Atomistic mechanisms of the regulation of small-conductance Ca2+-activated K+ channel (SK2) by PIP2.

Small-conductance Ca2+-activated K+ channels (SK, KCa2) are gated solely by intracellular microdomain Ca2+. The channel has emerged as a therapeutic target for cardiac arrhythmias. Calmodulin (CaM) interacts with the CaM binding domain (CaMBD) of the SK channels, serving as the obligatory Ca2+ sensor to gate the channels. In heterologous expression systems, phosphatidylinositol 4,5-bisphosphate (PIP2) coordinates with CaM in regulating SK channels. However, the roles and mechanisms of PIP2 in regulating SK channels in cardiomyocytes remain unknown. Here, optogenetics, magnetic nanoparticles, combined with Rosetta structural modeling, and molecular dynamics (MD) simulations revealed the atomistic mechanisms of how PIP2 works in concert with Ca2+-CaM in the SK channel activation. Our computational study affords evidence for the critical role of the amino acid residue R395 in the S6 transmembrane segment, which is localized in propinquity to the intracellular hydrophobic gate. This residue forms a salt bridge with residue E398 in the S6 transmembrane segment from the adjacent subunit. Both R395 and E398 are conserved in all known isoforms of SK channels. Our findings suggest that the binding of PIP2 to R395 residue disrupts the R395:E398 salt bridge, increasing the flexibility of the transmembrane segment S6 and the activation of the channel. Importantly, our findings serve as a platform for testing of structural-based drug designs for therapeutic inhibitors and activators of the SK channel family. The study is timely since inhibitors of SK channels are currently in clinical trials to treat atrial arrhythmias.

Elucidation of a dynamic interplay between a beta-2 adrenergic receptor, its agonist, and stimulatory G protein.

G protein-coupled receptors (GPCRs) represent the largest group of membrane receptors for transmembrane signal transduction. Ligand-induced activation of GPCRs triggers G protein activation followed by various signaling cascades. Understanding the structural and energetic determinants of ligand binding to GPCRs and GPCRs to G proteins is crucial to the design of pharmacological treatments targeting specific conformations of these proteins to precisely control their signaling properties. In this study, we focused on interactions of a prototypical GPCR, beta-2 adrenergic receptor (ß2AR), with its endogenous agonist, norepinephrine (NE), and the stimulatory G protein (Gs). Using molecular dynamics (MD) simulations, we demonstrated the stabilization of cationic NE, NE(+), binding to ß2AR by Gs protein recruitment, in line with experimental observations. We also captured the partial dissociation of the ligand from ß2AR and the conformational interconversions of Gs between closed and open conformations in the NE(+)-ß2AR-Gs ternary complex while it is still bound to the receptor. The variation of NE(+) binding poses was found to alter Gs α subunit (Gsα) conformational transitions. Our simulations showed that the interdomain movement and the stacking of Gsα α1 and α5 helices are significant for increasing the distance between the Gsα and ß2AR, which may indicate a partial dissociation of Gsα The distance increase commences when Gsα is predominantly in an open state and can be triggered by the intracellular loop 3 (ICL3) of ß2AR interacting with Gsα, causing conformational changes of the α5 helix. Our results help explain molecular mechanisms of ligand and GPCR-mediated modulation of G protein activation.

Rearrangement of a unique Kv1.3 selectivity filter conformation upon binding of a drug.

We report two structures of the human voltage-gated potassium channel (Kv) Kv1.3 in immune cells alone (apo-Kv1.3) and bound to an immunomodulatory drug called dalazatide (dalazatide-Kv1.3). Both the apo-Kv1.3 and dalazatide-Kv1.3 structures are in an activated state based on their depolarized voltage sensor and open inner gate. In apo-Kv1.3, the aromatic residue in the signature sequence (Y447) adopts a position that diverges 11 Å from other K+ channels. The outer pore is significantly rearranged, causing widening of the selectivity filter and perturbation of ion binding within the filter. This conformation is stabilized by a network of intrasubunit hydrogen bonds. In dalazatide-Kv1.3, binding of dalazatide to the channel's outer vestibule narrows the selectivity filter, Y447 occupies a position seen in other K+ channels, and this conformation is stabilized by a network of intersubunit hydrogen bonds. These remarkable rearrangements in the selectivity filter underlie Kv1.3's transition into the drug-blocked state.

