Biology subjects

Lindahl, E.

Publications and source records attributed to Lindahl, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Molecular determinants of ligand recognition and efficacy in the TRPM3 voltage sensor-like domain

Transient receptor potential melastatin 3 (TRPM3) is a calcium-permeable ion channel implicated in chronic pain and developmental and epileptic encephalopathies. The voltage sensor-like domain (VSLD) is a major site of pharmacological modulation, but the molecular determinants of ligand recognition and efficacy remain incompletely understood. Here we combine cryo-electron microscopy, molecular dynamics simulations, mutagenesis, and medicinal chemistry to investigate the interactions of TRPM3 with the inhibitors isosakuranetin, maprotiline, and diclofenac. We show that structurally diverse ligands occupy a common VSLD cavity but engage distinct interaction networks. Functional and computational analyses identify ligand-specific residue dependencies and support a halogen bond between diclofenac and D947 that contributes to inhibitor potency. Furthermore, esterification or amidation of the diclofenac carboxylate converts inhibition into potentiation, and mutagenesis and molecular dynamics simulations support partially overlapping VSLD configurations associated with these opposing effects. Together, these findings establish the TRPM3 VSLD as an adaptable allosteric pocket in which ligand-specific interactions shape recognition, potency, and efficacy.

biophysics↗

bioRxiv2026

CryoLigATE: enhancing the resolvability of cryo-EM maps in protein-ligand complexes using deep learning

Cryo-electron microscopy (cryo-EM) has become a central tool for structure-based drug discovery, yet ligand-binding sites often remain substantially less well resolved than the surrounding protein, limiting reliable atomic interpretation. Although deep-learning methods have substantially improved overall cryo-EM map quality, their predominantly protein-focused training limits their ability to recover ligand density. Here we present CryoLigATE, a deep learning framework specifically designed to enhance densities associated with protein-bound ligands in cryo-EM maps. We curated a chemically and structurally diverse dataset of more than 6,000 protein-ligand complexes from the EMDB and PDB, encompassing drug-like molecules, lipids, steroids, carbohydrates and other ligand classes, and trained a hybrid convolutional-transformer network to enhance local density around binding pockets. During inference, CryoLigATE automatically extracts the target region from a preliminary atomic model, requiring no manual map preparation and completing localized refinement in seconds on a desktop GPU. Evaluation on an independent test set of 649 complexes demonstrates substantial improvements in ligand resolvability, particularly for maps with poorly resolved binding sites, while preserving high-quality experimental densities. The enhanced maps recover chemically meaningful features, including ligand functional groups and topological continuity, enabling more confident atomic modeling. By learning the structural diversity of ligand features, CryoLigATE addresses a longstanding limitation of cryo-EM map enhancement and provides a useful framework for improving structural interpretation and structure-guided drug discovery.

biophysics↗

bioRxiv2026

An atomic interaction conserved for over 600 million years gates inhibitory neurotransmission

Pentameric ligand-gated ion channels (pLGICs) mediate fast inhibitory neurotransmission critical for neuronal network stability. A tyrosine residue in the M2-M3 linker of inhibitory pLGICs, conserved for over 600 million years, is positioned where it could hydrogen bond (H-bond) to the backbone of the neighboring Cys-loop. Given the pathogenic effects of variants of this tyrosine, we hypothesized that this H-bond stabilizes extracellular-to-transmembrane domain coupling essential for channel gating. To test this hypothesis, we used site-directed mutagenesis, noncanonical amino acid incorporation, and electrophysiological recordings in Xenopus laevis oocytes to disrupt this hydrogen bond in GABAA and glycine receptors. Loss of this interaction via tyrosine substitutions or backbone amide modifications that ablate the acceptor or donor, respectively, markedly decrease agonist sensitivity and maximal channel activation, with effects localized to specific subunits. Molecular dynamics simulations support a role for this H-bond in channel gating. These findings reveal a critical atomic interaction underlying a shared mechanism for inhibitory receptor gating and provide a mechanistic explanation for disease-associated mutations linked to epilepsy, neurodevelopmental disability, and hyperekplexia.

