Gate Modulation Research Articles

Effect of two activators on the gating of a K2P channel

TWIK-related potassium channel 1 (TREK1), a two-pore-domain mammalian potassium (K+) channel, regulates the resting potential across cell membranes, presenting a promising therapeutic target for neuropathy treatment. The gating of this channel converges in the conformation of the narrowest part of the pore: the selectivity filter (SF). Various hypotheses explain TREK1 gating modulation, including the dynamics of loops connecting the SF with transmembrane helices and the stability of hydrogen bond (HB) networks adjacent to the SF. Recently, two small molecules (Q6F and Q5F) were reported as activators that affect TREK1 by increasing its open probability in single-channel current measurements. Here, using molecular dynamics simulations, we investigate the effect of these ligands on the previously proposed modulation mechanisms of TREK1 gating compared to the apo channel. Our findings reveal that loop dynamics at the upper region of the SF exhibit only a weak correlation with permeation events/nonpermeation periods, whereas the HB network behind the SF appears more correlated. These nonpermeation periods arise from both distinct mechanisms: a C-type inactivation (resulting from dilation at the top of the SF), which has been described previously, and a carbonyl flipping in an SF binding site. We find that, besides the prevention of C-type inactivation in the channel, the ligands increase the probability of permeation by modulating the dynamics of the carbonyl flipping, influenced by a threonine residue at the bottom of the SF. These results offer insights for rational ligand design to optimize the gating modulation of TREK1 and related K+ channels.

Zinc inhibits the voltage-gated proton channel HCNL1

Voltage-gated ion channels allow ion flux across biological membranes in response to changes in the membrane potential. HCNL1 is a recently discovered voltage-gated ion channel that selectively conducts protons through its voltage-sensing domain (VSD), reminiscent of the well-studied depolarization-activated Hv1 proton channel. However, HCNL1 is activated by hyperpolarization, allowing the influx of protons, which leads to an intracellular acidification in zebrafish sperm. Zinc ions (Zn2+) are important cofactors in many proteins and essential for sperm physiology. Proton channels such as Hv1 and Otopetrin1 are inhibited by Zn2+. We investigated the effect of Zn2+ on heterologously expressed HCNL1 channels using electrophysiological and fluorometric techniques. Extracellular Zn2+ inhibits HCNL1 currents with an apparent half-maximal inhibition (IC50) of 26 μM. Zn2+ slows voltage-dependent current kinetics, shifts the voltage-dependent activation to more negative potentials, and alters hyperpolarization-induced conformational changes of the voltage sensor. Our data suggest that extracellular Zn2+ inhibits HCNL1 currents by multiple mechanisms, including modulation of channel gating. Two histidine residues located at the extracellular side of the VSD might weakly contribute to Zn2+ coordination: mutants with either histidine replaced with alanine show modest shifts of the IC50 values to higher concentrations. Interestingly, Zn2+ inhibits HCNL1 at even lower concentrations from the intracellular side (IC50 ≈ 0.5 μM). A histidine residue at the intracellular end of S1 (position 50) is important for Zn2+ binding: much higher Zn2+ concentrations are required to inhibit the mutant HCNL1-H50A (IC50 ≈ 106 μM). We anticipate that Zn2+ will be a useful ion to study the structure-function relationship of HCNL1 as well as the physiological role of HCNL1 in zebrafish sperm.

Improving real-time object detection in Internet-of-Things smart city traffic with YOLOv8-DSAF method