A multiscale predictive digital twin for neurocardiac modulation.

Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the ß-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.

Selectivity filter modalities and rapid inactivation of the hERG1 channel.

The human ether-á-go-go-related gene (hERG1) channel conducts small outward K+ currents that are critical for cardiomyocyte membrane repolarization. The gain-of-function mutation N629D at the outer mouth of the selectivity filter (SF) disrupts inactivation and K+-selective transport in hERG1, leading to arrhythmogenic phenotypes associated with long-QT syndrome. Here, we combined computational electrophysiology with Markov state model analysis to investigate how SF-level gating modalities control selective cation transport in wild-type (WT) and mutant (N629D) hERG1 variants. Starting from the recently reported cryogenic electron microscopy (cryo-EM) open-state channel structure, multiple microseconds-long molecular-dynamics (MD) trajectories were generated using different cation configurations at the filter, voltages, electrolyte concentrations, and force-field parameters. Most of the K+ permeation events observed in hERG1-WT simulations occurred at microsecond timescales, influenced by the spontaneous dehydration/rehydration dynamics at the filter. The SF region displayed conductive, constricted, occluded, and dilated states, in qualitative agreement with the well-documented flickering conductance of hERG1. In line with mutagenesis studies, these gating modalities resulted from dynamic interaction networks involving residues from the SF, outer-mouth vestibule, P-helices, and S5-P segments. We found that N629D mutation significantly stabilizes the SF in a state that is permeable to both K+ and Na+, which is reminiscent of the SF in the nonselective bacterial NaK channel. Increasing the external K+ concentration induced "WT-like" SF dynamics in N629D, in qualitative agreement with the recovery of flickering currents in experiments. Overall, our findings provide an understanding of the molecular mechanisms controlling selective transport in K+ channels with a nonconventional SF sequence.

A Computational Pipeline to Predict Cardiotoxicity: From the Atom to the Rhythm.

RATIONALE: Drug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation is an accepted surrogate marker for arrhythmia. But QT interval is too sensitive a marker and not selective, resulting in many useful drugs eliminated in drug discovery. OBJECTIVE: To predict the impact of a drug from the drug chemistry on the cardiac rhythm. METHODS AND RESULTS: In a new linkage, we connected atomistic scale information to protein, cell, and tissue scales by predicting drug-binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel. Model components were integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data were used for model framework validation and showed excellent agreement, demonstrating feasibility of a new approach for cardiotoxicity prediction. CONCLUSIONS: We present a multiscale model framework to predict electrotoxicity in the heart from the atom to the rhythm. Novel mechanistic insights emerged at all scales of the system, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundamental cellular and tissue-level arrhythmia mechanisms. Applications of machine learning indicate necessary and sufficient parameters that predict arrhythmia vulnerability. We expect that the model framework may be expanded to make an impact in drug discovery, drug safety screening for a variety of compounds and targets, and in a variety of regulatory processes.

Structural basis for antiarrhythmic drug interactions with the human cardiac sodium channel.

The human voltage-gated sodium channel, hNaV1.5, is responsible for the rapid upstroke of the cardiac action potential and is target for antiarrhythmic therapy. Despite the clinical relevance of hNaV1.5-targeting drugs, structure-based molecular mechanisms of promising or problematic drugs have not been investigated at atomic scale to inform drug design. Here, we used Rosetta structural modeling and docking as well as molecular dynamics simulations to study the interactions of antiarrhythmic and local anesthetic drugs with hNaV1.5. These calculations revealed several key drug binding sites formed within the pore lumen that can simultaneously accommodate up to two drug molecules. Molecular dynamics simulations identified a hydrophilic access pathway through the intracellular gate and a hydrophobic access pathway through a fenestration between DIII and DIV. Our results advance the understanding of molecular mechanisms of antiarrhythmic and local anesthetic drug interactions with hNaV1.5 and will be useful for rational design of novel therapeutics.

