Identification and classification of ion channels across the tree of life provide functional insights into understudied CALHM channels

Ion channels (ICs) are membrane-bound proteins critical to many physiological processes in the human body, including regulating cell volume, neurotransmitter release, muscle contraction, and glandular secretion (Como et al., 2021; Meir et al., 1999; Thorneloe and Nelson, 2005; Rajan et al., 1990). Abnormal channel functions have been causally associated with ‘channelopathies’ such as Parkinson’s disease, epilepsy, cardiac arrhythmia, cancer, and cystic fibrosis, to name but a few (Edelman and Saussereau, 2012; Kim, 2014; Rivolta et al., 2020; Bagal et al., 2013). The development of selective chemical probes for channels in disease states is currently hindered by the limited knowledge of the diverse gating mechanisms, ion selectivity, and pathway associations displayed by the various channels encoded in the human genome (Bagal et al., 2013; Braun et al., 2020). While IC sequences from diverse organisms encode critical information regarding underlying functions and effective mining of sequence data can provide important context for predicting and testing understudied IC functions, traditional bioinformatic approaches have had limited success due to the challenges in consistently defining the full IC complement (Wickenden et al., 2012; Fodor and Aldrich, 2006), and accurately aligning and mining large sequence datasets (Neuwald, 2009). Online resources like the collaborative platform Channelpedia (Ranjan et al., 2011), the Guide to Pharmacology (GtoP) database (Alexander et al., 2023), structure centric ChanFAD (Castro et al., 2022), and ChannelsDB (Špačková et al., 2024), and several other efforts have previously cataloged and curated ICs and provide extensive information on a number of IC sequences, but do not include all the human-encoded ICs, nor provide information on ICs from other organisms and taxa (Jegla et al., 2009; Gao et al., 2019; Li and Gallin, 2004; Moran et al., 2015). Most IC studies across taxa are largely confined to closely related families or limited taxonomic groups (Lara et al., 2023; Uribe et al., 2024).

The extensive diversification and widespread abundance of ICs across cell types and their similarities to other transmembrane (TM) protein families, such as transporters, have led to an inconsistent definition of the human IC complement. For example, previous literature has reported around 230 human ICs (Jegla et al., 2009). The Kyoto Encyclopedia of Genes and Genomes (KEGG) database has cataloged around 316 human ICs (Kanehisa and Goto, 2000; Kanehisa et al., 2023), the GtoP database lists 278 ICs (Alexander et al., 2023), while Pharos (Kelleher et al., 2023) and The Human Genome Organization (HUGO) (Seal et al., 2023) list around 344 and 330 proteins, respectively. Moreover, these resources classify the human ICs based on their function, which is not known for many. Furthermore, current classification rarely accounts for the pore-forming or auxiliary roles of ICs. Channel proteins often form large macromolecular complexes in association with other IC and auxiliary subunits. Separate studies have highlighted the myriad of roles that the non-conducting auxiliary subunits play in an IC complex that control channel trafficking, gating, and pharmacology (Kato and Bredt, 2007; Li et al., 2006; Abbott, 2022), making them suitable therapeutic targets for drugs to regulate IC activity. Unfortunately, many of the existing resources fail to identify, include, and annotate such auxiliary channels, leading to their exclusion from large-scale analyses for clinical outcomes. Due to these inconsistencies, downstream analyses have been hindered and limited to certain families or groups of closely related channels. Consequently, our current knowledge of IC functions is skewed toward a subset of well-studied ‘light’ channels, while a significant portion of the channelome remains understudied and is referred to as ‘dark’ channels by the Illuminating Druggable Genome (IDG) consortium (Sharma and Nadler, 2021; Sheils et al., 2020). Concerted efforts such as IDG and the Structural Genomics Consortium (Abbott, 2022) help address these gaps in knowledge by systematically identifying and prioritizing such understudied members. However, it is imperative to develop a functional and an evolutionary classification framework that provides tools for researchers to extend knowledge from light members to their dark counterparts, enabling them to make meaningful biological inferences and shed light on their critical roles in function and disease states.

