A Novel Loss-of-Function Variant in the Chloride Ion Channel Gene Clcn2 Associates with Atrial Fibrillation

Hansen, Thea Hyttel; Yan, Yannan; Ahlberg, Gustav; Vad, Oliver Bundgaard; Refsgaard, Lena; Santos, Joana Larupa; Mutsaers, Nancy; Svendsen, Jesper Hastrup; Olesen, Morten S.; Bentzen, Bo Hjorth; Schmitt, Nicole

doi:10.1038/s41598-020-58475-9

Cited by 13 publications

(11 citation statements)

References 46 publications

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“…The HICs that belonged to voltage-dependent anion channels controlled the flow of Ca 2+ ions during viral entry [6,24,55]. The chloride voltage gated channels helped to maintain homeostasis and also contributed to acidification, thus maintaining lysosomal pH [55][56][57][58][59]. Anoctamins may be responsible for the entry of viral proteins into the cells [60][61][62][63][64][65][66].…”

Section: Role Of Other Significant Hicsmentioning

confidence: 99%

Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

et al. 2022

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein–protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2.

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Section: Role Of Other Significant Hicsmentioning

confidence: 99%

Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

et al. 2022

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“…The proteins belonging to voltage dependent anion channels play a role in involving Ca 2+ ions during viral entry (6,58,59). Another important voltage gated channel showing interaction with the viral proteins were the chloride voltage gated channels which help in maintaining homeostasis and also contributes to acidification thus maintaining lysosomal pH (60)(61)(62)(63)(64).…”

Section: Protein-protein Interactions Of Sars-cov-2 Proteins With Hicsmentioning

confidence: 99%

Deciphering the interactions of SARS-CoV-2 proteins with human ion channels using machine learning-based method

Munjal

Sapra

Goyal

et al. 2021

Preprint

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the worldwide COVID-19 pandemic which began in 2019. It has a high transmission rate and pathogenicity leading to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning-based algorithms are providing higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, predictions of PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were performed using PPI-MetaGO algorithm. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% MCC score and 84.09% F1 score. Thereafter, PPI networks of SARS-CoV-2 proteins with HICs were generated. Furthermore, biological pathway analysis of HICs interacting with SARS-CoV-2 proteins showed the involvement of six pathways, namely inflammatory mediator regulation of TRP channels, insulin secretion, renin secretion, gap junction, taste transduction and apelin signaling pathway. The inositol 1,4,5-trisphosphate receptor 1 (ITPR1) and transient receptor potential cation channel subfamily A member 1 (TRPA1) were identified as potential target proteins. Various FDA approved drugs interacting with ITPR1 and TRPA1 are also available. It is anticipated that targeting ITPR1 and TRPA1 may provide a better therapeutic management of infection caused by SARS-CoV-2. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs.

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“…The proteins belonging to voltage dependent anion channels play a role involving Ca 2+ ions during viral entry (Fujioka et al 2018;Jitobaom et al 2016;Luzio et al 2007). Another important voltage gated channel showing interaction with the viral proteins were the chloride voltage gated channels which help in maintaining homeostasis and also contributes to acidification thus maintaining lysosomal pH (Bourdin et al 2015;Hansen et al 2020;Leisle et al 2011;Muller et al 2019;Yang et al 2011).…”

Section: Protein-protein Interactions Of Sars-cov-2 Proteins With Hicsmentioning

confidence: 99%

Deciphering the interactions of SARS-CoV-2 proteins with human ion channels using machine learning-based method

Munjal

Sapra

Goyal

et al. 2021

Preprint

View full text Add to dashboard Cite

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the worldwide COVID-19 pandemic which began in 2019. It has a high transmission rate and pathogenicity leading to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, predictions of PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were performed using PPI-MetaGO algorithm. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient (MCC) score and 84.09% F1 score. Thereafter, PPI networks of SARSCoV-2 proteins with HICs were generated. Furthermore, biological pathway analysis of HICs interacting with SARS-CoV-2 proteins showed the involvement of six pathways, namely inflammatory mediator regulation of transient receptor potential (TRP) channels, insulin secretion, renin secretion, gap junction, taste transduction and apelin signaling pathway. Our analysis suggests that transient receptor potential cation channel subfamily M member 4 (TRPM4), transient receptor potential cation channel subfamily A member 1 (TRPA1), gap junction protein alpha 1 (GJA1), potassium calcium-activated channel subfamily N member 4 (KCNN4), acid sensing ion channel subunit 1 (ASIC1) and inositol 1,4,5-trisphosphate receptor type 1 (ITPR1) could serve as an initial set to the experimentalists for further validation. Additionally, various US food and drug administration (FDA) approved drugs interacting with the potential HICs were also identified. The study also reinforcesthe drug repurposing approach for the development of host directed antiviral drugs.

show abstract

A Novel Loss-of-Function Variant in the Chloride Ion Channel Gene Clcn2 Associates with Atrial Fibrillation

Cited by 13 publications

References 46 publications

Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

Deciphering the interactions of SARS-CoV-2 proteins with human ion channels using machine learning-based method

Deciphering the interactions of SARS-CoV-2 proteins with human ion channels using machine learning-based method

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