With the rise of global smart city construction, target detection technology plays a crucial role in optimizing urban functions and improving the quality of life. However, existing target detection technologies still have shortcomings in terms of accuracy, real-time performance, and adaptability. To address this challenge, this study proposes an innovative target detection model. Our model adopts the structure of YOLOv8-DSAF, comprising three key modules: depthwise separable convolution (DSConv), dual-path attention gate module (DPAG), and feature enhancement module (FEM). Firstly, DSConv technology optimizes computational complexity, enabling real-time target detection within limited hardware resources. Secondly, the DPAG module introduces a dual-channel attention mechanism, allowing the model to selectively focus on crucial areas, thereby improving detection accuracy in high-dynamic traffic scenarios. Finally, the FEM module highlights crucial features to prevent their loss, further enhancing detection accuracy. Additionally, we propose an Internet of Things smart city framework consisting of four main layers: the application domain, the Internet of Things infrastructure layer, the edge layer, and the cloud layer. The proposed algorithm utilizes the Internet of Things infrastructure layer, edge layer, and cloud layer to collect and process data in real-time, achieving faster response times. Experimental results on the KITTI V and Cityscapes datasets indicate that our model outperforms the YOLOv8 model. This suggests that in complex urban traffic scenarios, our model exhibits superior performance with higher detection accuracy and adaptability. We believe that this innovative model will significantly propel the development of smart cities and advance target detection technology.

Analytical Photoresponses of Gated Nanowire Photoconductors.

Low-dimensional photoconductors have extraordinarily high photoresponse and gain, which can be modulated by gate voltages as shown in literature. However, the physics of gate modulation remains elusive. In this work, the physics of gate modulation in silicon nanowire photoconductors with the analytical photoresponse equations is investigated. It is found that the impact of gate voltage varies vastly for nanowires with different size. For the wide nanowires that cannot be pinched off by high gate voltage, it is found that the photoresponses are enhanced by at least one order of magnitude due to the gate-induced electric passivation. For narrow nanowires that starts with a pinched-off channel, the gate voltage has no electric passivation effect but increases the potential barrier between source and drain, resulting in a decrease in dark and photocurrent. For the nanowires with an intermediate size, the channel is continuous but can be pinched off by a high gate voltage. The photoresponsivity and photodetectivity is maximized during the transition from the continuous channel to the pinched-off one. This work provides important insights on how to design high-performance photoconductors.

CaM-dependent modulation of human CaV1.3 whole-cell and single-channel currents by C-terminal CaMKII phosphorylation site S1475.

Phosphorylation enables rapid modulation of voltage-gated calcium channels (VGCC) in physiological and pathophysiological conditions. How phosphorylation modulates human CaV1.3 VGCC, however, is largely unexplored. We characterized modulation of CaV1.3 gating via S1475, the human equivalent of a phosphorylation site identified in the rat. S1475 is highly conserved in CaV1.3 but absent from all other high-voltage activating calcium channel types co-expressed with CaV1.3 in similar tissues. Further, it is located in the C-terminal EF-hand motif, which binds calmodulin (CaM). This is involved in calcium-dependent channel inactivation (CDI). We used amino acid exchanges that mimic either sustained phosphorylation (S1475D) or phosphorylation resistance (S1475A). Whole-cell and single-channel recordings of phosphorylation state imitating CaV1.3 variants in transiently transfected HEK-293 cells revealed functional relevance of S1475 in human CaV1.3. We obtained three main findings: (1) CaV1.3_S1475D, imitating sustained phosphorylation, displayed decreased current density, reduced CDI and (in-) activation kinetics shifted to more depolarized voltages compared with both wildtype CaV1.3 and the phosphorylation-resistant CaV1.3_S1475A variant. Corresponding to the decreased current density, we find a reduced open probability of CaV1.3_S1475D at the single-channel level. (2) Using CaM overexpression or depletion, we find that CaM is necessary for modulating CaV1.3 through S1475. (3) CaMKII activation led to CaV1.3_WT-current properties similar to those of CaV1.3_S1475D, but did not affect CaV1.3_S1475A, confirming that CaMKII modulates human CaV1.3 via S1475. Given the physiological and pathophysiological importance of CaV1.3, our findings on the S1475-mediated interplay of phosphorylation, CaM interaction and CDI provide hints for approaches on specific CaV1.3 modulation under physiological and pathophysiological conditions. KEY POINTS: Phosphorylation modulates activity of voltage-gated L-type calcium channels for specific cellular needs but is largely unexplored for human CaV1.3 channels. Here we report that S1475, a CaMKII phosphorylation site identified in rats, is functionally relevant in human CaV1.3. Imitating phosphorylation states at S1475 alters current density and inactivation in a calmodulin-dependent manner. In wildtype CaV1.3 but not in the phosphorylation-resistant variant S1475A, CaMKII activation elicits effects similar to constitutively mimicking phosphorylation at S1475. Our findings provide novel insights on the interplay of modulatory mechanisms of human CaV1.3 channels, and present a possible target for CaV1.3-specific gating modulation in physiological and pathophysiological conditions.

