T-type Calcium Channels in Health and Disease

2020 ◽  
Vol 27 (19) ◽  
pp. 3098-3122 ◽  
Author(s):  
Dan Wang ◽  
Lotten Ragnarsson ◽  
Richard J. Lewis
Keyword(s):  
Calcium Channels ◽  
Low Voltage ◽  
Oscillatory Behavior ◽  
Neuronal Firing ◽  
Rational Drug Design ◽  
Structural Determinants ◽  
Rational Drug ◽  
Preferential Localization ◽  
Window Current ◽  
Health And Disease

Low Voltage-Activated (LVA) T-type calcium channels are characterized by transient current and Low Threshold Spikes (LTS) that trigger neuronal firing and oscillatory behavior. Combined with their preferential localization in dendrites and their specific “window current”, T-type calcium channels are considered to be key players in signal amplification and synaptic integration. Assisted by the emerging pharmacological tools, the structural determinants of channel gating and kinetics, as well as novel physiological and pathological functions of T-type calcium channels, are being uncovered. In this review, we provide an overview of structural determinants in T-type calcium channels, their involvement in disorders and diseases, the development of novel channel modulators, as well as Structure-Activity Relationship (SAR) studies that lead to rational drug design.

scholarly journals I–II Loop Structural Determinants in the Gating and Surface Expression of Low Voltage-Activated Calcium Channels

PLoS ONE ◽  
2008 ◽  
Vol 3 (8) ◽  
pp. e2976 ◽  
Author(s):  
Joel P. Baumgart ◽  
Iuliia Vitko ◽  
Isabelle Bidaud ◽  
Artem Kondratskyi ◽  
Philippe Lory ◽  
...  
Keyword(s):  
Calcium Channels ◽  
Low Voltage ◽  
Surface Expression ◽  
Structural Determinants

scholarly journals Regulation of the CaV3.2 calcium channels in health and disease Regulácia CaV3.2 vápnikových kanálov v zdraví a chorobe

2017 ◽  
Vol 64 (2) ◽  
pp. 15-21
Author(s):  
Ľ. Lacinová
Keyword(s):  
Calcium Channels ◽  
Low Voltage ◽  
Tissue Expression ◽  
Autism Spectrum ◽  
Promising Target ◽  
Tissue Expression Profile ◽  
Health And Disease ◽  
Spectrum Disorders ◽  
Specific Tissue ◽  
Lateral Sclerosis

AbstractFamily of T-type or low-voltage activated calcium channels consists of three members: CaV3.1, CaV3.2, and CaV3.3. CaV3.2 channel has almost identical biophysical properties as the CaV3.1 channel, but is distinguished by a specific tissue expression profile and a prominent role in several pathologies, including neuropathic pain, epilepsy, and dysregulation of cardiac rhythm. Further, it may be involved in phenotype of autism spectrum disorders, and amyotrophic lateral sclerosis. It represents a promising target for future pharmacotherapies.

Improving the Accuracy of Protein-Ligand Binding Affinity Prediction by Deep Learning Models: Benchmark and Model

2019 ◽  
Author(s):  
Mohammad Rezaei ◽  
Yanjun Li ◽  
Xiaolin Li ◽  
Chenglong Li
Keyword(s):  
Deep Learning ◽  
Drug Design ◽  
Binding Affinity ◽  
Benchmark Dataset ◽  
Rational Drug Design ◽  
Learning Models ◽  
Structure Based Drug Design ◽  
Binding Affinity Prediction ◽  
Affinity Prediction ◽  
Rational Drug

<b>Introduction:</b> The ability to discriminate among ligands binding to the same protein target in terms of their relative binding affinity lies at the heart of structure-based drug design. Any improvement in the accuracy and reliability of binding affinity prediction methods decreases the discrepancy between experimental and computational results.<br><b>Objectives:</b> The primary objectives were to find the most relevant features affecting binding affinity prediction, least use of manual feature engineering, and improving the reliability of binding affinity prediction using efficient deep learning models by tuning the model hyperparameters.<br><b>Methods:</b> The binding site of target proteins was represented as a grid box around their bound ligand. Both binary and distance-dependent occupancies were examined for how an atom affects its neighbor voxels in this grid. A combination of different features including ANOLEA, ligand elements, and Arpeggio atom types were used to represent the input. An efficient convolutional neural network (CNN) architecture, DeepAtom, was developed, trained and tested on the PDBbind v2016 dataset. Additionally an extended benchmark dataset was compiled to train and evaluate the models.<br><b>Results: </b>The best DeepAtom model showed an improved accuracy in the binding affinity prediction on PDBbind core subset (Pearson’s R=0.83) and is better than the recent state-of-the-art models in this field. In addition when the DeepAtom model was trained on our proposed benchmark dataset, it yields higher correlation compared to the baseline which confirms the value of our model.<br><b>Conclusions:</b> The promising results for the predicted binding affinities is expected to pave the way for embedding deep learning models in virtual screening and rational drug design fields.

