Predicting novel disease mutations in the cardiac sodium channel

In silico analysis of TRPM4 variants of unknown clinical significance

BACKGROUND

TRPM4 is a calcium-activated channel that selectively permeates monovalent cations. Genetic variants of the channel in cardiomyocytes are associated with various heart disorders, such as progressive familial heart block and Brugada syndrome. About97% of all known TRPM4 missense variants are classified as variants of unknown clinical significance (VUSs). The very large number of VUSs is a serious problem in diagnostics and treatment of inherited heart diseases.

METHODS AND RESULTS

We collected 233 benign or pathogenic missense variants in the superfamily of TRP channels from databases ClinVar, Humsavar and Ensembl Variation to compare performance of 22 algorithms that predict damaging variants. We found that ClinPred is the best-performing tool for TRP channels. We also used the paralogue annotation method to identify disease variants across the TRP family. In the set of 565 VUSs of hTRPM4, ClinPred predicted pathogenicity of 299 variants. Among these, 12 variants are also categorized as LP/P variants in at least one paralogue of hTRPM4. We further used the cryo-EM structure of hTRPM4 to find scores of contact pairs between parental (wild type) residues of VUSs for which ClinPred predicts a high probability of pathogenicity of variants for both contact partners. We propose that 68 respective missense VUSs are also likely pathogenic variants.

CONCLUSIONS

ClinPred outperformed other in-silico tools in predicting damaging variants of TRP channels. ClinPred, the paralogue annotation method, and analysis of residue contacts the hTRPM4 cryo-EM structure collectively suggest pathogenicity of 80 TRPM4 VUSs.

Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications

Membrane proteins mediate a wide spectrum of biological processes, such as signal transduction and cell communication. Due to the arduous and costly nature inherent to the experimental process, membrane proteins have long been devoid of well-resolved atomic-level tertiary structures and, consequently, the understanding of their functional roles underlying a multitude of life activities has been hampered. Currently, computational tools dedicated to furthering the structure-function understanding are primarily focused on utilizing intelligent algorithms to address a variety of site-wise prediction problems (e.g., topology and interaction sites), but are scattered across different computing sources. Moreover, the recent advent of deep learning techniques has immensely expedited the development of computational tools for membrane protein-related prediction problems. Given the growing number of applications optimized particularly by manifold deep neural networks, we herein provide a review on the current status of computational strategies mainly in membrane protein type classification, topology identification, interaction site detection, and pathogenic effect prediction. Meanwhile, we provide an overview of how the entire prediction process proceeds, including database collection, data pre-processing, feature extraction, and method selection. This review is expected to be useful for developing more extendable computational tools specific to membrane proteins.

How Functional Genomics Can Keep Pace With VUS Identification

Over the last two decades, an exponentially expanding number of genetic variants have been identified associated with inherited cardiac conditions. These tremendous gains also present challenges in deciphering the clinical relevance of unclassified variants or variants of uncertain significance (VUS). This review provides an overview of the advancements (and challenges) in functional and computational approaches to characterize variants and help keep pace with VUS identification related to inherited heart diseases.

Intersegment Contacts of Potentially Damaging Variants of Cardiac Sodium Channel

Over 1,500 missense variants of sodium channel hNav1.5, which are reported in the ClinVar database, are associated with cardiac diseases. For most of the variants, the clinical significance is uncertain (VUS), not provided (NP), or has conflicting interpretations of pathogenicity (CIP). Reclassifying these variants as pathogenic/likely pathogenic (P/LP) variants is important for diagnosing genotyped patients. In our earlier work, several bioinformatics tools and paralogue annotation method consensually predicted that 74 VUS/NP/CIP variants of 54 wild type residues (set w54) are potentially damaging variants (PDVs). Atomic mechanisms underlying dysfunction of the PDVs are unknown. Here we employed a recent cryo-EM structure of the hNav1.5 channel with likely inactivated pore domain (PD) and activated voltage-sensing domains (VSDs), and ad hoc models of the closed and open PD and resting VSDs to explore intersegment contacts of w54 residues. We found that 44 residues from set w54 contact 84 residues with 118 disease missense variants. These include 104 VUS/NP/CIP variants, most of which are associated with the loss-of-function Brugada syndrome (BrS1) or gain-of-function long QT syndrome (LQT3). Matrix representation of the PDVs and their contact variants facilitated recognition of coupled mutations associated with the same disease. In particular, BrS1-associated coupled mutations, which disturb the P-loops region with the selectivity filter slow inactivation gate, would cause the channel dysfunction. Other likely causes of the channel dysfunction include coupled BrS1-associated variants within VSDs that would destabilize their activated states and coupled LQT3-associated variants, which would stabilize the open PD or activated VSDs. Our study proposes mechanisms of channel dysfunction for scores of BrS1- and LQT3-associated variants, confirms status for 82% of PDVs, and suggests damaging status for their contact variants, which are currently categorized as VUS/NP/CIP variants.

