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Delemotte, L.

Publications and source records attributed to Delemotte, L..

At least 19 recordsLinked to original sources

Who's driving? Common evolutionary mechanism of activation of class A GPCRs

Cells communicate with their environment by integrating signals, often chemical in nature, triggered by specific molecules bind to specific membrane-bound receptors, resulting in a downstream signaling cascade. Arguably, Gprotein-coupled receptors (GPCRs) constitute the most pharmacologically important family of such receptors, binding small molecules, peptides, lipids, and hormones with high specificity. However, despite a highly conserved fold and sequence similarity, GPCRs are still mostly studied on a case-by-case basis. Here, we infer a general, evolutionarily conserved mechanism of class A GPCR activation. By leveraging coevolution and machine learning methods applied to all class A GPCRs structures, we derive a mathematical description (a so-called collective variable - CV) of the receptors activation state which is independent of its sequence. Then, we bias molecular dynamics simulations along this CV to obtain transitions between activation states of a diverse set of class A GPCR family members. To demonstrate that our model generalizes beyond GPCRs in our training set, we obtain conformational transitions of an orphan receptor, GPR183. Finally, we show that we can model ligand effect on the receptors by converging Free Energy Surfaces of activation of the {beta}2-adrenergic receptor within this common mechanism framework. These results, to our knowledge, prove for the first time the existence of a mechanism uniting all class A GPCRs. Our approach thus facilitates direct comparisons between receptors and opens up the possibility of structural and dynamical studies of many orphan and understudied GPCRs. It also serves as a blueprint for inferring family-wide protein mechanisms.

biophysics↗

Lipid-facilitated opening of the ADAM10 sheddase revealed by enhanced sampling simulations

ADAM10 is a crucial membrane-bound metalloprotease that regulates cellular physiology by cleaving and releasing membrane-anchored proteins, including adhesion molecules and growth factor precursors, thereby modulating cell signaling, adhesion, and migration. Despite its central role, its activation mechanisms are not fully understood. Here, we model how phosphatidylserine (PS) exposure during apoptosis triggers ADAM10 activation. We confirmed that PS externalization leads to shedding of CD43 from the surface of T cells via ADAM10 activity. Intriguingly, ADAM10 activation correlated with a loss of monoclonal ADAM10 antibody binding, suggesting a PS-induced conformational change that alters epitope accessibility. To explore this lipid-mediated conformational change of ADAM10, we employed molecular dynamics (MD) simulations to map the conformational landscape of ADAM10. Our simulations revealed that in the absence of PS, ADAM10 samples predominantly closed and intermediate states. By contrast, the presence of PS destabilizes the closed conformation, thereby favoring open states. We provide a mechanistic explanation for this PS-induced conformational change which drives ADAM10 activation and loss of mAb binding through conformational change. These findings offer new insights into the lipid-mediated regulation of ADAM10 and its conformational dynamics.

biophysics↗

Mechanisms of KCNQ1 gating modulation by KCNE1/3 for cell-specific function

KCNQ1 potassium channels are essential for physiological processes such as cardiac rhythm and intestinal chloride secretion. KCNE-family subunits (KCNE1-5) associate with KCNQ1, conferring distinct properties across various tissues. KCNQ1 activation requires membrane depolarization and phosphatidylinositol 4,5-bisphosphate (PIP2) whose cellular levels are controlled by Gq-coupled GPCR activation. While modulation of KCNQ1s voltage-dependent activation by KCNE1/3 is well-characterized, their effects on PIP2-dependent gating of KCNQ1 via GPCR signaling remain less understood. Here we resolved structures of KCNQ1-KCNE1 and reassessed reported KCNQ1-KCNE3 structures with and without PIP2. We revealed that KCNQ1-KCNE1/3 complexes feature two PIP2-binding sites, with KCNE1/3 contributing to a previously overlooked, uncharacterized site involving residues critical for voltage sensor and pore domain coupling. Via this site, KCNE1 and KCNE3 distinctly modulate the PIP2-dependent gating, in addition to the voltage sensitivity, of KCNQ1. Consequently, KCNE3 converts KCNQ1 into a voltage-insensitive PIP2-gated channel governed by GPCR signaling to maintain ion homeostasis in non-excitable cells. KCNE1, by significantly enhancing KCNQ1s PIP2 affinity and resistance to GPCR regulation, forms predominantly voltage-gated channels with KCNQ1 for conducting the slow-delayed rectifier current in excitable cardiac cells. Our study highlights how KCNE1/3 modulates KCNQ1 gating in different cellular contexts, providing insights for tissue-specifically targeting multi-functional channels.