Pre-gating and contextual attention gate — A new fusion method for multi-modal data tasks

Multi-modal representation learning has received significant attention across diverse research domains due to its ability to model a scenario comprehensively. Learning the cross-modal interactions is essential to combining multi-modal data into a joint representation. However, conventional cross-attention mechanisms can produce noisy and non-meaningful values in the absence of useful cross-modal interactions among input features, thereby introducing uncertainty into the feature representation. These factors have the potential to degrade the performance of downstream tasks. This paper introduces a novel Pre-gating and Contextual Attention Gate (PCAG) module for multi-modal learning comprising two gating mechanisms that operate at distinct information processing levels within the deep learning model. The first gate filters out interactions that lack informativeness for the downstream task, while the second gate reduces the uncertainty introduced by the cross-attention module. Experimental results on eight multi-modal classification tasks spanning various domains show that the multi-modal fusion model with PCAG outperforms state-of-the-art multi-modal fusion models. Additionally, we elucidate how PCAG effectively processes cross-modality interactions

2D Reconfigurable van der Waals Heterojunction for Logic Gate Circuits and Wide-Spectrum Photodetectors via Sulfur Substitution and Band Matching.

The attractive physical properties of two-dimensional (2D) semiconductors in group IVA-VIA have been fully revealed in recent years. Combining them with 2D ambipolar materials to construct van der Waals heterojunctions (vdWHs) can offer tremendous opportunities for designing multifunctional electronic and optoelectronic devices, such as logic switching circuits, half-wave rectifiers, and broad-spectrum photodetectors. Here, an optimized SnSe0.75S0.25 is grown to design a SnSe0.75S0.25/MoTe2 vdWH for logic operation and wide-spectrum photodetection. Benefiting from the excellent gate modulation under the appropriate sulfur substitution and type-II band alignment, the device exhibits reconfigurable antiambipolar and ambipolar transfer behaviors at positive and negative source-drain voltage (Vds), enabling stable XNOR logic operation. It also features a gate-modulated positive and negative rectifying behavior with rectification ratios of 265:1 and 1:196, confirming its potential as half-wave logic rectifiers. Besides, the device can respond from visible to infrared wavelength up to 1400 nm. Under 635 nm illumination, the maximum responsivity of 1.16 A/W and response time of 657/500 μs are achieved at the Vds of -2 V. Furthermore, due to the strong in-plane anisotropic structure of SnSe0.75S0.25-alloyed nanosheet and narrow bandgap of 2H-MoTe2, it shows a broadband polarization-sensitive function with impressive photocurrent anisotropic ratios of 15.6 (635 nm), 7.0 (808 nm), and 3.7 (1310 nm). The direction along the maximum photocurrent can be reconfigurable depending on the wavelengths. These results indicate that our designed alloyed SnSe0.75S0.25/MoTe2 vdWH has reconfigurable logic operation and broadband photodetection capabilities in 2D multifunctional integrated circuits.

