Jan 2026· Journal of Chemical Information and Modeling· Vol 66, pp. 1309-1315· 0 citations· 34 references
MedicineComputer Science
TL;DR
NavDB is a specialized and open-access database focusing on VGSC modulators and targets that integrates 8023 curated data records covering 5168 compounds, including small molecules, toxins, drugs, and peptides, along with comprehensive annotations on biological activity, druggability, and structural feature.
Abstract
Voltage-gated sodium channels (VGSCs/Navs) are essential targets for the treatment of numerous neurological, muscular, and cardiac disorders. Despite the increasing clinical interest in subtype-selective modulators, current public databases provide fragmented and inconsistent information on VGSC-related compounds and targets, particularly lacking coverage on peptides. To address this limitation, we developed NavDB, a specialized and open-access database focusing on VGSC modulators and targets. NavDB integrates 8023 curated data records covering 5168 compounds, including small molecules, toxins, drugs, and peptides, along with comprehensive annotations on biological activity, druggability, and structural feature. NavDB also features advanced functions such as text-based and structure-based search, peptide similarity matching, and AI-powered property prediction. Moreover, the database offers high-quality 3D visualizations of targets and peptides, with disulfide bond and signal peptide annotations. All data are freely downloadable to support both experimental and computational drug discovery. NavDB is publicly available at: http://cadd.zju.edu.cn/navdb/.
Voltage-gated sodium channel NaV1.7 is a key mediator of electrical excitability and signal transmission in peripheral nociceptors and has emerged as a highly attractive therapeutic target for the development of novel analgesic agents. However, the development of selective NaV1.7 inhibitors has been characterized by significant challenges, with repeated failures in clinical trials despite encouraging preclinical data. In this study, we developed and validated a series of ligand-based pharmacophore models (LBPMs) that can be useful for the discovery of novel NaV1.7 inhibitors with improved selectivity profiles. Using the VGSC database as our primary data source, we focused on sulfonamide-based inhibitors targeting the voltage-sensing domain IV (VSD-IV). Validation against active compounds and decoys demonstrated that most models achieved good discrimination performance with high areas under the curve (AUC) and strong enrichment factors. External validation using 22 inhibitors extracted from recent literature confirmed the models’ capability to identify novel NaV1.7 inhibitors. Virtual screening of 3 million commercially available compounds retrieved promising hits and known inhibitors, with molecular docking studies revealing binding modes consistent with established sulfonamide-based inhibitors. Experimental validation identified one compound with measurable selectivity for NaV1.7 over NaV1.5, providing preliminary support for the utility of the developed virtual screening workflow. In parallel, we developed NaV1.5 LBPMs to assess selectivity profiles and minimize potential cardiotoxic effects. Overall, our findings provide valuable computational tools and structural insights for the rational design of selective NaV1.7 inhibitors, offering important starting points for developing analgesics with reduced off-target effects.
Martina Piga, Péter Lukács, K. Pesti et al.· Journal of Computer-Aided Mo...· 0 citations
Results show that current co-folding methods remain unreliable as stand-alone predictors of ion-channel ligand-binding modes and highlight pose sampling, pocket selection, ligand representation and independent structural validation as priorities for methodological development.
Yu Zhu, Taufiq Rahman· Frontiers in Biophysics· 0 citations
Traditional broad-spectrum sodium channel blockers have long served as the mainstay of epilepsy therapy, yet their clinical utility is constrained by dose-limiting adverse effects and the risk of exacerbating certain genetic epilepsies. Targeting the specific Nav subtypes, including Nav1.1, Nav1.2, Nav1.3, and Nav1.6, has emerged as a promising therapeutic strategy to mitigate these liabilities. In this Perspective, we highlight the structure, physiological functions, and their pathological roles in epilepsies, and analyze the clinical status of Pan-Nav inhibitors and the recent advances in drug discovery strategies targeting Nav isoforms. We also discussed the challenges and opportunities of Nav channel inhibitors, with the aim of shedding light on future Nav drug discovery, emphasizing that the development of subtype-selective modulators represents a highly promising strategy to overcome the clinical limitations of current broad-spectrum antiepileptic therapies.
Kv7 voltage-gated potassium channels play a critical role in controlling electrical properties of excitable tissues. Neuronally-expressed Kv7 channels are involved in both common and rare neuropsychiatric disorders, ranging from epilepsy to depression and neurodegenerative diseases; thus, they represent attractive therapeutic targets. However, no Kv7 modulator is currently available for clinical use. Improved knowledge of the functional and structural determinants responsible for ligand-induced Kv7 channel modulation is likely to fill this gap. In the present work, we describe the cryo-electron microscopy structures of human Kv7.2 channels in complex with two retigabine analogues: compound 60 (c60), which we previously described as a Kv7 activator with improved pharmacokinetic and pharmacodynamic properties, and the newly designed compound 106 (c106), which acts as a potent Kv7 blocker. Although both compounds occupy the same pocket at the S5-S6 interface in the pore domain, docking and molecular dynamics simulations and electrophysiological experiments revealed that the opposite functional behavior is due to their differential interaction, involving the L307 residue. Thus, we herein provide novel mechanistic insights into the molecular mechanisms governing Kv7 channel modulation by exogenous ligands which may prove useful to target Kv7 channels with more potent and selective modulators.