The current classification of channel genes is largely based on experimentally determined electrophysiological parameters such as the type of ions they transport (Na⁺, K⁺, Ca²⁺, Cl^-) and the channel gating mechanism such as gating by voltage potential (voltage-gated) or ligand binding (ligand-gated), which has been quite helpful in placing ICs in a functional context (Alexander et al., 2023). One of the first comprehensive classifications of ICs was done by Jegla et al., 2009, where they described 235 human ICs distributed in 24 families, along with their conservation across select metazoan species, and family-specific phylogeny and evolutionary analyses. A more recent collection of ICs along with their classification can be obtained from the GtoP database (Alexander et al., 2023), a resource dedicated to providing detailed overviews of over 1900 human drug targets, spanning six major pharmacological targets – ICs being one of them. GtoP classifies 278 human ICs into 3 major groups (voltage-gated ion channels [VGICs], ligand-gated ion channels [LGICs], and other) and 31 families, and provides a detailed overview of these channels in a friendly interface. However, it does not include a lot of now well-known IC families such as calcium homeostasis modulator channels (CALHMs) or bestrophins (Best). Additionally, the resource being a general drug target resource is not IC-centric and lacks evolutionary and residue-level functional insights that might help hypotheses generation. The role or annotation for auxiliary channels, which play critical roles in the function and regulation of ICs, (Kato and Bredt, 2007; Vacher and Trimmer, 2011), has not been addressed in these resources either.

On the other hand, cryo-electron microscopy (cryo-EM) studies and analysis of IC structures have shown that despite extensive variation in primary sequences, several channels adopt common structural folds and mechanisms of action (Chen et al., 2023). For example, several ICs – potassium (K⁺), sodium (Na⁺), calcium (Ca²⁺), transient receptor potential, and hyperpolarization-activated cyclic nucleotide-gated – grouped together as voltage-gated-like, are proposed to have evolved from a common ancestor because they share key sequence and structural features (Yu et al., 2005; Huffer et al., 2020). Thus, quantitative comparisons of these commonly conserved regions at the sequence and structural level can provide new residue-level insights into IC function and a stronger basis for functional classification, much like in other large protein families such as kinases and glycosyltransferases (Shrestha et al., 2020; Picado et al., 2020; Taujale et al., 2020; Taujale et al., 2021). This is imperative since selective targeting of channels in diseases and a mechanistic understanding of disease-associated mutations in channelopathies will require a residue-level understanding of function-determining features in both well-studied ‘light’ and understudied ‘dark’ channels. Thus, there is a critical need for an updated classification that places ICs in functionally and evolutionarily related groups, enabling a deeper residue-level analysis of light and dark channels alike.

To develop a comprehensive classification of ICs, we first mined literature and sequence data sources to collect information on ICs stored across various databases and in disparate data sources and formats to build a well-curated knowledgebase toward defining the human ion ‘channelome.’ A comprehensive list encompassing established and putative IC sequences in the human proteome is provided as a unified table alongside other contextual data for functional annotations such as regulatory interactions, ion selectivity, and pore-lining residues. Leveraging the identification of a pore region and pore-lining residues, we make a clear distinction between pore-containing vs auxiliary ICs. Based on this curation, we then perform a comprehensive classification of ICs into well-defined groups and families and identify the extent of understudied channels in each family, providing a premise for prioritizing studies in IC families with more understudied members.

We further performed a comprehensive evolutionary analysis to define and collect more than 48,000 well-defined IC orthologous relationships from diverse taxonomic groups, spanning metazoans, fungi, protists, bacteria, and archaea. We demonstrate the application of these sequences in annotating understudied CALHMs at residue-level resolution using Bayesian statistical approaches (Neuwald, 2014) and in predicting and experimentally validating the structural and functional impact of disease-associated mutations. These studies support our working premise that integrative mining of available sequence, structure, and functional data on ICs from diverse organisms (well-studied and understudied) will provide an important context for defining sequence and structural features associated with understudied channel functions.

Here, for the first time, we have computationally defined the full IC complement of the human genome – the ‘channelome’. We provide this comprehensive list and a rich annotation of functional, structural, and sequence features, mapping them to 4 widely accepted IC groups and further classifying them into 55 families. We also highlight unclassified outlier groups that contain most of the understudied ‘dark’ and potentially novel unclassified IC sequences. As part of our curation, we also provide annotation for the pore-containing domain that is based on multiple sources, including an extensive literature review, further strengthened by the application of literature mining using LLMs and structural analysis tools. We use the pore-containing domain to distinguish pore-containing from auxiliary ICs, providing additional functional context. Our annotations can serve as a reference for comparing ICs within or across families, designing experiments for functional studies, and identifying potential targets to illuminate the functional relevance of understudied ICs further.

The application of LLMs, specifically RAG systems, in our research demonstrates significant potential in automating literature mining and correcting certain inaccuracies. However, the system currently faces limitations related to diverse data presentation formats, complex channel subunit relationships, and variant gene nomenclature, which hinder its effectiveness. The high frequency of responses where evidence was not found underscores the need for enhanced entity recognition capabilities, particularly for accurately identifying gene and protein names across different nomenclatures. Additionally, the RAG system’s ability to critically engage with data by identifying and amending presumed inaccuracies can be widely used to verify and correct annotation entries, though this also raises concerns about potential overcorrections or misinterpretations without adequate validation. By more data cleaning and standardizations, LLMs and RAG systems can become more reliable and integral tools for curating and expanding bioinformatics databases, ultimately enhancing the accuracy and comprehensiveness of our IC knowledgebase.