AdaFN-AG: Enhancing multimodal interaction with Adaptive Feature Normalization for multimodal sentiment analysis

In multimodal sentiment analysis, achieving effective fusion among text, acoustic, and visual modalities for enhanced sentiment prediction is a crucial research topic. Recent studies typically employ tensor-based or attention-based mechanisms for multimodal fusion. However, the former fails to achieve satisfactory prediction performance, and the latter complicates the computation of fusion between non-textual modalities. Therefore, this paper proposes the multimodal sentiment analysis model based on Adaptive Feature Normalization and Attention Gating mechanism (AdaFN-AG). Firstly, facing highly synchronized non-textual modalities, we design the Adaptive Feature Normalization (AdaFN) method, which focuses more on sentiment features interaction rather than timing features association. In AdaFN, acoustic and visual modality features achieve cross-modal interaction through normalization, inverse normalization, and mix-up operations, with weights utilized for adaptive strength regulation of the cross-modal interaction. Meanwhile, we design the Attention Gating mechanism that facilitates cross-modal interactions between textual and non-textual modalities through cross-attention and captures timing associations, while the gating module concurrently regulates the intensity of these interactions. Additionally, we employ self-attention to capture the intrinsic correlations within single-modal features. Subsequently, we conduct experiments on three benchmark datasets for multimodal sentiment analysis, with the results indicating that AdaFN-AG outperforms the baselines across the majority of evaluation metrics. Through research and experiments, we validate that AdaFN-AG not only enhances performance by adopting appropriate methods for different types of cross-modal interactions while conserving computational resources but also verifies the generalization capability of the AdaFN method.

Numerical modelling for triple hybrid gate optimization dielectric modulated junctionless gate all around SiNWFET based uricase and ChOX biosensor

Numerical modelling for triple hybrid gate optimization dielectric modulated junctionless gate all around SiNWFET based uricase and ChOX biosensor

Cavitation Investigation in the Sluice Section of the Sefid Rood Dam Using Flow 3D Software for Environmental Purposes

It is evident that water resources are essential for the existence of living organisms, particularly human life. Outlets are a series of structures employed to transfer water from the dam reservoir to the discharge point downstream. Due to the significance of this section of the dam, the performance analysis of the outlet, including the channel, gates, and their outlet, is sensitive. The presence of pressurized flow in the upstream of the outlet gate, energy dissipation due to various factors, and the very low values concerning the gate opening compared to the water head over the outlet gate cause significant errors in determining various parameters related to the outlets. This includes pressure drops across the gates and their discharge capacities when using theoretical methods. This research aims to investigate pressure distribution at various points along the outlet channel, determine the gate discharge capacity, and calculate its discharge coefficient. It explores the possibility of cavitation occurrence, compares the presented scenarios for post-service and emergency gate operations in the simultaneous operation of two gates, and determines the main loss coefficients in the channel, including frictional losses, conversion losses, and gate losses. This investigation utilizes data obtained from the physical model of the spillway outlet constructed at the Soil and Watershed Conservation Research Center laboratory. The physical model includes the channel and gates (service and emergency), and necessary experiments were conducted. The pressure values at different points, gate discharge rates at three opening levels (60%, 80%, and 100%), were measured in the reservoir, and the results are presented in corresponding tables and graphs. Additionally, the Flow 3D software was employed to numerically model the outlet discharge under three gate openings (60%, 80%, and 100%) for comparison between experimental and numerical results and with previous findings in this research. Subsequently, it will be demonstrated that, under single-gate operation and simultaneous operation, the cavitation index in critical areas, such as gate slots and between gates, in the single- gate mode falls within an acceptable range, practically eliminating the risk of cavitation. However, in simultaneous operation mode, negative pressures occur in some gate openings, posing the possibility of cavitation occurrence.

Anisotropic Network Analysis of Open/Closed HCN4 Channel Advocates Asymmetric Subunit Cooperativity in cAMP Modulation of Gating.

Hyperpolarization-activated cyclic nucleotide-modulated (HCN) channels are opened in an allosteric manner by membrane hyperpolarization and cyclic nucleotides such as cAMP. Because of conflicting reports from experimental studies on whether cAMP binding to the four available binding sites in the channel tetramer operates cooperatively in gating, we employ here a computational approach as a promising route to examine ligand-induced conformational changes after binding to individual sites. By combining an elastic network model (ENM) with linear response theory (LRT) for modeling the apo-holo transition of the cyclic nucleotide-binding domain (CNBD) in HCN channels, we observe a distinct pattern of cooperativity matching the "positive-negative-positive" cooperativity reported from functional studies. This cooperativity pattern is highly conserved among HCN subtypes (HCN4, HCN1), but only to a lesser extent visible in structurally related channels, which are only gated by voltage (KAT1) or cyclic nucleotides (TAX4). This suggests an inherent cooperativity between subunits in HCN channels as part of a ligand-triggered gating mechanism in these channels.

