The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics.

Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.

A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction.

De novo heterozygous variants in KCNC2 encoding the voltage-gated potassium (K+) channel subunit Kv3.2 are a recently described cause of developmental and epileptic encephalopathy (DEE). A de novo variant in KCNC2 c.374G > A (p.Cys125Tyr) was identified via exome sequencing in a patient with DEE. Relative to wild-type Kv3.2, Kv3.2-p.Cys125Tyr induces K+ currents exhibiting a large hyperpolarizing shift in the voltage dependence of activation, accelerated activation, and delayed deactivation consistent with a relative stabilization of the open conformation, along with increased current density. Leveraging the cryogenic electron microscopy (cryo-EM) structure of Kv3.1, molecular dynamic simulations suggest that a strong π-π stacking interaction between the variant Tyr125 and Tyr156 in the α-6 helix of the T1 domain promotes a relative stabilization of the open conformation of the channel, which underlies the observed gain of function. A multicompartment computational model of a Kv3-expressing parvalbumin-positive cerebral cortex fast-spiking γ-aminobutyric acidergic (GABAergic) interneuron (PV-IN) demonstrates how the Kv3.2-Cys125Tyr variant impairs neuronal excitability and dysregulates inhibition in cerebral cortex circuits to explain the resulting epilepsy.

The molecular basis for sugar import in malaria parasites.

Elucidating the mechanism of sugar import requires a molecular understanding of how transporters couple sugar binding and gating events. Whereas mammalian glucose transporters (GLUTs) are specialists1, the hexose transporter from the malaria parasite Plasmodium falciparum PfHT12,3 has acquired the ability to transport both glucose and fructose sugars as efficiently as the dedicated glucose (GLUT3) and fructose (GLUT5) transporters. Here, to establish the molecular basis of sugar promiscuity in malaria parasites, we determined the crystal structure of PfHT1 in complex with D-glucose at a resolution of 3.6 Å. We found that the sugar-binding site in PfHT1 is very similar to those of the distantly related GLUT3 and GLUT5 structures4,5. Nevertheless, engineered PfHT1 mutations made to match GLUT sugar-binding sites did not shift sugar preferences. The extracellular substrate-gating helix TM7b in PfHT1 was positioned in a fully occluded conformation, providing a unique glimpse into how sugar binding and gating are coupled. We determined that polar contacts between TM7b and TM1 (located about 15 Å from D-glucose) are just as critical for transport as the residues that directly coordinate D-glucose, which demonstrates a strong allosteric coupling between sugar binding and gating. We conclude that PfHT1 has achieved substrate promiscuity not by modifying its sugar-binding site, but instead by evolving substrate-gating dynamics.

An intracellular hydrophobic nexus critical for hERG1 channel slow deactivation.

Slow deactivation is a critical property of voltage-gated K+ channels encoded by the human Ether-à-go-go-Related Gene 1 (hERG). hERG1 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 (gPAS; residues 26-135) and an N-terminal PAS-cap that is further subdivided into an initial unstructured "tip" (residues 1-12) and an amphipathic α-helical region (residues 13-25). Although the PAS-cap tip has long been considered the effector of slow deactivation, how its position near the gating machinery is controlled has not been elucidated. Here, we show that a triad of hydrophobic interactions among the gPAS, PAS-cap α helix, and the CNBh domains is required to support slow deactivation in hERG1. The primary sequence of this "hydrophobic nexus" is highly conserved among mammalian ERG channels but shows key differences to fast-deactivating Ether-à-go-go 1 (EAG1) channels. Combining sequence analysis, structure-directed mutagenesis, electrophysiology, and molecular dynamics simulations, we demonstrate that polar serine substitutions uncover an intermediate deactivation mode that is also mimicked by deletion of the PAS-cap α helix. Molecular dynamics simulation analyses of the serine-substituted channels show an increase in distance among the residues of the hydrophobic nexus, a rotation of the intracellular gating ring, and a retraction of the PAS-cap tip from its receptor site near the voltage sensor domain and channel gate. These findings provide compelling evidence that the hydrophobic nexus coordinates the respective components of the intracellular gating ring and positions the PAS-cap tip to control hERG1 deactivation gating.

Functional cross-talk between phosphorylation and disease-causing mutations in the cardiac sodium channel Nav1.5.