Molecular determinants of pro-arrhythmia proclivity of d- and l-sotalol via a multi-scale modeling pipeline.

Drug isomers may differ in their proarrhythmia risk. An interesting example is the drug sotalol, an antiarrhythmic drug comprising d- and l- enantiomers that both block the hERG cardiac potassium channel and confer differing degrees of proarrhythmic risk. We developed a multi-scale in silico pipeline focusing on hERG channel - drug interactions and used it to probe and predict the mechanisms of pro-arrhythmia risks of the two enantiomers of sotalol. Molecular dynamics (MD) simulations predicted comparable hERG channel binding affinities for d- and l-sotalol, which were validated with electrophysiology experiments. MD derived thermodynamic and kinetic parameters were used to build multi-scale functional computational models of cardiac electrophysiology at the cell and tissue scales. Functional models were used to predict inactivated state binding affinities to recapitulate electrocardiogram (ECG) QT interval prolongation observed in clinical data. Our study demonstrates how modeling and simulation can be applied to predict drug effects from the atom to the rhythm for dl-sotalol and also increased proarrhythmia proclivity of d- vs. l-sotalol when accounting for stereospecific beta-adrenergic receptor blocking.

Atomistic Simulations of Membrane Ion Channel Conduction, Gating, and Modulation.

Membrane ion channels are the fundamental electrical components in the nervous system. Recent developments in X-ray crystallography and cryo-EM microscopy have revealed what these proteins look like in atomic detail but do not tell us how they function. Molecular dynamics simulations have progressed to the point that we can now simulate realistic molecular assemblies to produce quantitative calculations of the thermodynamic and kinetic quantities that control function. In this review, we summarize the state of atomistic simulation methods for ion channels to understand their conduction, activation, and drug modulation mechanisms. We are at a crossroads in atomistic simulation, where long time scale observation can provide unbiased exploration of mechanisms, supplemented by biased free energy methodologies. We illustrate the use of these approaches to describe ion conduction and selectivity in voltage-gated sodium and acid-sensing ion channels. Studies of channel gating present a significant challenge, as activation occurs on longer time scales. Enhanced sampling approaches can ensure convergence on minimum free energy pathways for activation, as illustrated here for pentameric ligand-gated ion channels that are principal to nervous system function and the actions of general anesthetics. We also examine recent studies of local anesthetic and antiepileptic drug binding to a sodium channel, revealing sites and pathways that may offer new targets for drug development. Modern simulations thus offer a range of molecular-level insights into ion channel function and modulation as a learning platform for mechanistic discovery and drug development.

Exploring the free-energy landscape of GPCR activation.

G-protein-coupled receptors (GPCRs) are a large group of membrane-bound receptor proteins that are involved in a plethora of diverse processes (e.g., vision, hormone response). In mammals, and particularly in humans, GPCRs are involved in many signal transduction pathways and, as such, are heavily studied for their immense pharmaceutical potential. Indeed, a large fraction of drugs target various GPCRs, and drug-development is often aimed at GPCRs. Therefore, understanding the activation of GPCRs is a challenge of major importance both from fundamental and practical considerations. And yet, despite the remarkable progress in structural understanding, we still do not have a translation of the structural information to an energy-based picture. Here we use coarse-grained (CG) modeling to chart the free-energy landscape of the activation process of the ß-2 adrenergic receptor (ß2AR) as a representative GPCR. The landscape provides the needed tool for analyzing the processes that lead to activation of the receptor upon binding of the ligand (adrenaline) while limiting constitutive activation. Our results pave the way to better understand the biological mechanisms of action of the ß2AR and GPCRs, from a physical chemistry point of view rather than simply by observing the receptor's behavior physiologically.

A demonstration of modularity, reuse, reproducibility, portability and scalability for modeling and simulation of cardiac electrophysiology using Kepler Workflows.