Unveiling Tst3, a Multi-Target Gating Modifier Scorpion α Toxin from Tityus stigmurus Venom of Northeast Brazil: Evaluation and Comparison with Well-Studied Ts3 Toxin of Tityus serrulatus.

Studies on the interaction sites of peptide toxins and ion channels typically involve site-directed mutations in toxins. However, natural mutant toxins exist among them, offering insights into how the evolutionary process has conserved crucial sequences for activities and molecular target selection. In this study, we present a comparative investigation using electrophysiological approaches and computational analysis between two alpha toxins from evolutionarily close scorpion species of the genus Tityus, namely, Tst3 and Ts3 from T. stigmurus and T. serrulatus, respectively. These toxins exhibit three natural substitutions near the C-terminal region, which is directly involved in the interaction between alpha toxins and Nav channels. Additionally, we characterized the activity of the Tst3 toxin on Nav1.1-Nav1.7 channels. The three natural changes between the toxins did not alter sensitivity to Nav1.4, maintaining similar intensities regarding their ability to alter opening probabilities, delay fast inactivation, and induce persistent currents. Computational analysis demonstrated a preference for the down conformation of VSD4 and a shift in the conformational equilibrium towards this state. This illustrates that the sequence of these toxins retained the necessary information, even with alterations in the interaction site region. Through electrophysiological and computational analyses, screening of the Tst3 toxin on sodium isoform revealed its classification as a classic α-NaTx with a broad spectrum of activity. It effectively delays fast inactivation across all tested isoforms. Structural analysis of molecular energetics at the interface of the VSD4-Tst3 complex further confirmed this effect.

Advancing non-invasive fetal health monitoring: A time–frequency approach to extracting fetal electrocardiogram signals

The fetal electrocardiogram (FECG) provides an important way for clinicians to assess fetal health and to monitor pregnancy conditions. Although FECG can be captured through abdominal electrocardiogram (AECG) recordings from pregnant women, it often receives interference from maternal cardiac activity and other external sources. Particularly, as the high-amplitude maternal electrocardiogram (MECG) typically obscures the waveform of the FECG, isolating FECG from the AECG signals is challenging. Nevertheless, the differences in frequency patterns between MECG and FECG suggest a potential way for reconstructing FECG by combining the frequency and amplitude information. To this end, we proposed a novel method for separating FECG signals from the AECG via the time–frequency representation. We designed an encoder–decoder architecture based hierarchical multiscale-aware network to capture features embedded in both the time and frequency domains. Equipped with a holistic attention-aware module (HAA), the model extracts and consolidates fetal heart activity-related features in the time–frequency domain. Further introducingan attention gate module (AG) to emphasize key features during encoder-to-decoder transmission, the model enhances the quality and efficiency of FECG extraction without any redundancy in high-quality feature mapping. The model was trained using a hybrid time-domain and frequency-domain loss function and validated on two public databases. Excellent performances, such as an average Pearson correlation coefficient of 0.85 for estimating the quality of FECG signals, were observed demonstrating its excellent performance and providing a promising non-invasive method for monitoring fetal health. These findings indicate that the proposed method effectively captures the amplitude differences between fetal and maternal heartbeats across various frequency components within the AECG, leading to the extraction of high-quality FECG signals.

High spatiotemporal resolution scintillation imaging of pulsed pencil beam scanning proton beams produced by a gantry-mounted synchrocyclotron.

