Crystal structure of the PAS domain of the hEAG potassium channel

Discovery of a Novel Shared Variant Among RTEL1 Gene and RTEL1-TNFRSF6B lncRNA at Chromosome 20q13.33 in Familial Progressive Myoclonus Epilepsy

Background: Progressive myoclonus epilepsy (PME) is a neurodegenerative disorder marked by recurrent seizures and progressive myoclonus. To date, based on the phenotypes and causal genes, more than 40 subtypes of PMEs have been identified, and more remain to be characterized. Our study is aimed at identifying the aberrant gene(s) possibly associated with PMEs in two siblings born to asymptomatic parents, in the absence of known genetic mutations. Methods: Clinical assessments and molecular analyses, such as the repeat expansion test for CSTB; SCA1, 2, 3, 6, and 7; whole exome sequencing (WES); and mitochondrial genome sequencing coupled with computational analysis, were performed. Results: A family-based segregation analysis of WES data was performed to identify novel genes associated with PMEs. The potassium channel, KCNH8 [c.298T>C; (p.Tyr100His)], a DNA repair gene, regulator of telomere elongation helicase 1 (RTEL1) [c.691G>T; (p.Asp231Tyr)] and long noncoding RNA, RTEL1-TNFRSF6B [chr20:62298898_G>T; NR_037882.1, hg19] were among the candidate genes that were found to be associated with PMEs. These homozygous variations in siblings belong to genes with a loss-of-function intolerant (pLI) score of ≤ 0.86, expected to be detrimental by multiple computational analyses, and were heterozygous in parents. Additionally, computational analysis and the expression of RTEL1 and RTEL1-TNFRSF6B revealed that RTEL1-TNFRSF6B may modulate RTEL1 via hsa-miR-3529-3p. In the patient with the severe phenotype, a further deleterious mutation in SLC22A17 was identified. No de novo variants specific to these probands were identified in the mitochondrial genome. Conclusions: Our study is the first to report variants in KCNH8, RTEL1, and RTEL1-TNFRSF6B among PME cases. These genes when characterized fully may shed light on pathogenicity and have the potential to be used in the diagnosis of PME.

Prediction of Kv11.1 potassium channel PAS-domain variants trafficking via machine learning

Congenital long QT syndrome (LQTS) is characterized by a prolonged QT-interval on an electrocardiogram (ECG). An abnormal prolongation in the QT-interval increases the risk for fatal arrhythmias. Genetic variants in several different cardiac ion channel genes, including KCNH2, are known to cause LQTS. Here, we evaluated whether structure-based molecular dynamics (MD) simulations and machine learning (ML) could improve the identification of missense variants in LQTS-linked genes. To do this, we investigated KCNH2 missense variants in the Kv11.1 channel protein shown to have wild type (WT) like or class II (trafficking-deficient) phenotypes in vitro. We focused on KCNH2 missense variants that disrupt normal Kv11.1 channel protein trafficking, as it is the most common phenotype for LQTS-associated variants. Specifically, we used computational techniques to correlate structural and dynamic changes in the Kv11.1 channel protein PAS domain (PASD) with Kv11.1 channel protein trafficking phenotypes. These simulations unveiled several molecular features, including the numbers of hydrating waters and hydrogen bonding pairs, as well as folding free energy scores, that are predictive of trafficking. We then used statistical and machine learning (ML) (Decision tree (DT), Random forest (RF), and Support vector machine (SVM)) techniques to classify variants using these simulation-derived features. Together with bioinformatics data, such as sequence conservation and folding energies, we were able to predict with reasonable accuracy (≈75%) which KCNH2 variants do not traffic normally. We conclude that structure-based simulations of KCNH2 variants localized to the Kv11.1 channel PASD led to an improvement in classification accuracy. Therefore, this approach should be considered to complement the classification of variant of unknown significance (VUS) in the Kv11.1 channel PASD.

Druggability assessment of mammalian Per-Arnt-Sim [PAS] domains using computational approaches

Per-Arnt-Sim (PAS) domains are key regions that occur in different regulatory proteins from all kingdoms of life. PAS domains show a remarkably conserved structural scaffold, despite a highly variable primary sequence. In this study we have attempted to address some of the gaps in knowledge regarding the druggability of PAS-A domains, differences in structure and dynamics within the PAS domain family and how this affects the druggability potential, as well as give insight into the druggability of steroid receptor coactivators and putative binding modes of the NCOA1. Investigations were performed through a range of computational methods including molecular docking studies, atomistic molecular dynamics simulations, and hotspot mapping. Atomistic molecular dynamics simulations show that the function of the AhR PAS-B domain is regulated by the dynamics of the highly conserved tyrosine Y322 residue, which acts as a "gatekeeper" controlling the access to the binding cavity and finely tuning the binding affinity. Furthermore, the transition between the partially unfolded and helical conformation of the loop1 segment within PAS-B domains was shown to be essential for the generation of "druggable" sites, especially for the NCOA1 PAS-B domain. Finally, our simulations indicated the undruggability of PAS-A domains, caused by the inherent characteristics of their putative binding sites. In conclusion, this work emphasises the role of intrinsic dynamics in tuning the druggability of PAS-B domains and shows that PAS-B domains of steroid receptor coactivators, such as NCOA1, can be targeted by small molecule ligands, which highlights the potential of developing new therapeutics designed to target these coactivators using structure-based approaches.

Node of Ranvier as an Array of Bio-Nanoantennas for Infrared Communication in Nerve Tissue

Electromagnetic radiation, in the visible and infrared spectrum, is increasingly being investigated for its possible role in the most evolved brain capabilities. Beside experimental evidence of electromagnetic cellular interactions, the possibility of light propagation in the axon has been recently demonstrated using computational modelling, although an explanation of its source is still not completely understood. We studied electromagnetic radiation onset and propagation at optical frequencies in myelinated axons, under the assumption that ion channel currents in the node of Ranvier behave like an array of nanoantennas emitting in the wavelength range from 300 to 2500 nm. Our results suggest that the wavelengths below 1600 nm are most likely to propagate throughout myelinated segments. Therefore, a broad wavelength window exists where both generation and propagation could happen, which in turn raises the possibility that such a radiation may play some role in neurotransmission.