Rational Drug Design Approach of Receptor Tyrosine Kinase Type III Inhibitors

2020 ◽  
Vol 26 (42) ◽  
pp. 7623-7640 ◽  
Author(s):  
Cheolhee Kim ◽  
Eunae Kim
Keyword(s):  
Drug Design ◽  
Tyrosine Kinase ◽  
Receptor Tyrosine Kinase ◽  
Synergistic Effects ◽  
Rational Drug Design ◽  
Computational Techniques ◽  
Biological Targets ◽  
Type Iii ◽  
Theoretical Approaches ◽  
Rational Drug

: Rational drug design is accomplished through the complementary use of structural biology and computational biology of biological macromolecules involved in disease pathology. Most of the known theoretical approaches for drug design are based on knowledge of the biological targets to which the drug binds. This approach can be used to design drug molecules that restore the balance of the signaling pathway by inhibiting or stimulating biological targets by molecular modeling procedures as well as by molecular dynamics simulations. Type III receptor tyrosine kinase affects most of the fundamental cellular processes including cell cycle, cell migration, cell metabolism, and survival, as well as cell proliferation and differentiation. Many inhibitors of successful rational drug design show that some computational techniques can be combined to achieve synergistic effects.

Recent Advances in the Rational Drug Design Based on Multi-target Ligands

2020 ◽  
Vol 27 (28) ◽  
pp. 4720-4740 ◽  
Author(s):  
Ting Yang ◽  
Xin Sui ◽  
Bing Yu ◽  
Youqing Shen ◽  
Hailin Cong
Keyword(s):  
Drug Resistance ◽  
Clinical Practice ◽  
Side Effects ◽  
Drug Design ◽  
Rational Drug Design ◽  
Health Conditions ◽  
Pharmacokinetic Parameters ◽  
Single Target ◽  
Rational Drug ◽  
Huge Challenge

Multi-target drugs have gained considerable attention in the last decade owing to their advantages in the treatment of complex diseases and health conditions linked to drug resistance. Single-target drugs, although highly selective, may not necessarily have better efficacy or fewer side effects. Therefore, more attention is being paid to developing drugs that work on multiple targets at the same time, but developing such drugs is a huge challenge for medicinal chemists. Each target must have sufficient activity and have sufficiently characterized pharmacokinetic parameters. Multi-target drugs, which have long been known and effectively used in clinical practice, are briefly discussed in the present article. In addition, in this review, we will discuss the possible applications of multi-target ligands to guide the repositioning of prospective drugs.

Rational Drug Design Paradigms: The Odyssey for Designing Better Drugs

2015 ◽  
Vol 18 (3) ◽  
pp. 238-256 ◽  
Author(s):  
Tahsin Kellici ◽  
Dimitrios Ntountaniotis ◽  
Eleni Vrontaki ◽  
George Liapakis ◽  
Panagiota Moutevelis-Minakakis ◽  
...  
Keyword(s):  
Drug Design ◽  
Rational Drug Design ◽  
Rational Drug

scholarly journals Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge

2021 ◽  
Author(s):  
Teresa Danielle Bergazin ◽  
Nicolas Tielker ◽  
Yingying Zhang ◽  
Junjun Mao ◽  
M. R. Gunner ◽  
...  
Keyword(s):  
Free Energy ◽  
Partition Coefficients ◽  
Physical Property ◽  
Rational Drug Design ◽  
Log P ◽  
Prediction Methods ◽  
Research Groups ◽  
Reasonable Accuracy ◽  
Statistical Assessment ◽  
Rational Drug

AbstractThe Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds. The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7. Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods.

scholarly journals Modeling temperature- and Cav3 subtype-dependent alterations in T-type calcium channel mediated burst firing

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fernando R. Fernandez ◽  
Mircea C. Iftinca ◽  
Gerald W. Zamponi ◽  
Ray W. Turner
Keyword(s):  
Calcium Channel ◽  
Neuronal Excitability ◽  
Neuronal Firing ◽  
Mammalian Brain ◽  
Peripheral Tissues ◽  
Window Current ◽  
Modeling Data ◽  
The Brain ◽  
Firing Neuron ◽  
Cav3 Channel

AbstractT-type calcium channels are important regulators of neuronal excitability. The mammalian brain expresses three T-type channel isoforms (Cav3.1, Cav3.2 and Cav3.3) with distinct biophysical properties that are critically regulated by temperature. Here, we test the effects of how temperature affects spike output in a reduced firing neuron model expressing specific Cav3 channel isoforms. The modeling data revealed only a minimal effect on baseline spontaneous firing near rest, but a dramatic increase in rebound burst discharge frequency for Cav3.1 compared to Cav3.2 or Cav3.3 due to differences in window current or activation/recovery time constants. The reduced response by Cav3.2 could optimize its activity where it is expressed in peripheral tissues more subject to temperature variations than Cav3.1 or Cav3.3 channels expressed prominently in the brain. These tests thus reveal that aspects of neuronal firing behavior are critically dependent on both temperature and T-type calcium channel subtype.

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