biophysics↗

bioRxiv2026

Several multiple sequence alignment perturbation methods enhance AlphaFold3 sampling of alternative protein states

Protein function often involves multiple conformational states. Several multiple sequence alignment-perturbing strategies, including stochastic subsampling, clustering, and column masking, have been shown to enhance AlphaFold2 (AF2) sampling of alternative protein states. Here, we evaluate these strategies on AlphaFold3 (AF3) and compare their performance with the BioEmu Boltzmann sampling model on 107 proteins with multiple experimentally solved conformational states. We find that unperturbed AF3 samples alternative states with significantly higher TM-scores compared to AF2 and comparable to BioEmu. In particular, all MSA perturbation methods improve AF3 sampling at a statistically significant level, improving the top 1% TM-score by at least 0.05 in approximately 20% of cases each, while rarely worsening the performance. Furthermore, we find that different choices of amino acid masks can improve column-masked AF3 sampling for specific targets. Our results highlight how MSA perturbations remain relevant in AF3, providing a useful tool for understanding dynamic biological processes.

biophysics↗

bioRxiv2026

Mechanism of Alkaline Gating in a Pentameric Ion Channel

Pentameric ligand-gated ion channels (pLGICs) are key mediators of electrochemical signal transduction in various organisms. Like many proteins involved in cellular signaling, they are modulated by a variety of environmental factors including pH and small molecules. However, the molecular mechanisms underlying pLGIC activation and modulation remain unclear. A promising model system in this family is the bacterial ion channel sTeLIC, which can be activated by alkaline pH, and for which we recently determined structures in multiple functional states. However, protonation changes and other pH-driven dynamics cannot be directly observed in these structures. Here, we used constant-pH molecular dynamics simulations and oocyte-electrophysiology recordings from engineered mutants to develop a comprehensive mechanistic model for pH sensing. Interestingly, critical residues include two Glu residues (E106, E160) located in the extracellular-vestibule and domain-interface regions of each subunit, where they mediate differential electrostatic interactions in closed versus open states. This work demonstrates the applicability of constant-pH methods to model dynamic processes in a multimeric membrane-embedded protein, and offers a detailed mechanism for pH sensing, likely extensible to human drug targets.

biophysics↗

bioRxiv2025

A sensory system for mating in octopus

Sensory systems for mate recognition maintain species boundaries and influence diversification. Therefore, uncovering how molecules and receptors evolve to mediate this critical function is essential to understanding biodiversity. Male octopuses use a specialized arm called the hectocotylus to identify females and navigate their internal organs to reach the oviduct and deliver sperm. Here, we discovered that the hectocotylus is a dual sensory and mating organ that uses contactdependent chemosensation of progesterone, a conserved ovarian hormone. We identify chemotactile receptors for progesterone and resolve the structural basis for their evolution from ancestral neurotransmitter receptors and subsequent expansion and tuning across cephalopods. These findings reveal principles by which sensory innovations shape reproductive behavior and suggest mechanisms for how sensory evolution contributes to the diversification of life.

cell biology↗

bioRxiv2025

Calcium stabilization of a flexible N-terminal domain in a pentameric ligand-gated ion channel

Pentameric ligand-gated ion channels (pLGICs) are responsible for the rapid conversion of chemical to electrical signals. In addition to the canonical extracellular and transmembrane domains, some prokaryotic pLGICs contain an N-terminal domain (NTD) of unclear structure and function. In one such case, the calcium-sensitive channel DeCLIC, the NTD appears to accelerate gating; however, its evident flexibility has posed a challenge to model building, and its role in calcium sensitivity is unclear. Here we report cryo-EM structures of DeCLIC to the highest resolutions thus far, in circularized lipid nanodiscs. Application of refinement tools enabled definition of multiple calcium-binding sites in each symmetric subunit. Under calcium-free conditions, both symmetric and asymmetric classes could be reconstructed, implicating a heterogeneous ensemble. Behavior of these structures in molecular dynamics simulations was consistent with calcium stabilization of the NTD, an effect that may be conserved in structurally homologous domains across evolution.

