scholarly journals Modeling of the Binding of Peptide Blockers to Voltage-Gated Potassium Channels: Approaches and Evidence

Acta Naturae ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 35-46 ◽  
Author(s):  
V. N. Novoseletsky ◽  
A. D. Volyntseva ◽  
K. V. Shaitan ◽  
M. P. Kirpichnikov ◽  
A. V. Feofanov
Keyword(s):  
Potassium Channels ◽  
Rational Design ◽  
Computational Simulation ◽  
Bound State ◽  
Amino Acid Residues ◽  
Molecular Tools ◽  
Computational Approaches ◽  
Functional Roles ◽  
Voltage Gated ◽  
Kv Channels

Modeling of the structure of voltage-gated potassium (KV) channels bound to peptide blockers aims to identify the key amino acid residues dictating affinity and provide insights into the toxin-channel interface. Computational approaches open up possibilities for in silico rational design of selective blockers, new molecular tools to study the cellular distribution and functional roles of potassium channels. It is anticipated that optimized blockers will advance the development of drugs that reduce over activation of potassium channels and attenuate the associated malfunction. Starting with an overview of the recent advances in computational simulation strategies to predict the bound state orientations of peptide pore blockers relative to KV-channels, we go on to review algorithms for the analysis of intermolecular interactions, and then take a look at the results of their application.

Gene transcription of brain voltage-gated potassium channels is reversibly regulated by oxygen supply

2003 ◽  
Vol 285 (6) ◽  
pp. R1317-R1321 ◽  
Author(s):  
Howard M. Prentice ◽  
Sarah L. Milton ◽  
Daniela Scheurle ◽  
Peter L. Lutz
Keyword(s):  
Potassium Channels ◽  
Oxygen Supply ◽  
Brain Activity ◽  
Acute Hypoxia ◽  
Mrna Levels ◽  
Voltage Gated ◽  
Kv Channel ◽  
Kv Channels ◽  
Voltage Dependent ◽  
Channel Expression

Voltage-dependent potassium channels (Kv channels) are important determinants of brain electrical activity. Hypoxia may be an important modifier, because several voltage-gated K+ channels are reversibly blocked by acute hypoxia and are thought to act as oxygen sensors. Here we show, using the anoxia-tolerant turtle brain ( Trachemys scripta) as a model, that brain Kv1 channel transcription is reversibly regulated by oxygen supply. We found that in turtle brains exposed to 4-h anoxia Kv1 transcripts were reduced to 18.5% of normoxic levels. Kv1 channel mRNA levels were restored to normal within 4 h of subsequent reoxygenation. Our results provide clear evidence that brain Kv channel expression is sensitive to oxygen supply and indicate an important mechanism that matches brain activity to oxygen supply.

Atypical sialylated N-glycan structures are attached to neuronal voltage-gated potassium channels

2009 ◽  
Vol 29 (5) ◽  
pp. 301-313 ◽  
Author(s):  
Tara A. Cartwright ◽  
Ruth A. Schwalbe
Keyword(s):  
Potassium Channels ◽  
Neuroblastoma Cells ◽  
Fine Tuning ◽  
Mammalian Brain ◽  
Migration Patterns ◽  
Voltage Gated ◽  
Adult Rat ◽  
Electrophoretic Migration ◽  
Kv Channels ◽  
Rat Brain Membranes

Mammalian brains contain relatively high amounts of common and uncommon sialylated N-glycan structures. Sialic acid linkages were identified for voltage-gated potassium channels, Kv3.1, 3.3, 3.4, 1.1, 1.2 and 1.4, by evaluating their electrophoretic migration patterns in adult rat brain membranes digested with various glycosidases. Additionally, their electrophoretic migration patterns were compared with those of NCAM (neural cell adhesion molecule), transferrin and the Kv3.1 protein heterologously expressed in B35 neuroblastoma cells. Metabolic labelling of the carbohydrates combined with glycosidase digestion reactions were utilized to show that the N-glycan of recombinant Kv3.1 protein was capped with an oligo/poly-sialyl unit. All three brain Kv3 glycoproteins, like NCAM, were terminated with α2,3-linked sialyl residues, as well as atypical α2,8-linked sialyl residues. Additionally, at least one of their antennae was terminated with an oligo/poly-sialyl unit, similar to recombinant Kv3.1 and NCAM. In contrast, brain Kv1 glycoproteins consisted of sialyl residues with α2,8-linkage, as well as sialyl residues linked to internal carbohydrate residues of the carbohydrate chains of the N-glycans. This type of linkage was also supported for Kv3 glycoproteins. To date, such a sialyl linkage has only been identified in gangliosides, not N-linked glycoproteins. We conclude that all six Kv channels (voltage-gated K+ channels) contribute to the α2,8-linked sialylated N-glycan pool in mammalian brain and furthermore that their N-glycan structures contain branched sialyl residues. Identification of these novel and unique sialylated N-glycan structures implicate a connection between potassium channel activity and atypical sialylated N-glycans in modulating and fine-tuning the excitable properties of neurons in the nervous system.