L-Type Calcium Channel: Predicting Pathogenic/Likely Pathogenic Status for Variants of Uncertain Clinical Significance

(1) Background: Defects in gene CACNA1C, which encodes the pore-forming subunit of the human Cav1.2 channel (hCav1.2), are associated with cardiac disorders such as atrial fibrillation, long QT syndrome, conduction disorders, cardiomyopathies, and congenital heart defects. Clinical manifestations are known only for 12% of CACNA1C missense variants, which are listed in public databases. Bioinformatics approaches can be used to predict the pathogenic/likely pathogenic status for variants of uncertain clinical significance. Choosing a bioinformatics tool and pathogenicity threshold that are optimal for specific protein families increases the reliability of such predictions. (2) Methods and Results: We used databases ClinVar, Humsavar, gnomAD, and Ensembl to compose a dataset of pathogenic/likely pathogenic and benign variants of hCav1.2 and its 20 paralogues: voltage-gated sodium and calcium channels. We further tested the performance of sixteen in silico tools in predicting pathogenic variants. ClinPred demonstrated the best performance, followed by REVEL and MCap. In the subset of 309 uncharacterized variants of hCav1.2, ClinPred predicted the pathogenicity for 188 variants. Among these, 36 variants were also categorized as pathogenic/likely pathogenic in at least one paralogue of hCav1.2. (3) Conclusions: The bioinformatics tool ClinPred and the paralogue annotation method consensually predicted the pathogenic/likely pathogenic status for 36 uncharacterized variants of hCav1.2. An analogous approach can be used to classify missense variants of other calcium channels and novel variants of hCav1.2.

Recombinant PaurTx-3, a spider toxin, inhibits sodium channels and decreases membrane excitability in DRG neurons

Voltage-gated sodium channels are critical for the generation and propagation of action potentials. Gating modifier toxins from spider venom can modulate the gating mechanism of sodium channels and thus have potential as drug leads. Here, we established expression of the gating modifier toxin PaurTx-3, a sodium channel inhibitor found in the venom of the spider Phrixotrichus auratus. Whole-cell voltage-clamp recordings indicated that recombinant PaurTx-3 (rPaurTx-3) inhibited Nav1.4, Nav1.5, and Nav1.7 currents with IC₅₀ values of 61 nM, 72 nM, and 25 nM, respectively. Furthermore, rPaurTx-3 irreversibly inhibited Nav1.7 currents, but had 60-70% recovery in Nav1.4 and Nav1.5 after washing with a bath solution. rPaurTx-3 also hyperpolarized the voltage-dependent steady-state inactivation curve and significantly slowed recovery from fast inactivation of Nav1.7. Current-clamp recordings showed that rPaurTx-3 suppressed small DRG neuron activity. The biological activity assay findings for rPaurTx-3 support its potent pharmacological effect in Nav1.7 and small DRG neurons.

Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins

Membrane proteins are unique in that they interact with lipid bilayers, making them indispensable for transporting molecules and relaying signals between and across cells. Due to the significance of the protein's functions, mutations often have profound effects on the fitness of the host. This is apparent both from experimental studies, which implicated numerous missense variants in diseases, as well as from evolutionary signals that allow elucidating the physicochemical constraints that intermembrane and aqueous environments bring. In this review, we report on the current state of knowledge acquired on missense variants (referred to as to single amino acid variants) affecting membrane proteins as well as the insights that can be extrapolated from data already available. This includes an overview of the annotations for membrane protein variants that have been collated within databases dedicated to the topic, bioinformatics approaches that leverage evolutionary information in order to shed light on previously uncharacterized membrane protein structures or interaction interfaces, tools for predicting the effects of mutations tailored specifically towards the characteristics of membrane proteins as well as two clinically relevant case studies explaining the implications of mutated membrane proteins in cancer and cardiomyopathy.