biophysics↗

bioRxiv2025

Structure and dynamics of a multidomain ligand-gated ion channel revealed under acidic conditions

Pentameric ligand-gated ion channels are critical mediators of electrochemical signal transduction across evolution, including key targets of biophysical studies and therapeutic development. However, the intrinsically allosteric, polymodal, modular nature of gating in this protein family presents persistent challenges to biophysical characterization. The bacterial channel DeCLIC constitutes a provocative model system for structure, function, and dynamics in this family, including a modulatory N-terminal domain (NTD). Previous closed structures of DeCLIC support a rationale for its inhibition by calcium via a site of conserved relevance in other family members; however, mechanisms of gating in DeCLIC and properties of its open state have remained unclear. Here we integrated structure-function methods including cryogenic electron microscopy (cryo-EM), molecular dynamics simulations and small-angle neutron scattering under acidic conditions to characterize a previously unreported conformation of DeCLIC with a fully hydrated pore. In contrast to previous structures, the low-pH open conformation captured by cryo-EM was stable and permeable in simulations, and consistent with solution-phase behavior as measured by small-angle scattering. We further captured an alternative closed state of the channel, evidently promoted by depletion of modulatory calcium at low pH, exhibiting dynamic rearrangements in the N-terninal domain. The expanded-pore structure evidently corresponds to a functional open state of DeCLIC, while calcium-site and NTD dynamics drive channel closure, providing a detailed template for biophysical characterization of modulatory mechanisms in ligand-gated ion channels and related systems. Significance StatementThe bacterial protein DeCLIC is a provocative representative of the pentameric ligand-gated ion-channel family. Like its eukaryotic relatives, DeCLIC is sensitive to external calcium, and incorporates a possibly disordered modulatory domain. But as for many ion channels, the details of DeCLIC activation have remained unclear, as no stable open state has been characterized. Combining biophysical methods, including cryogenic electron microscopy, molecular dynamics simulations, and small-angle neutron scattering, allows us to capture, validate, and characterize an evidently open state of DeCLIC, as well as a closed state with a disordered modulatory region. Details of these structures, their function, and their dynamics allow us to propose a mechanism for DeCLIC gating, as well as a generalized scheme for the larger protein family.

biophysics↗

bioRxiv2025

Modeling ligands in cryo-EM with generative AI and density-guided simulations

Resolving protein-ligand interactions in atomic detail is key to understanding how small molecules regulate macromolecular function. Although recent break-throughs in cryogenic electron microscopy (cryo-EM) have enabled high-quality reconstruction of numerous complex biomolecules, the resolution of bound ligands is often relatively poor. Furthermore, automated methods for building and refining molecular models into cryo-EM maps have largely focused on proteins and may not be optimized for the diverse properties of small-molecule ligands. Here, we present an approach that integrates generative artificial intelligence (AI) with cryo-EM density-guided simulations to fit ligands into experimental maps. Using three inputs: 1) a protein amino acid sequence, 2) a ligand specification, and 3) an experimental cryo-EM map, we validated our approach on a set of biomedically relevant protein-ligand complexes including kinases, GPCRs, and solute transporters, none of which were present in the AI training data. In cases for which generative AI was not sufficient to predict experimental poses outright, integration of flexible fitting into molecular dynamics simulations improved ligand model-to-map cross-correlation relative to the deposited structure from 40-71% to 82-95%. This work offers a straightforward template for integrating generative AI and density-guided simulations to automate model building in cryo-EM maps of ligand-protein complexes, with potential applications for characterization and design of novel modulators and drugs.