The voltage-gated sodium channel Nav1.5 initiates the cardiac action potential. Alterations of its activation and inactivation properties due to mutations can cause severe, life-threatening arrhythmias. Yet despite intensive research efforts, many functional aspects of this cardiac channel remain poorly understood. For instance, Nav1.5 undergoes extensive posttranslational modification in vivo, but the functional significance of these modifications is largely unexplored, especially under pathological conditions. This is because most conventional approaches are unable to insert metabolically stable posttranslational modification mimics, thus preventing a precise elucidation of the contribution by these modifications to channel function. Here, we overcome this limitation by using protein semisynthesis of Nav1.5 in live cells and carry out complementary molecular dynamics simulations. We introduce metabolically stable phosphorylation mimics on both wild-type (WT) and two pathogenic long-QT mutant channel backgrounds and decipher functional and pharmacological effects with unique precision. We elucidate the mechanism by which phosphorylation of Y1495 impairs steady-state inactivation in WT Nav1.5. Surprisingly, we find that while the Q1476R patient mutation does not affect inactivation on its own, it enhances the impairment of steady-state inactivation caused by phosphorylation of Y1495 through enhanced unbinding of the inactivation particle. We also show that both phosphorylation and patient mutations can impact Nav1.5 sensitivity toward the clinically used antiarrhythmic drugs quinidine and ranolazine, but not flecainide. The data highlight that functional effects of Nav1.5 phosphorylation can be dramatically amplified by patient mutations. Our work is thus likely to have implications for the interpretation of mutational phenotypes and the design of future drug regimens.

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.

Design of Drug Efficacy Guided by Free Energy Simulations of the ß2 -Adrenoceptor.

G-protein-coupled receptors (GPCRs) play important roles in physiological processes and are modulated by drugs that either activate or block signaling. Rational design of the pharmacological efficacy profiles of GPCR ligands could enable the development of more efficient drugs, but is challenging even if high-resolution receptor structures are available. We performed molecular dynamics simulations of the ß2 adrenergic receptor in active and inactive conformations to assess if binding free energy calculations can predict differences in ligand efficacy for closely related compounds. Previously identified ligands were successfully classified into groups with comparable efficacy profiles based on the calculated shift in ligand affinity upon activation. A series of ligands were then predicted and synthesized, leading to the discovery of partial agonists with nanomolar potencies and novel scaffolds. Our results demonstrate that free energy simulations enable design of ligand efficacy and the same approach can be applied to other GPCR drug targets.

An open state of a voltage-gated sodium channel involving a π-helix and conserved pore-facing asparagine.

Voltage-gated sodium (Nav) channels play critical roles in propagating action potentials and otherwise manipulating ionic gradients in excitable cells. These channels open in response to membrane depolarization, selectively permeating sodium ions until rapidly inactivating. Structural characterization of the gating cycle in this channel family has proved challenging, particularly due to the transient nature of the open state. A structure from the bacterium Magnetococcus marinus Nav (NavMs) was initially proposed to be open, based on its pore diameter and voltage-sensor conformation. However, the functional annotation of this model, and the structural details of the open state, remain disputed. In this work, we used molecular modeling and simulations to test possible open-state models of NavMs. The full-length experimental structure, termed here the α-model, was consistently dehydrated at the activation gate, indicating an inability to conduct ions. Based on a spontaneous transition observed in extended simulations, and sequence/structure comparison to other Nav channels, we built an alternative π-model featuring a helix transition and the rotation of a conserved asparagine residue into the activation gate. Pore hydration, ion permeation, and state-dependent drug binding in this model were consistent with an open functional state. This work thus offers both a functional annotation of the full-length NavMs structure and a detailed model for a stable Nav open state, with potential conservation in diverse ion-channel families.

Allosteric Effect of Nanobody Binding on Ligand-Specific Active States of the ß2 Adrenergic Receptor.

Nanobody binding stabilizes G-protein-coupled receptors (GPCR) in a fully active state and modulates their affinity for bound ligands. However, the atomic-level basis for this allosteric regulation remains elusive. Here, we investigate the conformational changes induced by the binding of a nanobody (Nb80) on the active-like ß2 adrenergic receptor (ß2AR) via enhanced sampling molecular dynamics simulations. Dimensionality reduction analysis shows that Nb80 stabilizes structural features of the ß2AR with an ∼14 Å outward movement of transmembrane helix 6 and a close proximity of transmembrane (TM) helices 5 and 7, and favors the fully active-like conformation of the receptor, independent of ligand binding, in contrast to the conditions under which no intracellular binding partner is bound, in which case the receptor is only stabilized in an intermediate-active state. This activation is supported by the residues located at hotspots located on TMs 5, 6, and 7, as shown by supervised machine learning methods. Besides, ligand-specific subtle differences in the conformations assumed by intracellular loop 2 and extracellular loop 2 are captured from the trajectories of various ligand-bound receptors in the presence of Nb80. Dynamic network analysis further reveals that Nb80 binding triggers tighter and stronger local communication networks between the Nb80 and the ligand-binding sites, primarily involving residues around ICL2 and the intracellular end of TM3, TM5, TM6, as well as ECL2, ECL3, and the extracellular ends of TM6 and TM7. In particular, we identify unique allosteric signal transmission mechanisms between the Nb80-binding site and the extracellular domains in conformations modulated by a full agonist, BI167107, and a G-protein-biased partial agonist, salmeterol, involving mainly TM1 and TM2, and TM5, respectively. Altogether, our results provide insights into the effect of intracellular binding partners on the GPCR activation mechanism, which should be taken into account in structure-based drug discovery.