biochemistry↗

Revealing molecular determinants of ligand efficacy and affinity at the D2 dopamine receptor through molecular dynamics simulations

G protein-coupled receptors (GPCRs) control numerous physiological processes and are important therapeutic targets. Despite major research efforts, rational design of drugs that stimulate GPCR signaling is challenging because the molecular basis of activation remains poorly understood. Here, a combination of molecular dynamics simulations and pharmacological assays was used to study the activation mechanism of the D2 dopamine receptor (D2R), a major drug target for central nervous system diseases. Enhanced sampling simulations were performed to identify the key conformational changes involved in D2R activation by dopamine, and a computational platform for ligand profiling based on free energy calculations was developed. Simulations and experimental characterization of a series of dopamine derivatives showed that free energy calculations can predict the effect of small chemical modifications on ligand affinity and efficacy. Furthermore, simulations of D2 dopamine and {beta}2 adrenergic receptor activation revealed that ligand-induced activation of these GPCRs is driven by different molecular mechanisms despite recognizing chemically similar catecholamine agonists. Whereas dopamine interactions with the sixth transmembrane helix primarily drive activation of the D2R, hydrogen bonding with the fifth helix is the key interaction for activation of the {beta}2 adrenergic receptor. Our results highlight the complexity of GPCR activation and illustrate how molecular simulations can provide mechanistic insight and quantitative predictions of ligand activity, enabling structure-based drug design. Significance statementG protein-coupled receptors (GPCRs) on the cell surface recognize ligands such as hormones and neurotransmitters. The binding of the ligand to the receptor leads to the activation of intracellular signaling pathways, a communication system that controls essential physiological functions. GPCRs are therefore important therapeutic targets, and many drugs exert effects by modulating their activity. Here, we use molecular simulations to study the activation mechanism of a dopamine receptor, which is implicated in neurodegenerative and neuropsychiatric disorders. We elucidate the mechanism of receptor activation and develop strategies to predict ligand affinity and efficacy. We also identify differsences in the activation mechanisms of dopamine and adrenergic receptors. These findings provide novel insights into receptor activation and can accelerate the drug discovery process.

biophysics↗

Computational design of constitutively active mutants of Dopamine D2 receptor inspired by ligand-independent activation mechanisms

G protein-coupled receptors (GPCRs) can signal in the absence of agonists through constitutive activity. This activity can be enhanced by mutations, resulting in receptors known as constitutively active mutants (CAMs). Such receptors can be implicated in various physiological and pathophysiological conditions, and also offer significant therapeutic potential. However, the molecular basis of their constitutive activity remains unknown. To investigate how CAMs affect receptor activation, we employed enhanced sampling simulations to study the dopamine D2 receptor (D2R), a key target in central nervous system therapies. Free energy landscape analyses revealed that CAMs promote a conformational shift favoring an active state similar to the agonist-bound receptor. To then identify novel CAMs, we developed a comprehensive strategy combining structural comparison, in-silico residue scanning, and free energy calculations, validated by luminescence-complementation-based assays. Applied to D2R, this approach uncovered a new single-point CAM, D2R-I481.46W, which was functionally validated. Further investigation revealed that this mutation activates allosteric communication pathways primarily involving transmembrane helix 5, particularly Ser1945.43, underscoring its role in transmitting activation signals to the intracellular domain. These findings deepen our understanding of constitutive GPCR activity and demonstrate the utility of this framework for identifying CAMs as ligand-independent models for structural, cellular, and physiological studies.

biophysics↗

Structural diversity of Arc oligomers within the excitatory synapse

The Activity-Regulated Cytoskeleton-Associated protein (Arc), is pivotal to mediate plasticity responses in neuronal cells. In vitro studies suggest its ability to form high- and low-order oligomers, which are involved in neuronal trafficking. Despite its important functions, no direct observation of Arc oligomers in cells has been presented due to its highly regulated spatiotemporal expression, the small size of the structures, the lack of appropriate labelling strategies and the background associated to free diffusing cytosolic proteins. Here, we apply super resolution microscopy to observe Arc oligomeric states in cellular environment with focus on the excitatory synapse. In cells, we provide the first evidence of Arc high-order oligomers; we uncovered intermolecular interactions of Arc, its tendency to form liquid condensates and interaction with lipid bilayers. Arc high-order oligomers affect AMPA receptor surface levels. Together, our observations suggest a model by which Arc oligomerization mediates plasma membrane negative curvature favoring AMPA receptors endocytosis.