To the best of our knowledge, identifying true orthologs across the tree of life performed here is the first large-scale effort to consolidate IC orthologs across diverse organisms and provides a comprehensive view of the evolutionary conservation of individual ICs. Based on this analysis, we could pinpoint the Aquaporins family of ICs as the most ancient family of ICs with orthologous sequences present back to bacterial and archaeal species. More importantly, the clustering of human ICs based on their depth of conservation placed them into functionally meaningful clusters with many enriched functions exclusive to their orthologous taxonomic group. The placement of understudied ICs in such groups allows for meaningful functional predictions, which can be further elucidated using experimental approaches.

The orthologous sequences identified and presented here can serve as a valuable resource for performing evolutionary and functional analysis using statistical and machine learning approaches. We demonstrate one such use by performing a Bayesian pattern-based classification on the CALHM subset of ICs to identify amino acid positions significantly conserved across all CALHM sequences. These features reside on a functionally important S1-S2 linker region that potentially governs their gating mechanism. Because these features were conserved and shared across all CALHM sequences, we also hypothesize that all CALHM sequences share this gating mechanism. By performing targeted mutations on these conserved residues, we show that a mutation in any of these evolutionarily conserved residues results in a dramatic loss of gating function, thus highlighting the functional importance of the identified pattern positions.

Among the conserved positions targeted for mutations, mutations of residues in the S1-S2 linker (F40C in CALHM1; F39L in CALHM6; Y52A in CALHM1; and Y51A in CALHM6) resulted in strong phenotypic changes, most likely due to their direct involvement in the conformational dynamics of S1 for channel gating. Mutations in W114 in CALHM1, which is not directly on the S1-S2 linker, also resulted in abolished activity; however, mutations in an analogous position W113 in CALHM6 did not impair channel function, presenting an exception compared to other residues across CALHM1 and 6. Among other residues that are near – but not within – the S1-S2 linker, the positioning of P60 on the S2 helix of CALHM1 is particularly intriguing. In the cryo-EM structure, P60 resides approximately midway along S2, inducing a distortion or bending of the helix due to the rigid ring structure of proline. This bent configuration allows extensive contact between the extracellular portion of S2 and the S1-S2 linker, while the intracellular portion of S2 interacts extensively with S1. Furthermore, we hypothesize that this bent conformation of S2 contributes to the flexibility of the S1-S2 linker, as if S2 were straightened, it would consequently straighten the S1-S2 linker, potentially reducing its flexibility. Replacing the proline with glycine eliminates the structural constraint imposed by proline’s cyclic side chain, allowing S2 to adopt a more regular, uninterrupted helical structure. Consequently, a straightened S2 may lead to reduced flexibility of the S1-S2 linker, ultimately impacting channel gating. Similarly, L57 in CALHM1 is positioned near P60 on the protrusion of the bend of S2, with its side chain facing residues on the adjacent S3. We hypothesize that the larger side chain of the L57R mutant would force S2 to straighten due to steric collision between the bulky arginine side chain and residues on S2, again reducing the flexibility of the S1-S2 linker and altering channel gating. A127 in CALHM6 resides in a short alpha helix within the extracellular domain. While A127 does not directly interact with the S1-S2 linker, it is adjacent to the highly conserved disulfide bond (between C41 and C126), linking the helix containing A127 to the S1-S2 linker. Thus, it is conceivable that the A127G mutant may indirectly affect the conformation of the S1-S2 linker through this disulfide bond.

These findings complement prior studies and provide additional insights into CALHM gating mechanisms. Several previous studies examined conserved residues in CALHM channels and proposed roles in gating (Tanis et al., 2013; Danielli et al., 2023; Tanis et al., 2017; Ma et al., 2025; Kwon et al., 2021; Syrjänen et al., 2023). These studies were based on comparisons of a limited set of homologs from model organisms such as C. elegans or mouse and identified residues in various parts of the protein that influence gating, providing important clues toward their functioning. Here, we have extended the analysis to encompass thousands of CALHM sequences collected from the entire tree of life, allowing us to identify residues conserved across all family members through evolution. Guided by a hypothesis from previous structural and functional studies (Ma et al., 2025; Choi et al., 2019), which highlighted the NTH/S1 region as a key element in channel gating, we focused on evolutionarily conserved residues in the S1-S2 linker and at the interface of S1 with the rest of the TMD. We reasoned that if S1 movement is critical for gating, then these two structural elements – the S1-S2 linker, acting as a hinge, and the S1 interface with the TMD, serving as a stabilizing contact – would be key determinants of the conformational dynamics of S1.