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel.

As the first potassium channel with an x-ray structure determined, and given its homology to eukaryotic channels, the pH-gated prokaryotic channel KcsA has been extensively studied. Nevertheless, questions related, in particular, to the allosteric coupling between its gates remain open. The many currently available x-ray crystallography structures appear to correspond to various stages of activation and inactivation, offering insights into the molecular basis of these mechanisms. Since these studies have required mutations, complexation with antibodies, and substitution of detergents in place of lipids, examining the channel under more native conditions is desirable. Solid-state nuclear magnetic resonance (SSNMR) can be used to study the wild-type protein under activating conditions (low pH), at room temperature, and in bacteriomimetic liposomes. In this work, we sought to structurally assign the activated state present in SSNMR experiments. We used a combination of molecular dynamics (MD) simulations, chemical shift prediction algorithms, and Bayesian inference techniques to determine which of the most plausible x-ray structures resolved to date best represents the activated state captured in SSNMR. We first identified specific nuclei with simulated NMR chemical shifts that differed significantly when comparing partially open vs fully open ensembles from MD simulations. The simulated NMR chemical shifts for those specific nuclei were then compared to experimental ones, revealing that the simulation of the partially open state was in good agreement with the SSNMR data. Nuclei that discriminate effectively between partially and fully open states belong to residues spread over the sequence and provide a molecular level description of the conformational change.

Pulsed Electric Fields Can Create Pores in the Voltage Sensors of Voltage-Gated Ion Channels.

Pulsed electric fields are increasingly used in medicine to transiently increase the cell membrane permeability via electroporation to deliver therapeutic molecules into the cell. One type of event that contributes to this increase in membrane permeability is the formation of pores in the membrane lipid bilayer. However, electrophysiological measurements suggest that membrane proteins are affected as well, particularly voltage-gated ion channels (VGICs). The molecular mechanisms by which the electric field could affects these molecules remain unidentified. In this study, we used molecular dynamics simulations to unravel the molecular events that take place in different VGICs when exposing them to electric fields mimicking electroporation conditions. We show that electric fields can induce pores in the voltage-sensor domains (VSDs) of different VGICs and that these pores form more easily in some channels than in others. We demonstrate that poration is more likely in VSDs that are more hydrated and are electrostatically more favorable for the entry of ions. We further show that pores in VSDs can expand into so-called complex pores, which become stabilized by lipid headgroups. Our results suggest that such complex pores are considerably more stable than conventional lipid pores, and their formation can lead to severe unfolding of VSDs from the channel. We anticipate that such VSDs become dysfunctional and unable to respond to changes in transmembrane voltage, which is in agreement with previous electrophysiological measurements showing a decrease in the voltage-dependent transmembrane ionic currents after pulse treatment. Finally, we discuss the possibility of activation of VGICs by submicrosecond-duration pulses. Overall, our study reveals a new, to our knowledge, mechanism of electroporation through membranes containing VGICs.

Molecular Insights from Conformational Ensembles via Machine Learning.

Biomolecular simulations are intrinsically high dimensional and generate noisy data sets of ever-increasing size. Extracting important features from the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides powerful dimensionality reduction tools. However, such methods are often criticized as resembling black boxes with limited human-interpretable insight. We use methods from supervised and unsupervised ML to efficiently create interpretable maps of important features from molecular simulations. We benchmark the performance of several methods, including neural networks, random forests, and principal component analysis, using a toy model with properties reminiscent of macromolecular behavior. We then analyze three diverse biological processes: conformational changes within the soluble protein calmodulin, ligand binding to a G protein-coupled receptor, and activation of an ion channel voltage-sensor domain, unraveling features critical for signal transduction, ligand binding, and voltage sensing. This work demonstrates the usefulness of ML in understanding biomolecular states and demystifying complex simulations.

Energy Landscapes Reveal Agonist Control of G Protein-Coupled Receptor Activation via Microswitches.