neuroscience↗

PI-(3,5)P2-mediated oligomerization of the endosomal sodium/proton exchanger NHE9

Na+/H+ exchangers are found in all cells to regulate intracellular pH, sodium levels and cell volume. Na+/H+ exchangers are physiological homodimers that operate by an elevator alternating-access mechanism. While the structure of the core ion translocation domain is fairly conserved, the scaffold domain and oligomerization show larger structural variation. The Na+/H+ exchanger NhaA from E. coli has a weak oligomerization interface mediated by a {beta}-hairpin domain and homodimerization was shown to be dependent of the lipid cardiolipin. Organellar Na+/H+ exchangers NHE6, NHE7 and NHE9 are likewise predicted to contain {beta}-hairpin domains and a recent analysis of horse NHE9 indicated that the lipid PIP2 binds at the dimerization interface. Despite predicted lipid-mediated oligomerization, their structural validation has been lacking. Here, we report cryo-EM structures of E. coli NhaA and horse NHE9 with the coordination of cardiolipin and PI(3,5)P2 binding at the dimer interface, respectively. Cell based assays confirms that NHE9 is inactive at the plasma membrane and thermal-shift assays, solid-supported membrane (SSM) electrophysiology and MD simulations, corroborates that NHE9 specifically binds the endosomal PI(3,5)P2 lipid, which stabilizes the homodimer and enhances activity. Taken together, we propose specific lipids regulate Na+/H+ exchange activity by stabilizing oligomerization and stimulating Na+ binding under lipid-specific cues.

biochemistry↗

Coevolution-driven method for efficiently simulating conformational changes in proteins reveals molecular details of ligand effects in the beta2AR receptor

With the advent of AI-powered structure prediction, the scientific community is inching ever closer to solving protein folding. An unresolved enigma, however, is to accurately, reliably and deterministically predict alternative conformational states that are crucial for the function of e.g. transporters, receptors or ion channels where conformational cycling is innately coupled to protein function. Accurately discovering and exploring all conformational states of membrane proteins has been challenging due to the need to retain atomistic detail while enhancing the sampling along interesting degrees of freedom. The challenges include but are not limited to finding which degrees of freedom are relevant, how to accelerate the sampling along them, and then quantifying the populations of each micro- and macrostate. In this work, we present a methodology that finds the relevant degrees of freedom by combining evolution and physics through machine learning and apply it to the {beta}2 adrenergic receptor conformational sampling. In addition to predicting new conformations that are beyond the training set, we have computed free energy surfaces associated with the proteins conformational landscape. We then show that the methodology is able to quantitatively predict the effect of an array of ligands on the {beta}2 adrenergic receptor activation, and that the full conformational landscape, including states related to biased signaling, is discovered using this procedure. Lastly, we also stake out the structural determinants of activation and inactivation pathway signaling through different ligands.

biophysics↗

The full spectrum of OCT1 (SLC22A1) mutations bridges transporter biophysics to drug pharmacogenomics

Membrane transporters play a fundamental role in the tissue distribution of endogenous compounds and xenobiotics and are major determinants of efficacy and side effects profiles. Polymorphisms within these drug transporters result in inter-individual variation in drug response, with some patients not responding to the recommended dosage of drug whereas others experience catastrophic side effects. For example, variants within the major hepatic Human organic cation transporter OCT1 (SLC22A1) can change endogenous organic cations and many prescription drug levels. To understand how variants mechanistically impact drug uptake, we systematically study how all known and possible single missense and single amino acid deletion variants impact expression and substrate uptake of OCT1. We find that human variants primarily disrupt function via folding rather than substrate uptake. Our study revealed that the major determinants of folding reside in the first 300 amino acids, including the first 6 transmembrane domains and the extracellular domain (ECD) with a stabilizing and highly conserved stabilizing helical motif making key interactions between the ECD and transmembrane domains. Using the functional data combined with computational approaches, we determine and validate a structure-function model of OCT1s conformational ensemble without experimental structures. Using this model and molecular dynamic simulations of key mutants, we determine biophysical mechanisms for how specific human variants alter transport phenotypes. We identify differences in frequencies of reduced function alleles across populations with East Asians vs European populations having the lowest and highest frequency of reduced function variants, respectively. Mining human population databases reveals that reduced function alleles of OCT1 identified in this study associate significantly with high LDL cholesterol levels. Our general approach broadly applied could transform the landscape of precision medicine by producing a mechanistic basis for understanding the effects of human mutations on disease and drug response.