Multi-scale computational modeling is a major branch of computational biology as evidenced by the US federal interagency Multi-Scale Modeling Consortium and major international projects. It invariably involves specific and detailed sequences of data analysis and simulation, often with multiple tools and datasets, and the community recognizes improved modularity, reuse, reproducibility, portability and scalability as critical unmet needs in this area. Scientific workflows are a well-recognized strategy for addressing these needs in scientific computing. While there are good examples if the use of scientific workflows in bioinformatics, medical informatics, biomedical imaging and data analysis, there are fewer examples in multi-scale computational modeling in general and cardiac electrophysiology in particular. Cardiac electrophysiology simulation is a mature area of multi-scale computational biology that serves as an excellent use case for developing and testing new scientific workflows. In this article, we develop, describe and test a computational workflow that serves as a proof of concept of a platform for the robust integration and implementation of a reusable and reproducible multi-scale cardiac cell and tissue model that is expandable, modular and portable. The workflow described leverages Python and Kepler-Python actor for plotting and pre/post-processing. During all stages of the workflow design, we rely on freely available open-source tools, to make our workflow freely usable by scientists.

Challenges and advances in atomistic simulations of potassium and sodium ion channel gating and permeation.

Ion channels are implicated in many essential physiological events such as electrical signal propagation and cellular communication. The advent of K+ and Na+ ion channel structure determination has facilitated numerous investigations of molecular determinants of their behaviour. At the same time, rapid development of computer hardware and molecular simulation methodologies has made computational studies of large biological molecules in all-atom representation tractable. The concurrent evolution of experimental structural biology with biomolecular computer modelling has yielded mechanistic details of fundamental processes unavailable through experiments alone, such as ion conduction and ion channel gating. This review is a short survey of the atomistic computational investigations of K+ and Na+ ion channels, focusing on KcsA and several voltage-gated channels from the KV and NaV families, which have garnered many successes and engendered several long-standing controversies regarding the nature of their structure-function relationship. We review the latest advancements and challenges facing the field of molecular modelling and simulation regarding the structural and energetic determinants of ion channel function and their agreement with experimental observations.

A multiscale computational modelling approach predicts mechanisms of female sex risk in the setting of arousal-induced arrhythmias.

KEY POINTS: This study represents a first step toward predicting mechanisms of sex-based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening. We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias. Using the recently solved cryo-EM structure for the Eag-family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S). Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore. ABSTRACT: Female sex is a risk factor for inherited and acquired long-QT associated torsade de pointes (TdP) arrhythmias, and sympathetic discharge is a major factor in triggering TdP in female long-QT syndrome patients. We used a combined experimental and computational approach to predict 'the perfect storm' of hormone concentration, IKr block and sympathetic stimulation that induces arrhythmia in females with inherited and acquired long-QT. More specifically, we developed mathematical models of acquired and inherited long-QT syndrome in male and female ventricular human myocytes by combining effects of a hormone and a hERG blocker, dofetilide, or hERG mutations. These 'male' and 'female' model myocytes and tissues then were used to predict how various sex-based differences underlie arrhythmia risk in the setting of acute sympathetic nervous system discharge. The model predicted increased risk for arrhythmia in females when acute sympathetic nervous system discharge was applied in the settings of both inherited and acquired long-QT syndrome. Females were predicted to have protection from arrhythmia induction when progesterone is high. Males were protected by the presence of testosterone. Structural modelling points towards two plausible and distinct mechanisms of oestrogen action enhancing torsadogenic effects: oestradiol interaction with hERG mutations in the pore loop containing G604 or with common TdP-related blockers in the intra-cavity binding site. Our study presents findings that constitute the first evidence linking structure to function mechanisms underlying female dominance of arousal-induced arrhythmias.

Ion conduction and conformational flexibility of a bacterial voltage-gated sodium channel.