A dosimeter with high spatial and temporal resolution would be of significant interest for pencil beam scanning (PBS) proton beams' characterization, especially when facing small fields and beams with high temporal dynamics. Optical imaging of scintillators has potential in providing sub-millimeter spatial resolution with pulse-by-pulse basis temporal resolution when the imaging system is capable of operating in synchrony with the beam-producing accelerator. We demonstrate the feasibility of imaging PBS proton beams as they pass through a plastic scintillator detector to simultaneously obtain multiple beam parameters, including proton range, pencil beam's widths at different depths, spot's size, and spot's position on a pulse-by-pulse basis with sub-millimeter resolution. A PBS synchrocyclotron was used for proton irradiation. A BC-408 plastic scintillator block with 30 × 30 × 5 cm3 size, and another block with 30 × 30 × 0.5 cm3 size, positioned in an optically sealed housing, were used sequentially to measure the proton range, and spot size/location, respectively. A high-speed complementary metal-oxide-semiconductor (CMOS) camera system synchronized with the accelerator's pulses through a gating module was used for imaging. Scintillation images, captured with the camera directly facing the 5-cm-thick scintillator, were corrected for background (BG), and ionization quenching of the scintillator to obtain the proton range. Spots' position and size were obtained from scintillation images of the 0.5-cm-thick scintillator when a 45° mirror was used to reflect the scintillation light toward the camera. Scintillation images with 0.16mm/pixel resolution corresponding to all proton pulses were captured. Pulse-by-pulse analysis showed that variations of the range, spots' position, and size were within±0.2% standard deviation of their average values. The absolute ranges were within±1mm of their expected values. The average spot-positions were mostly within±0.8mm and spots' sigma agreed within 0.2mm of the expected values. Scintillation-imaging PBS beams with high-spatiotemporal resolution is feasible and may help in efficient and cost-effective acceptance testing and commissioning of existing and even emerging technologies such as FLASH, grid, mini-beams, and so forth.

Allosteric Cholesterol Site in Glycine Receptors Characterized through Molecular Simulations.

Glycine receptors are pentameric ligand-gated ion channels that conduct chloride ions across postsynaptic membranes to facilitate fast inhibitory neurotransmission. In addition to gating by the glycine agonist, interactions with lipids and other compounds in the surrounding membrane environment modulate their function, but molecular details of these interactions remain unclear, in particular, for cholesterol. Here, we report coarse-grained simulations in a model neuronal membrane for three zebrafish glycine receptor structures representing apparent resting, open, and desensitized states. We then converted the systems to all-atom models to examine detailed lipid interactions. Cholesterol bound to the receptor at an outer-leaflet intersubunit site, with a preference for the open and desensitized versus resting states, indicating that it can bias receptor function. Finally, we used short atomistic simulations and iterative amino acid perturbations to identify residues that may mediate allosteric gating transitions. Frequent cholesterol contacts in atomistic simulations clustered with residues identified by perturbation analysis and overlapped with mutations influencing channel function and pathology. Cholesterol binding at this site was also observed in a recently reported pig heteromeric glycine receptor. These results indicate state-dependent lipid interactions relevant to allosteric transitions of glycine receptors, including specific amino acid contacts applicable to biophysical modeling and pharmaceutical design.

Partial hard occluded target reconstruction of Fourier single pixel imaging guided through range slice

Fourier single pixel imaging utilizes pre-programmed patterns for laser spatial distribution modulation to reconstruct intensity image of the target through reconstruction algorithms. The approach features non-locality and high anti-interference performance. However, Poor image quality is induced when the target of interest is occluded in Fourier single pixel imaging. To address the problem, a deep learning-based image inpainting algorithm is employed within Fourier single pixel imaging to reconstruct partially obscured targets with high quality. It applies a distance-based segmentation method to segment obscured regions and the target of interest. Additionally, it utilizes an image inpainting network that combines multi-scale sparse convolution and transformer architecture, along with a reconstruction network that integrates Channel Attention Mechanism and Attention Gate modules to reconstruct complete and clear intensity images of the target of interest. The proposed method significantly expands the application scenarios and improves the imaging quality of Fourier single pixel imaging. Simulation and real-world experimental results demonstrate that the proposed method exhibits the high inpainting and reconstruction capacity in the conditions of hard occlusion and down-sampling.