biophysics↗

MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD [fi]les in generalist data repositories, constituting the dark matter of MD -- data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 [fi]les and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on [fi]les produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identi[fi]ed systems with speci[fi]c molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.

bioinformatics↗

Free energy landscapes of KcsA inactivation

The bacterial ion channel KcsA has become a useful model of complex K+-ion channels thanks to its single pore domain structure whose sequence shares many similarities with eukaryotic channels. Like many physiologically-relevant ion channels, KcsA inactivates after prolonged exposure to stimuli (in this case, a lowered pH). The inactivation mechanism has been heavily investigated, using structural, functional and simulations methods, but the molecular basis underlying the energetics of the process remains actively debated. In this work, we use the "string method with swarms of trajectories" enhanced sampling technique to characterize the free energy landscape lining the KcsA inactivation process. After channel opening following a pH drop, KcsA presents metastable open states leading to an inactivated state. The final inactivation step consists of a constriction of the selectivty filter and entry of three water molecules into binding sites behind each selectivity filter subunit. Based our simulations, we propose a key role for residue L81 in opening a gateway for water molecules to enter their buried sites, rather than for Y82 which has previously been suggested to act as a lid. In addition, since we found the energetically favored inactivation mechanism to be dependent on the force field, our results also address the importance of parameter choice for this type of mechanism. In particular, inactivation involves passing through the fully-open state only when using the AMBER force field. In contrast, using CHARMM, selectivity filter constriction proceeds directly from the partially open state. Finally, our simulations suggest that removing the co-purifying lipids stabilizes the partially open states, rationalizing their importance for the proper inactivation of the channel.

biophysics↗

Modulation of pore opening of Eukaryotic sodium channels by π-helices in S6

Voltage-gated sodium channels are heterotetrameric sodium selective ion channels that play a central role in electrical signaling in excitable cells. With recent advances in structural biology, structures of eukaryotic sodium channels have been captured in several distinct conformations corresponding to different functional states. The secondary structure of the pore lining S6 helices of subunit DI, DII, and DIV has been captured with both short {pi}-helix stretches and in fully -helical conformations. The relevance of these secondary structure elements for pore gating is not yet understood. Here, we propose that a {pi} helix in at least DI-S6, DIII-S6, and DIV-S6 results in a fully conductive state. On the other hand, the absence of {pi}-helix in either DI-S6 or DIV-S6 yields a sub-conductance state, and its absence from both DI-S6 and DIV-S6 yields a non-conducting state. This work highlights the impact of the presence of a {pi}-helix in the different S6 helices of an expanded pore on pore conductance, thus opening new doors towards reconstructing the entire conformational landscape along the functional cycle of Nav Channels and paving the way to the design of state-dependent modulators. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/534196v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1690f87org.highwire.dtl.DTLVardef@7a97faorg.highwire.dtl.DTLVardef@8facb1org.highwire.dtl.DTLVardef@92b36c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

An intracellular hydrophobic nexus is critical for slow deactivation in hERG channels