Together, our experimental data indicate that the conserved residues at the S1-S2 linker and its immediate surroundings play an important role in CALHM channel gating, supporting a model in which S1 dynamics are central to the gating mechanism (Ma et al., 2025; Choi et al., 2019). Furthermore, the contrasting phenotypes of Y52A in CALHM1 vs Y51A in CALHM6, W114A in CALHM1 vs W113A of CALHM6, and I109W in CALHM1 vs L108W in CALHM6 highlight differences in gating properties specific to each family member. Overall, the complementary results from this study and the published literature highlight the complexity of CALHM gating and suggest that distinct conserved elements contribute to both shared and lineage-specific gating mechanisms in this unique family of large-pore channels. Importantly, this was demonstrated not only for the well-studied CALHM1 but also for the relatively understudied human CALHM6, providing valuable clues into shared gating features across light and dark CALHM sequence sets.

In addition to the CALHM shared patterns, we also present a second subset of conserved positions shared only within CALHM2, 4, 5, and 6, paralogs that are evolutionarily closer compared to CALHM1 and 3 (Figure 3—figure supplement 1). These subsets of conserved residues fall in the intracellular helical segment that is involved in oligomerization and formation of the pore complex governing CALHM function. Previous studies have indicated that CALHM2 adopts a unique undecameric oligomer different from the CALHM1 octamer (Syrjanen et al., 2020). Thus, with the presence of shared patterns within the subset of CALHM2 and the understudied CALHM4, 5, and 6 in this intracellular helical region, we hypothesize that these conserved positions help maintain a similar mode of oligomerization between these evolutionarily related subsets of CALHMs. Because many disease mutations map to these conserved positions, we believe the datasets and approaches offer a powerful avenue for elucidating the functional and clinical relevance of the understudied ICs.

The human IC annotation table with all the curation information is made available with the manuscript as Supplementary file 1A. The fasta sequences for the human ICs (both full-length sequences and the pore domain sequences) are available through Zenodo. The full length sequences for all the identified orthologs are also available through Zenodo. The code and results related to the RAG annotation pipeline are available at GitHub (copy archived at Kannan, 2026).

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Author details

1. Rahil Taujale

   1. Institute of Bioinformatics, University of Georgia, Athens, United States
   2. Department of Biochemistry and Molecular Biology, University of Georgia, Athens, United States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Sung Jin Park

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1292-1619

2. Sung Jin Park

   Department of Molecular Biosciences, Northwestern University, Evanston, United States

   Contribution

   Data curation, Formal analysis, Visualization, Methodology, Writing – original draft

   Contributed equally with

   Rahil Taujale

   Competing interests

   No competing interests declared

3. Nathan Gravel

   Institute of Bioinformatics, University of Georgia, Athens, United States

   Contribution

   Resources, Formal analysis, Validation, Investigation

   Competing interests

   No competing interests declared

4. Saber Soleymani

   Department of Biochemistry and Molecular Biology, University of Georgia, Athens, United States

   Contribution

   Data curation, Formal analysis, Visualization, Methodology, Writing – original draft

   Competing interests

   No competing interests declared

5. Rayna Carter

   Department of Biochemistry and Molecular Biology, University of Georgia, Athens, United States

   Contribution

   Data curation, Formal analysis, Methodology

   Competing interests

   No competing interests declared

6. Kennady Boyd

   Department of Biochemistry and Molecular Biology, University of Georgia, Athens, United States

   Contribution

   Resources, Data curation

   Competing interests

   No competing interests declared

7. Sarah I Keuning

   Department of Molecular Biosciences, Northwestern University, Evanston, United States

   Contribution

   Formal analysis, Validation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0009-0008-9408-5119

8. Zheng Ruan

   Department of Biochemistry & Molecular Biology, Thomas Jefferson University, Philadelphia, United States

   Contribution

   Supervision, Validation, Methodology

   Competing interests

   No competing interests declared

9. Wei Lü

   1. Department of Molecular Biosciences, Northwestern University, Evanston, United States
   2. Department of Pharmacology, Northwestern University, Chicago, United States
   3. Chemistry of Life Processes Institute, Northwestern University, Evanston, United States

   Contribution

   Conceptualization, Funding acquisition, Investigation, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   wei.lu@northwestern.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3009-1025

10. Natarajan Kannan

    1. Institute of Bioinformatics, University of Georgia, Athens, United States
    2. Department of Biochemistry and Molecular Biology, University of Georgia, Athens, United States

    Contribution

    Conceptualization, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    nkannan@uga.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2833-8375

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  citation for Reviewed Preprint v2 https://doi.org/10.7554/eLife.106134.2