biophysics↗

bioRxiv2025

Modeling cryo-EM structures in alternative states with generative AI and density-guided simulations

Modeling atomic coordinates into a target cryo-electron microscopy map is a crucial step in structure determination. Despite recent advances, proteins with multiple functional states remain a challenge - particularly when suitable molecular templates are unavailable for certain states, and the map resolution is not high enough to build de novo models. This is a common scenario, for example, among pharmacologically relevant membrane-bound receptors and transporters. Here, we introduce a refinement approach in which i) several initial models are generated by stochastic subsampling of the multiple sequence alignment (MSA) space in AlphaFold2, ii) the resulting models are subjected to structure-based clustering, iii) density-guided molecular dynamics simulations are performed from the centroid structures, and iv) a final model is selected on the basis of both map fit and model quality. This results in improved fitting accuracy compared to single starting point scenarios for three membrane proteins (the calcitonin receptor-like receptor, L-type amino acid transporter and alanine-serine-cysteine transporter which undergo substantial conformational transitions between functional states. Our results indicate that ensemble construction using generative AI combined with simulation-based refinement facilitates building of alternative states in several families of membrane proteins.

biophysics↗

bioRxiv2025

Structural basis for activation and potentiation in a human α5β3 GABAA receptor

General anesthetics like etomidate mediate amnesic as well as sedative effects through different populations of gamma amino butyric acid receptors (GABAARs) in the central nervous system. The amnesic effects have largely been attributed to 5-subunit-containing receptors in the hippocampus, indicating a clear role in learning and memory for these receptors. The 5 subunit is thought to primarily coassemble with {beta}3 and, in some cases, {gamma}2 subunits, generating a variety of receptor subtypes with differential functional and pharmacological properties. However, the stoichiometry, structure, and gating mechanisms of these different subpopulations are not well understood. Here we report structures of human 5{beta}3 GABAARs with various modulators, assembled in two stoichiometries. Our cryo-EM structures, combined with electrophysiology in Xenopus oocytes, support a primary assembly of 2:3 :{beta} subunits, though a minority population of 1:4 :{beta} indicates multiple assemblies are possible. Differential glycosylation of the 5 and {beta}3 subunits enabled reconstruction of the heteromeric complex even in the absence of added fiducials. In the resting state of the receptor, Zn2+ binds to histidine residues at the M2-17' position in the {beta}3 subunit, blocking ion passage. In the activated state, GABA binding to the orthosteric site is associated with global rearrangements propagating to unbinding of the 17' Zn2+ atoms and opening of the 9' hydrophobic gate. Unlike the 1{beta}3 receptor where GABA is effectively a partial agonist, saturating GABA binding to 5{beta}3 appears to drive activation of nearly all receptors, resulting in a single desensitized state observed under the cryo-EM conditions. In agreement with this high GABA efficacy, the GABA-bound structure is virtually unaffected by further addition of the anesthetic etomidate at the {beta}- transmembrane domain interface. These structures offer new detailed models for gating and modulation of a GABAAR subtype critical to learning and memory, including prospective templates for structure-based drug discovery.

biochemistry↗

bioRxiv2024

A single main-chain hydrogen bond required to keep GABAA receptors closed

GABAA receptors are the primary inhibitory neurotransmitter receptors throughout the central nervous system. Despite significant progress understanding their three-dimensional structure, a critical gap remains in determining the molecular basis for channel gating. We recently identified M2-M3 linker mutations that suggest linker flexibility has asymmetric subunit-specific correlations with channel opening. Here we use non-canonical amino acids (ncAAs) to investigate the role of main-chain H-hydrogen bonds (H-bonds) that may stabilize the M2-M3 linkers. We show that a single main-chain H-bond within the {beta}2 subunit M2-M3 linker inhibits pore opening and is required to keep the unliganded channel closed. Furthermore, breaking this H-bond during channel opening accounts for approximately one third of the activation energy derived from GABA binding. In contrast, the analogous H-bond in the 1 subunit has no effect on gating. Our observations suggest that channel opening involves state-dependent breakage/disruption of a specific main-chain H-bond within the {beta}2 subunit M2-M3 linker.