Slow deactivation is a critical biophysical and physiological property of voltage-gated K+ channels encoded by the human Ether-a-go-go-Related Gene (hERG). hERG channel deactivation is modulated by interactions between intracellular N-terminal Per-Arnt-Sim (PAS) and C-terminal cyclic nucleotide-binding homology (CNBh) domains. The PAS domain is multipartite, comprising a globular domain (residues 26-136) and an N-terminal PAS-cap that is further subdivided into an initial unstructured segment (residues 1-12) and an amphipathic -helical region (residues 13-25). Disruption of interactions within the PAS-CNBhD complex accelerates deactivation kinetics and impairs the slow repolarization of the cardiac action potential. Similarly, deletion of the PAS-cap unstructured segment, modeled as a "foot-in-the-door," accelerates channel closing. Here, we tested the hypothesis that a three-dimensional hydrophobic nexus, comprising residues in the PAS-cap -helix, the globular PAS, and CNBh domains, plays a crucial role in slow deactivation. Utilizing structure-directed mutagenesis, electrophysiology, and molecular dynamics simulations, we provide evidence that altering hydrophobicity at this interface accelerates deactivation kinetics and causes a rearrangement in the network of residues comprising the hydrophobic nexus. Moreover, the PAS-cap unstructured segment disengages from the gating machinery. We propose that the nexus hydrophobicity positions the PAS-cap -helix and promotes engagement of the upstream PAS-cap unstructured segment with the gating machinery, resulting in slow channel closing. Interestingly, several long QT syndrome disease mutations lie at this interface, underscoring the importance of the hydrophobic nexus and the novel role of the PAS-cap -helix in hERG gating.

biophysics↗

Reconstructing the transport cycle in the sugar porter superfamily using coevolution-powered machine learning

Sugar porters represent the largest group of secondary-active transporters. Some members, such as the glucose (GLUT) transporters, are well-known for their role in maintaining blood glucose homeostasis in mammals, with their expression upregulated in many types of cancers. Because only a few sugar porter structures have been determined, mechanistic models have been constructed by piecing together structural states of distantly related proteins. Current GLUT transport models are predominantly descriptive and oversimplified. Here, we have combined coevolution analysis and comparative modeling, to predict structures of the entire sugar porter superfamily in each state of the transport cycle. We have analysed the state-specific contacts inferred from coevolving residue pairs and shown how this information can be used to rapidly generate free-energy landscapes consistent with experimental estimates, as illustrated here for the mammalian fructose transporter GLUT5. By comparing many different sugar porter models and scrutinizing their sequence, we have been able to define the molecular determinants of the transport cycle, which are conserved throughout the sugar porter superfamily. We have also been able to highlight differences leading to the emergence of proton-coupling, validating, and extending the previously proposed latch mechanism. Our computational approach is transferable to any transporter, and to other protein families in general.

biophysics↗

An α-π transition in S6 shapes the conformational cycle of the bacterial sodium channel NavAb

Voltage gated sodium channels play an important role in electrical signaling in excitable cells. In response to changes in membrane potential, they cycle between nonconducting and conducting conformations. With recent advances in structural biology, structures of sodium channels have been captured in several distinct conformations, thought to represent different functional states. However, it has been difficult to capture the intrinsically transient open state. We recently showed that a proposed open state of the bacterial sodium channel NavMs was not conductive, and that a conformational change involving a transition to a{pi} helix in the pore-lining S6 helix converted this structure into a conducting state. However, the relevance of this structural feature in other sodium channels, and its implications for the broader gating cycle, remained unclear. Here, we propose a comparable open state of another class of bacterial channel from Aliarcobacter butzleri (NavAb), with characteristic pore hydration, ion permeation and drug binding properties. Furthermore, we show that a{pi} -helix transition can lead to pore opening, and that such a conformational change blocks fenestrations in the inner helix bundle. We also discover that a region in the C-terminal domain can undergo a disordering transition proposed to be important for pore opening. These results support a role for a{pi} -helix transition in the opening of NavAb, enabling new proposals for the structural annotation and drug modulation mechanisms in this important model sodium channel.

biophysics↗

Determinants of sugar-induced influx in the mammalian fructose transporter GLUT5

In mammals, glucose transporters (GLUT) control organism-wide blood glucose homeostasis. In human, this is accomplished by fourteen different GLUT isoforms, that transport glucose and other monosaccharides with varying substrate preferences and kinetics. Nevertheless, there is little difference between the sugar-coordinating residues in the GLUT proteins and even the malarial plasmodium falciparum transporter PfHT1, which is uniquely able to transport a wide range of different sugars. PfHT1 was captured in an intermediate "occluded" state, revealing how the extracellular gating helix TM7b has moved to break and occlude the sugar-binding site. Sequence difference and kinetics indicated that the TM7b gating helix dynamics and interactions likely evolved to enable substrate promiscuity in PfHT1, rather than the sugar-binding site itself. It was unclear, however, if the TM7b structural transitions observed in PfHT1 would be similar in the other GLUT proteins. Here, using enhanced sampling molecular dynamics simulations, we show that the fructose transporter GLUT5 spontaneously transitions through an occluded state that closely resembles PfHT1. The coordination of fructose lowers the energetic barriers between the outward and inward-facing states, and the observed binding mode for fructose is consistent with biochemical analysis. Rather than a substrate binding site that achieves strict specificity by having a high-affinity for the substrate, we conclude GLUT proteins have allosterically coupled sugar binding with an extracellular gate that forms the high-affinity transition-state instead. This substrate-coupling pathway presumably enables the catalysis of fast sugar flux at physiological relevant blood-glucose concentrations.