Interpretable SMILES-based QSAR model of inhibitory activity of sirtuins 1 and 2

2020 ◽  
Vol 23 ◽  
Author(s):  
Apilak Worachartcheewan ◽  
Alla P. Toropova ◽  
Andrey A. Toropov ◽  
Reny Pratiwi ◽  
Virapong Prachayasittikul ◽  
...  
Keyword(s):  
Histone Deacetylases ◽  
Rational Design ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Sirtuin 1 ◽  
Data Set ◽  
Functional Roles ◽  
Molecular Features ◽  
Oecd Principles ◽  
Qsar Models

Background: Sirtuin 1 (Sirt1) and sirtuin 2 (Sirt2) are NAD+ -dependent histone deacetylases which play important functional roles in removal of the acetyl group of acetyl-lysine substrates. Considering the dysregulation of Sirt1 and Sirt2 as etiological causes of diseases, Sirt1 and Sirt2 are lucrative target proteins for treatment, thus there has been great interest in the development of Sirt1 and Sirt2 inhibitors. Objective: This study compiled the bioactivity data of Sirt1 and Sirt2 for the construction of quantitative structure-activity relationship (QSAR) models in accordance with the OECD principles. Method: Simplified molecular input line entry system (SMILES)-based molecular descriptors were used to characterize the molecular features of inhibitors while the Monte Carlo method of the CORAL software was employed for multivariate analysis. The data set was subjected to 3 random splits in which each split separated the data into 4 subsets consisting of training, invisible training, calibration and external sets. Results: Statistical indices for the evaluation of QSAR models suggested good statistical quality for models of Sirt1 and Sirt2 inhibitors. Furthermore, mechanistic interpretation of molecular substructures that are responsible for modulating the bioactivity (i.e. promoters of increase or decrease of bioactivity) was extracted via the analysis of correlation weights. It exhibited molecular features involved Sirt1 and Sirt2 inhibitors. Conclusion: It is anticipated that QSAR models presented herein can be useful as guidelines in the rational design of potential Sirt1 and Sirt2 inhibitors for the treatment of Sirtuin-related diseases.

Molecular Mechanisms Underlying the Functions of Cellular Markers Associated with the Phenotype of Cancer Stem Cells

2019 ◽  
Vol 14 (5) ◽  
pp. 405-420 ◽  
Author(s):  
Eduardo Alvarado-Ortiz ◽  
Miguel Á. Sarabia-Sánchez ◽  
Alejandro García-Carrancá
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Molecular Mechanisms ◽  
Tumor Biology ◽  
Molecular Tools ◽  
Recent Past ◽  
Functional Roles ◽  
Cellular Population ◽  
Cellular Markers ◽  
A Minor

Cancer Stem Cells (CSC) generally constitute a minor cellular population within tumors that exhibits some capacities of normal Stem Cells (SC). The existence of CSC, able to self-renew and differentiate, influences central aspects of tumor biology, in part because they can continue tumor growth, give rise to metastasis, and acquire drug and radioresistance, which open new avenues for therapeutics. It is well known that SC constantly interacts with their niche, which includes mesenchymal cells, extracellular ligands, and the Extra Cellular Matrix (ECM). These interactions regularly lead to homeostasis and maintenance of SC characteristics. However, the exact participation of each of these components for CSC maintenance is not clear, as they appear to be context- or cell-specific. In the recent past, surface cellular markers have been fundamental molecular tools for identifying CSC and distinguishing them from other tumor cells. Importantly, some of these cellular markers have been shown to possess functional roles that affect central aspects of CSC. Likewise, some of these markers can participate in regulating the interaction of CSC with their niche, particularly the ECM. We focused this review on the molecular mechanisms of surface cellular markers commonly employed to identify CSC, highlighting the signaling pathways and mechanisms involved in CSC-ECM interactions, through each of the cellular markers commonly used in the study of CSC, such as CD44, CD133, CD49f, CD24, CXCR4, and LGR5. Their presence does not necessarily implicate them in CSC biology.

Computational Approaches to Predict the Non-canonical DNAs

2019 ◽  
Vol 14 (6) ◽  
pp. 470-479 ◽  
Author(s):  
Nazia Parveen ◽  
Amen Shamim ◽  
Seunghee Cho ◽  
Kyeong Kyu Kim
Keyword(s):  
Computational Methods ◽  
Genetic Instability ◽  
Computational Prediction ◽  
Structure And Function ◽  
Sequence Motifs ◽  
Computational Approaches ◽  
Functional Roles ◽  
And Function ◽  
Genetic Events ◽  
Insight Into

Background: Although most nucleotides in the genome form canonical double-stranded B-DNA, many repeated sequences transiently present as non-canonical conformations (non-B DNA) such as triplexes, quadruplexes, Z-DNA, cruciforms, and slipped/hairpins. Those noncanonical DNAs (ncDNAs) are not only associated with many genetic events such as replication, transcription, and recombination, but are also related to the genetic instability that results in the predisposition to disease. Due to the crucial roles of ncDNAs in cellular and genetic functions, various computational methods have been implemented to predict sequence motifs that generate ncDNA. Objective: Here, we review strategies for the identification of ncDNA motifs across the whole genome, which is necessary for further understanding and investigation of the structure and function of ncDNAs. Conclusion: There is a great demand for computational prediction of non-canonical DNAs that play key functional roles in gene expression and genome biology. In this study, we review the currently available computational methods for predicting the non-canonical DNAs in the genome. Current studies not only provide an insight into the computational methods for predicting the secondary structures of DNA but also increase our understanding of the roles of non-canonical DNA in the genome.

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