Voltage-gated Na(+) channels play an essential role in electrical signaling in the nervous system and are key pharmacological targets for a range of disorders. The recent solution of X-ray structures for the bacterial channel NavAb has provided an opportunity to study functional mechanisms at the atomic level. This channel's selectivity filter exhibits an EEEE ring sequence, characteristic of mammalian Ca(2+), not Na(+), channels. This raises the fundamentally important question: just what makes a Na(+) channel conduct Na(+) ions? Here we explore ion permeation on multimicrosecond timescales using the purpose-built Anton supercomputer. We isolate the likely protonation states of the EEEE ring and observe a striking flexibility of the filter that demonstrates the necessity for extended simulations to study conduction in this channel. We construct free energy maps to reveal complex multi-ion conduction via knock-on and "pass-by" mechanisms, involving concerted ion and glutamate side chain movements. Simulations in mixed ionic solutions reveal relative energetics for Na(+), K(+), and Ca(2+) within the pore that are consistent with the modest selectivity seen experimentally. We have observed conformational changes in the pore domain leading to asymmetrical collapses of the activation gate, similar to proposed inactivated structures of NavAb, with helix bending involving conserved residues that are critical for slow inactivation. These structural changes are shown to regulate access to fenestrations suggested to be pathways for lipophilic drugs and provide deeper insight into the molecular mechanisms connecting drug activity and slow inactivation.

Local anesthetic and antiepileptic drug access and binding to a bacterial voltage-gated sodium channel.

Voltage-gated sodium (Nav) channels are important targets in the treatment of a range of pathologies. Bacterial channels, for which crystal structures have been solved, exhibit modulation by local anesthetic and anti-epileptic agents, allowing molecular-level investigations into sodium channel-drug interactions. These structures reveal no basis for the "hinged lid"-based fast inactivation, seen in eukaryotic Nav channels. Thus, they enable examination of potential mechanisms of use- or state-dependent drug action based on activation gating, or slower pore-based inactivation processes. Multimicrosecond simulations of NavAb reveal high-affinity binding of benzocaine to F203 that is a surrogate for FS6, conserved in helix S6 of Domain IV of mammalian sodium channels, as well as low-affinity sites suggested to stabilize different states of the channel. Phenytoin exhibits a different binding distribution owing to preferential interactions at the membrane and water-protein interfaces. Two drug-access pathways into the pore are observed: via lateral fenestrations connecting to the membrane lipid phase, as well as via an aqueous pathway through the intracellular activation gate, despite being closed. These observations provide insight into drug modulation that will guide further developments of Nav inhibitors.

Refining the treatment of membrane proteins by coarse-grained models.

Obtaining a quantitative description of the membrane proteins stability is crucial for understanding many biological processes. However the advance in this direction has remained a major challenge for both experimental studies and molecular modeling. One of the possible directions is the use of coarse-grained models but such models must be carefully calibrated and validated. Here we use a recent progress in benchmark studies on the energetics of amino acid residue and peptide membrane insertion and membrane protein stability in refining our previously developed coarse-grained model (Vicatos et al., Proteins 2014;82:1168). Our refined model parameters were fitted and/or tested to reproduce water/membrane partitioning energetics of amino acid side chains and a couple of model peptides. This new model provides a reasonable agreement with experiment for absolute folding free energies of several ß-barrel membrane proteins as well as effects of point mutations on a relative stability for one of those proteins, OmpLA. The consideration and ranking of different rotameric states for a mutated residue was found to be essential to achieve satisfactory agreement with the reference data.

Ion-induced defect permeation of lipid membranes.

We have explored the mechanisms of uncatalyzed membrane ion permeation using atomistic simulations and electrophysiological recordings. The solubility-diffusion mechanism of membrane charge transport has prevailed since the 1960s, despite inconsistencies in experimental observations and its lack of consideration for the flexible response of lipid bilayers. We show that direct lipid bilayer translocation of alkali metal cations, Cl(-), and a charged arginine side chain analog occurs via an ion-induced defect mechanism. Contrary to some previous suggestions, the arginine analog experiences a large free-energy barrier, very similar to those for Na(+), K(+), and Cl(-). Our simulations reveal that membrane perturbations, due to the movement of an ion, are central for explaining the permeation process, leading to both free-energy and diffusion-coefficient profiles that show little dependence on ion chemistry and charge, despite wide-ranging hydration energies and the membrane's dipole potential. The results yield membrane permeabilities that are in semiquantitative agreement with experiments in terms of both magnitude and selectivity. We conclude that ion-induced defect-mediated permeation may compete with transient pores as the dominant mechanism of uncatalyzed ion permeation, providing new understanding for the actions of a range of membrane-active peptides and proteins.