biophysics↗

bioRxiv2024

Resolving the conformational ensemble of a membrane protein by integrating small-angle scattering with AlphaFold

The function of a protein is enabled by its conformational landscape. For non-rigid proteins, a complete characterization of this landscape requires understanding the proteins structure in all functional states, the stability of these states under target conditions, and the transition pathways between them. Several strategies have recently been developed to drive the machine learning algorithm AlphaFold2 (AF) to sample multiple conformations, but it is more challenging to a priori predict what states are stabilized in particular conditions and how the transition occurs. Here, we combine AF sampling with small-angle scattering curves to obtain a weighted conformational ensemble of functional states under target environmental conditions. We apply this to the pentameric ion channel GLIC using small-angle neutron scattering (SANS) curves, and identify apparent closed and open states. Under resting conditions, we find that the best fit to experimental SANS data corresponds to a population of only closed states, while activating conditions allow for a subpopulation of open channels, matching both experiments and extensive simulation sampling using Markov state models. The predicted closed and open states closely resemble crystal structures determined under resting and activating conditions respectively, and project to predicted basins in free energy landscapes calculated from the Markov state models. Further, without using any structural information, the AF sampling also correctly captures intermediate conformations and projects onto the transition pathway resolved in the extensive sampling. This combination of machine learning algorithms and low-dimensional experimental data appears to provide an efficient way to predict not only stable conformations but also accurately sample the transition pathways several orders of magnitude faster than simulation-based sampling. Author summaryThe dynamic behavior of proteins is key to their function, including nerve signaling, enzyme catalysis, and cellular regulation. These functions rely on precise movements and shape changes that allow proteins to interact with other molecules. Understanding protein structures and their evolution at the atomic level is thus crucial for many applications such as drug development, but remains a challenging problem. High-resolution experimental techniques can determine the structural states of many proteins, but often struggle to capture less-populated states. While computational approaches can model protein dynamics, they can be expensive and are typically limited to short time scales that may not encompass the full range of biologically relevant behavior. Recently, artificial intelligence-driven tools like AlphaFold2 (AF) have emerged to predict protein structures with high accuracy. However, they usually default to predicting a single structure, and while modified workflows allow for sampling of alternative states, it can be difficult to assess their functional relevance. Here, we introduce a method that combines AlphaFold2 with small-angle scattering data to predict multiple protein states and their frequencies under specific biological conditions. This approach offers a computationally efficient alternative for integrating experimental data with computational methods, providing a new tool for studying protein dynamics.

biophysics↗

bioRxiv2024

Cryo-EM structures of {rho}1 GABA(A) receptors with antagonist and agonist drugs

The family of {rho}-type GABAA receptors includes potential therapeutic targets in several neurological conditions, and features distinctive pharmacology compared to other subtypes. Here we combine structures, recordings and simulations to characterize the binding and conformational impact of the drugs THIP (a non-opioid analgesic), CGP36742 (phosphinic acid inhibitor) and GABOB (an anticonvulsant) on a human {rho}1 GABAA receptor. We identify a distinctive binding pose of THIP in {rho}1 versus neuronal 4{beta}3{delta} GABAA receptors, offering a rationale for its inverse effects on these subtypes. CGP36742 binding is similar to the canonical {rho}-type inhibitor TPMPA, supporting a shared mechanism of action among phosphinic acid inhibitors. Binding of GABOB is similar to that of GABA, but produces a mixture of primed and desensitized states, likely underlying its weaker agonist activity. Together, these results elucidate interactions of a {rho}-type GABAA receptor with therapeutic drugs, offering mechanistic insights and a prospective basis for further pharmaceutical development.