Self-supervised feature-gate coupling for dynamic network pruning

Gating modules have been widely explored in dynamic network pruning (DNP) to reduce the run-time computational cost of deep neural networks while keeping the features representative. Despite the substantial progress, existing methods remain ignoring the consistency between feature and gate distributions, which may lead to distortion of gated features. In this paper, we propose a feature-gate coupling (FGC) approach aiming to align distributions of features and gates. FGC is a plug-and-play module that consists of two steps carried out in an iterative self-supervised manner. In the first step, FGC utilizes the k-Nearest Neighbor algorithm in the feature space to explore instance neighborhood relationships, which are treated as self-supervisory signals. In the second step, FGC exploits contrastive self-supervised learning (CSL) to regularize gating modules, leading to the alignment of instance neighborhood relationships within the feature and gate spaces. Experimental results validate that the proposed FGC method improves the baseline approach with significant margins, outperforming state-of-the-art methods with a better accuracy-computation trade-off. Code is publicly available at github.com/smn2010/FGC-PR.

Structural basis for inhibition of the lysosomal two-pore channel TPC2 by a small molecule antagonist

Two pore channels are lysosomal cation channels with crucial roles in tumor angiogenesis and viral release from endosomes. Inhibition of the two-pore channel 2 (TPC2) has emerged as potential therapeutic strategy for the treatment of cancers and viral infections, including Ebola and COVID-19. Here, we demonstrate that antagonist SG-094, a synthetic analog of the Chinese alkaloid medicine tetrandrine with increased potency and reduced toxicity, induces asymmetrical structural changes leading to a single binding pocket at only one intersubunit interface within the asymmetrical dimer. Supported by functional characterization of mutants by Ca2+ imaging and patch clamp experiments, we identify key residues in S1and S4 involved in compound binding to the voltage sensing domain II. SG-094 arrests IIS4 in a downward shifted state which prevents pore opening via the IIS4/S5 linker, hence resembling gating modifiers of canonical VGICs. These findings may guide the rational development of new therapeutics antagonizing TPC2 activity.

Mechanosensing by Piezo1 and its implications in the kidney.

Piezo1 is an essential mechanosensitive transduction ion channel in mammals. Its unique structure makes it capable of converting mechanical cues into electrical and biological signals, modulating biological and (patho)physiological processes in a wide variety of cells. There is increasing evidence demonstrating that the piezo1 channel plays a vital role in renal physiology and disease conditions. This review summarizes the current evidence on the structure and properties of Piezo1, gating modulation, and pharmacological characteristics, with special focus on the distribution and (patho)physiological significance of Piezo1 in the kidney, which may provide insights into potential treatment targets for renal diseases involving this ion channel.

Evolutionary trajectory of TRPM2 channel activation by adenosine diphosphate ribose and calcium

Ion channel activation upon ligand gating triggers a myriad of biological events and, therefore, evolution of ligand gating mechanism is of fundamental importance. TRPM2, a typical ancient ion channel, is activated by adenosine diphosphate ribose (ADPR) and calcium and its activation has evolved from a simple mode in invertebrates to a more complex one in vertebrates, but the evolutionary process is still unknown. Molecular evolutionary analysis of TRPM2s from more than 280 different animal species has revealed that, the C-terminal NUDT9-H domain has evolved from an enzyme to a ligand binding site for activation, while the N-terminal MHR domain maintains a conserved ligand binding site. Calcium gating pattern has also evolved, from one Ca2+-binding site as in sea anemones to three sites as in human. Importantly, we identified a new group represented by olTRPM2, which has a novel gating mode and fills the missing link of the channel gating evolution. We conclude that the TRPM2 ligand binding or activation mode evolved through at least three identifiable stages in the past billion years from simple to complicated and coordinated. Such findings benefit the evolutionary investigations of other channels and proteins.