The Membrane Dipole Potential and the Roles of Interfacial Water and Lipid Hydrocarbon Chains.

Understanding membrane charge transport processes, including the actions of ion channels, pumps, carriers, and membrane-active peptides, requires a description of the electrostatics of the lipid bilayer. We have simulated a library of different lipid chemistries to reveal the impact of the headgroup, glycerol backbone, and hydrocarbon chains on the membrane dipole potential. We found a strong dependence of the potential on lipid packing, but this was not caused by the packing of lipid polar components, due to cancellation of their electric fields by electrolyte. In contrast, lipid tail contributions were determined by area per lipid, arising from two countering effects. Increased area per lipid leads to chain tilting that increases methylene dipole projections to strengthen the electric field within the bilayer, while at the same time decreasing the electric field from terminal methyl groups. Moreover, electric fields from some nonterminal groups and the terminal methyl group can extend beyond the bilayer center and be canceled by the opposing leaflet. This interleaflet field annulment explains the experimental reduction in dipole potential for unsaturated and branched lipid bilayers, by as much as ∼200 mV, as well as experiments that substitute chain carbons with sulfur. Replacing ester with ether groups (eliminating two carbonyl groups) causes a significant reduction in potential, also by ∼200 mV, in agreement with experiment. We show that the effect can be largely attributed to the loss of aligned water molecules in the glycerol backbone region, lowering the potential inside the bilayer core. When only one of the two carbonyls is removed (using a hybrid ester-ether lipid or a single-chain lipid), most of this reduction in potential was lost, with the single carbonyl group able to maintain full hydration in the interfacial region. While headgroup chemistry can have a major effect (by as much as ±100 mV relative to phosphatidylcholine), anionic headgroups either decrease or increase the dipole potential, with the variation involving perturbation in hydrogen-bonded water molecules and changes in packing of lipid tails. Overall, these results suggest that membrane electrostatics are dominated by aligned water molecules at the polar-hydrocarbon interface and, surprisingly, by the charge distribution of the nonpolar lipid tails, and not the packing of headgroup and glycerol carbonyl dipoles.

Harnessing AlphaFold to reveal state secrets: Prediction of hERG closed and inactivated states.

To design safe, selective, and effective new therapies, there must be a deep understanding of the structure and function of the drug target. One of the most difficult problems to solve has been resolution of discrete conformational states of transmembrane ion channel proteins. An example is KV11.1 (hERG), comprising the primary cardiac repolarizing current, IKr. hERG is a notorious drug anti-target against which all promising drugs are screened to determine potential for arrhythmia. Drug interactions with the hERG inactivated state are linked to elevated arrhythmia risk, and drugs may become trapped during channel closure. However, the structural details of multiple conformational states have remained elusive. Here, we guided AlphaFold2 to predict plausible hERG inactivated and closed conformations, obtaining results consistent with myriad available experimental data. Drug docking simulations demonstrated hERG state-specific drug interactions aligning well with experimental results, revealing that most drugs bind more effectively in the inactivated state and are trapped in the closed state. Molecular dynamics simulations demonstrated ion conduction that aligned with earlier studies. Finally, we identified key molecular determinants of state transitions by analyzing interaction networks across closed, open, and inactivated states in agreement with earlier mutagenesis studies. Here, we demonstrate a readily generalizable application of AlphaFold2 as a novel method to predict discrete protein conformations and novel linkages from structure to function.

Toward Digital Twin Technology for Precision Pharmacology.

The authors demonstrate the feasibility of technological innovation for personalized medicine in the context of drug-induced arrhythmia. The authors use atomistic-scale structural models to predict rates of drug interaction with ion channels and make predictions of their effects in digital twins of induced pluripotent stem cell-derived cardiac myocytes. The authors construct a simplified multilayer, 1-dimensional ring model with sufficient path length to enable the prediction of arrhythmogenic dispersion of repolarization. Finally, the authors validate the computational pipeline prediction of drug effects with data and quantify drug-induced propensity to repolarization abnormalities in cardiac tissue. The technology is high throughput, computationally efficient, and low cost toward personalized pharmacologic prediction.