biophysics↗

bioRxiv2024

Engineering cardiolipin binding to an artificial membrane protein

Integral membrane proteins carry out essential functions in the cell, and their activities are often modulated by specific protein-lipid interactions in the membrane. Here, we elucidate the intricate role of cardiolipin (CDL), a regulatory lipid, as a stabilizer of membrane proteins and their complexes. Using the in silico-designed model protein TMHC4_R (ROCKET) as a scaffold, we employ a combination of molecular dynamics simulations and native mass spectrometry to explore the protein features that facilitate preferential lipid interactions and mediate stabilization. We find that the spatial arrangement of positively charged residues as well as local conformational flexibility are factors that distinguish stabilizing from non-stabilizing CDL interactions. However, we also find that even in this controlled, artificial system, a clear-cut distinction between binding and stabilization is difficult to attain, revealing that overlapping lipid contacts can partially compensate for the effects of binding site mutations. Extending our insights to naturally occurring proteins, we identify a stabilizing CDL site within the E. coli rhomboid intramembrane protease GlpG and uncover its regulatory influence on enzyme substrate preference. In this work, we establish a framework for engineering functional lipid interactions, paving the way for the design of proteins with membrane-specific properties or functions.

biochemistry↗

bioRxiv2024

Vestibular modulation by stimulant derivatives in a pentameric ligand-gated ion channel

Allosteric modulation of pentameric ligand-gated ion channels (pLGICs) is critical to the action of neurotransmitters and many psychoactive drugs. However, details of their modulatory mechanisms remain unclear, especially beyond the orthosteric neurotransmitter-binding sites. The recently reported prokaryotic channel sTeLIC, a pH-gated homolog of eukaryotic receptors in the pLGIC family, is thought to be modulated by aromatic compounds via a relatively uncharacterized modulatory site in the extracellular vestibule. Here, we show that sTeLIC is sensitive to potentiation by psychostimulant derivatives. By determining new cryo-EM and X-ray structures in closed and open states, and testing the impact of targeted mutations on electrophysiological behavior, we show that several amphiphilic compounds preferentially bind a vestibular pocket in the contracted open-state extracellular domain. This work provides a detailed structure-function mechanism for allosteric potentiation via a noncanonical lig- and site, with potential conservation in eukaryotic pentameric ligand-gated ion channels.

biophysics↗

bioRxiv2024

Adaptive sampling-based structural prediction reveals opening of a GABAA receptor through the αβ interface

GABAA receptors are ligand-gated ion channels in the central nervous system with largely inhibitory function. Despite being a target for drugs including general anesthetics and benzodiazepines, experimental structures have yet to capture an open state of canonical 1{beta}2{gamma}2 GABAA receptors. Here, we use a goal-oriented adaptive sampling strategy in molecular dynamics simulations followed by Markov state modeling to capture an energetically stable putative open state of the receptor. The model conducts chloride ions with comparable conductance as in electrophysiology measurements. The channel desensitizes by narrowing at both the cytoplasmic (-2') and central (9') gates, a motion primarily mediated by transmembrane {beta} subunit interface. Consistent with previous experiments, targeted substitutions disrupting interactions at this interface slowed the open-to-desensitized transition rate. This work demonstrates the capacity of advanced simulation techniques to investigate a computationally and experimentally plausible functionally critical of a complex membrane protein, yet to be resolved by experimental methods.

biophysics↗

bioRxiv2024

An 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. To identify such interactions, here we report on 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, and observe cholesterol bound to the receptor at an outer-leaflet intersubunit site in a state-dependent manner, indicating that it can bias receptor function. Finally, using a modified perturbation-response scanning approach, we applied short atomistic simulations to identify amino-acid translations correlated with gating conformational changes. 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 heteromeric glycine receptors, including specific amino-acid contacts applicable to biophysical modeling and pharmaceutical design.

biophysics↗