T. Ciaglia, G. Carleo, Zhenni Yang et al.· Angewandte Chemie· 0 citations
Voltage-gated sodium channels (NaVs) are critical membrane proteins in excitable cells, with NaV1.5 playing a pivotal role in cardiac electrophysiology. Mutations of human NaV1.5 (hNaV1.5) are linked to severe cardiac channelopathies, including atrial fibrillation and Brugada syndrome, making it a prime therapeutic target. Natural peptide toxins from venomous animals, such as tarantulas, offer valuable molecular tools for exploring NaV function. Among these, CcoTx3, a toxin from the straight-horned baboon tarantula, selectively inhibits hNaV1.5/β1 (IC50 = 447 nM), while other NaV subtypes are unaffected (hNaV1.1/β1-1.4/β1) or only partially blocked at higher concentrations (hNaV1.8/β1). Despite its pharmacological potential, the structural basis of CcoTx3 interaction with hNaV1.5 remains unresolved, particularly for the resting-state voltage-sensing domains II (VSDII) and IV (VSDIV), for which no experimental structure exists. This study combined molecular modeling and site-directed mutagenesis to elucidate the binding mechanism of the synthetic CcoTx3-hNaV1.5. Models of CcoTx3 bound to VSDII and VSDIV were generated, and molecular interactions were analyzed. Key binding residues were validated through site-directed mutagenesis at neurotoxin sites 3 and 4, followed by two-electrode voltage clamp assays. S743, E746, E747, R800, and S802 were identified as critical hotspots for inhibition of channel activation in VSDII, while D1610 and K1614 were key for fast inactivation inhibition. Synthetic CcoTx3 toxin (CcoTx3-synth) also interacted with zwitterionic and negatively charged liposomes, supporting a reduction-of-dimensionality mechanism. These findings provide the first structural and functional insights into the selective multisite engagement of CcoTx3-synth with hNaV1.5 and may guide the design of peptide therapeutics targeting cardiac channelopathies.
Erbio Díaz-Pico, Luciano Peña-Tejo, Pablo Barrías et al.· European Journal of Pharmaco...· 0 citations
Synaptic vesicle glycoprotein 2C (SV2C) is a vesicular protein enriched in dopaminergic neurons of the basal ganglia that modulates dopamine storage and release, and its disruption is implicated in Parkinson’s disease (PD). Despite strong genetic and pathological links to PD, there are no selective small-molecule probes for SV2C. Here, we describe an AI-enhanced virtual screening (VS) and experimental campaign that identified multiple novel chemotypes with low-micromolar affinity and marked selectivity for SV2C over SV2A and SV2B, starting from a large, general-purpose commercial library. Because no full-length high-resolution SV2C structure was available, we built a homology model using SV2A cryo-EM structures as templates and characterized its conformational landscape by molecular dynamics (MD) and Gaussian accelerated MD (GaMD) simulations in apo form and in complex with known SV2 ligands (plosaracetam, levetiracetam, brivaracetam, and padsevonil). A convolutional neural network-based scoring function (CNN VS), retrospectively validated on a manually curated 39-ligand SV2A benchmark (r = 0.72 vs experimental pIC50), was then applied in a multi-stage funnel to 5.96 million Mcule in-stock compounds, which were sequentially filtered to 3.19 million CNS-relevant molecules before docking and rescoring. From 94 VS-prioritized candidates, 71 compounds were experimentally profiled in an orthogonal primary assay cascade combining a thermal shift assay (TSA) with a [3H]-padsevonil scintillation proximity assay (SPA), followed by Ki determination and isoform selectivity profiling for key hits. This campaign yielded 22 active molecules (31% hit rate) that naturally segregated into two categories: compounds that showed primary site competition, and compounds that did not show primary site competition with [3H]-padsevonil. A subset of competitor compounds also showed thermostabilization activity. Among these, compounds 36 and 56 emerged as particularly attractive leads, with Ki values of 24.6 µM and 3.25 µM at SV2C, respectively, and >10-fold selectivity versus SV2A; compound 56 also maintained ∼12-fold selectivity relative to SV2B. A complementary subset of SV2C-selective hits behaved as padsevonil-site competitors, providing a lead set that will serve as a template for functional characterization and future drug development for conditions that affect dopaminergic signaling. Docking analysis suggests a common binding mode anchored by conserved tryptophan residues in the SV2 pocket, a prediction independently confirmed by an unpublished SV2A– plosaracetam cryo-EM structure showing 0.76 Å binding-site Cα RMSD relative to the SV2C model and complete conservation of the tryptophan cage. Subtle differences in the luminal domain and transmembrane region point to the structural determinants underlying isoform selectivity. Collectively, these results demonstrate that an AI-driven VS pipeline, tightly integrated with medium-throughput biophysical assays, can deliver selective SV2C binders from a general chemical library on a structurally under-characterized membrane target. The identified hits provide multiple starting points for hit-to-lead optimization and tools for probing SV2C biology and its role in PD.
Alexander C. Brueckner, Matthew F. Martin, Sheenam Khuttan et al.· bioRxiv· 0 citations
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