◽  
Channel Structure ◽  
Thiol Reagent

scholarly journals Modeling the ion channel structure of cecropin

1992 ◽  
Vol 63 (6) ◽  
pp. 1623-1631 ◽  
Author(s):  
S.R. Durell ◽  
G. Raghunathan ◽  
H.R. Guy
Keyword(s):  
Ion Channel ◽  
Channel Structure

scholarly journals Theoretical models of the ion channel structure of amyloid beta-protein

1994 ◽  
Vol 67 (6) ◽  
pp. 2137-2145 ◽  
Author(s):  
S.R. Durell ◽  
H.R. Guy ◽  
N. Arispe ◽  
E. Rojas ◽  
H.B. Pollard
Keyword(s):  
Ion Channel ◽  
Amyloid Beta ◽  
Theoretical Models ◽  
Channel Structure ◽  
Amyloid Beta Protein

scholarly journals Precision physiology and rescue of brain ion channel disorders

2017 ◽  
Vol 149 (5) ◽  
pp. 533-546 ◽  
Author(s):  
Jeffrey Noebels
Keyword(s):  
Ion Channel ◽  
Clinical Utility ◽  
Clinical Decision Making ◽  
Central Nervous System Disease ◽  
Clinical Decision ◽  
Channel Structure ◽  
Clinical Severity ◽  
Developmental Relationships ◽  
System Disease ◽  
Phenotypic Spectrum

Ion channel genes, originally implicated in inherited excitability disorders of muscle and heart, have captured a major role in the molecular diagnosis of central nervous system disease. Their arrival is heralded by neurologists confounded by a broad phenotypic spectrum of early-onset epilepsy, autism, and cognitive impairment with few effective treatments. As detection of rare structural variants in channel subunit proteins becomes routine, it is apparent that primary sequence alone cannot reliably predict clinical severity or pinpoint a therapeutic solution. Future gains in the clinical utility of variants as biomarkers integral to clinical decision making and drug discovery depend on our ability to unravel complex developmental relationships bridging single ion channel structure and human physiology.

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