biophysics↗

Markov State Modelling Reveals Heterogeneous Drug-Inhibition Mechanism of Calmodulin

Calmodulin (CaM) is a calcium sensor which binds and regulates a wide range of target-proteins. This implicitly enables the concentration of calcium to influence many downstream physiological responses, including muscle contraction, learning and depression. The antipsychotic drug trifluoperazine (TFP) is a known CaM inhibitor. By binding to various sites, TFP prevents CaM from associating to target-proteins. However, the molecular and state-dependent mechanisms behind CaM inhibition by drugs such as TFP are largely unknown. Here, we build a Markov state model (MSM) from adaptively sampled molecular dynamics simulations and reveal the structural and dynamical features behind the inhibitory mechanism of TFP-binding to the C-terminal domain of CaM. We specifically identify three major TFP binding-modes from the MSM macrostates, and distinguish their effect on CaM conformation by using a systematic analysis protocol based on biophysical descriptors and tools from machine learning. The results show that depending on the binding orientation, TFP effectively stabilizes features of the calcium-unbound CaM, either affecting the CaM hydrophobic binding pocket, the calcium binding sites or the secondary structure content in the bound domain. The conclusions drawn from this work may in the future serve to formulate a complete model of pharmacological modulation of CaM, which furthers our understanding of how these drugs affect signaling pathways as well as associated diseases. Author summaryCalmodulin (CaM) is a calcium-sensing protein which makes other proteins dependent on the surrounding calcium concentration by binding to these proteins. Such protein-protein interactions with CaM are vital for calcium to control many physiological pathways within the cell. The antipsychotic drug trifluoperazine (TFP) inhibits CaMs ability to bind and regulate other proteins. Here, we use molecular dynamics simulations together with Markov state modeling and machine learning to understand the structural and dynamical features by which TFP bound to the one domain of CaM prevents association to other proteins. We find that TFP encourages CaM to adopt a conformation that is like the one stabilized in absence of calcium: depending on the binding orientation of TFP, the drug indeed either affects the CaM hydrophobic binding pocket, the calcium binding sites or the secondary structure content in the domain. Understanding TFP binding is a first step towards designing better drugs targeting CaM.

biophysics↗

Interplay between VSD, pore and membrane lipids in electromechanical coupling in HCN channels

Hyperpolarized-activated and Cyclic Nucleotide-gated (HCN) channels are the only members of the voltage-gated ion channel superfamily in mammals that open upon hyperpolarization, conferring them pacemaker properties that are instrumental for rhythmic firing of cardiac and neuronal cells. Activation of their voltage-sensor domains (VSD) upon hyperpolarization occurs through a downward movement of the S4 helix bearing the gating charges, which triggers a break in the alpha-helical hydrogen bonding pattern at the level of a conserved Serine residue. Previous structural and molecular simulation studies had however failed to capture pore opening that should be triggered by VSD activation, presumably because of a low VSD/pore electromechanical coupling efficiency and the limited timescales accessible to such techniques. Here, we have used advanced modeling strategies, including enhanced sampling molecular dynamics simulations exploiting comparisons between non-domain swapped voltage-gated ion channel structures trapped in closed and open states to trigger pore gating and characterize electromechanical coupling in HCN1. We propose that the coupling mechanism involves the reorganization of the interfaces between the VSD helices, in particular S4, and the pore-forming helices S5 and S6, subtly shifting the balance between hydrophobic and hydrophilic interactions in a "domino effect" during activation and gating in this region. Remarkably, our simulations reveal state-dependent occupancy of lipid molecules at this emergent coupling interface, suggesting a key role of lipids in hyperpolarization-dependent gating. Our model provides a rationale for previous observations and a possible mechanism for regulation of HCN channels by the lipidic components of the membrane.

biophysics↗