Agonist binding to G protein-coupled receptors (GPCRs) leads to conformational changes in the transmembrane region that activate cytosolic signaling pathways. Although high-resolution structures of different receptor states are available, atomistic details of allosteric signaling across the membrane remain elusive. We calculated free energy landscapes of ß2 adrenergic receptor activation using atomistic molecular dynamics simulations in an optimized string of swarms framework, which shed new light on how microswitches govern the equilibrium between conformational states. Contraction of the extracellular binding site in the presence of the agonist BI-167107 is obligatorily coupled to conformational changes in a connector motif located in the core of the transmembrane region. The connector is probabilistically coupled to the conformation of the intracellular region. An active connector promotes desolvation of a buried cavity, a twist of the conserved NPxxY motif, and an interaction between two conserved tyrosines in transmembrane helices 5 and 7 (Y-Y motif), which lead to a larger population of active-like states at the G protein binding site. This coupling is augmented by protonation of the strongly conserved Asp792.50. The agonist binding site hence communicates with the intracellular region via a cascade of locally connected microswitches. Characterization of these can be used to understand how ligands stabilize distinct receptor states and contribute to development drugs with specific signaling properties. The developed simulation protocol can likely be transferred to other class A GPCRs.

Tracking the motion of the KV1.2 voltage sensor reveals the molecular perturbations caused by a de novo mutation in a case of epilepsy.

KEY POINTS: KV1.2 channels, encoded by the KCNA2 gene, regulate neuronal excitability by conducting K+ upon depolarization. A new KCNA2 missense variant was discovered in a patient with epilepsy, causing amino acid substitution F302L at helix S4, in the KV1.2 voltage-sensing domain. Immunocytochemistry and flow cytometry showed that F302L does not impair KCNA2 subunit surface trafficking. Molecular dynamics simulations indicated that F302L alters the exposure of S4 residues to membrane lipids. Voltage clamp fluorometry revealed that the voltage-sensing domain of KV1.2-F302L channels is more sensitive to depolarization. Accordingly, KV1.2-F302L channels opened faster and at more negative potentials; however, they also exhibited enhanced inactivation: that is, F302L causes both gain- and loss-of-function effects. Coexpression of KCNA2-WT and -F302L did not fully rescue these effects. The proband's symptoms are more characteristic of patients with loss of KCNA2 function. Enhanced KV1.2 inactivation could lead to increased synaptic release in excitatory neurons, steering neuronal circuits towards epilepsy. ABSTRACT: An exome-based diagnostic panel in an infant with epilepsy revealed a previously unreported de novo missense variant in KCNA2, which encodes voltage-gated K+ channel KV1.2. This variant causes substitution F302L, in helix S4 of the KV1.2 voltage-sensing domain (VSD). F302L does not affect KCNA2 subunit membrane trafficking. However, it does alter channel functional properties, accelerating channel opening at more hyperpolarized membrane potentials, indicating gain of function. F302L also caused loss of KV1.2 function via accelerated inactivation onset, decelerated recovery and shifted inactivation voltage dependence to more negative potentials. These effects, which are not fully rescued by coexpression of wild-type and mutant KCNA2 subunits, probably result from the enhancement of VSD function, as demonstrated by optically tracking VSD depolarization-evoked conformational rearrangements. In turn, molecular dynamics simulations suggest altered VSD exposure to membrane lipids. Compared to other encephalopathy patients with KCNA2 mutations, the proband exhibits mild neurological impairment, more characteristic of patients with KCNA2 loss of function. Based on this information, we propose a mechanism of epileptogenesis based on enhanced KV1.2 inactivation leading to increased synaptic release preferentially in excitatory neurons, and hence the perturbation of the excitatory/inhibitory balance of neuronal circuits.

Network analysis reveals how lipids and other cofactors influence membrane protein allostery.

Many membrane proteins are modulated by external stimuli, such as small molecule binding or change in pH, transmembrane voltage, or temperature. This modulation typically occurs at sites that are structurally distant from the functional site. Revealing the communication, known as allostery, between these two sites is key to understanding the mechanistic details of these proteins. Residue interaction networks of isolated proteins are commonly used to this end. Membrane proteins, however, are embedded in a lipid bilayer, which may contribute to allosteric communication. The fast diffusion of lipids hinders direct use of standard residue interaction networks. Here, we present an extension that includes cofactors such as lipids and small molecules in the network. The novel framework is applied to three membrane proteins: a voltage-gated ion channel (KCNQ1), a G-protein coupled receptor (GPCR-ß2 adrenergic receptor), and a pH-gated ion channel (KcsA). Through systematic analysis of the obtained networks and their components, we demonstrate the importance of lipids for membrane protein allostery. Finally, we reveal how small molecules may stabilize different protein states by allosterically coupling and decoupling the protein from the membrane.

Biophysical Characterization of Epigallocatechin-3-Gallate Effect on the Cardiac Sodium Channel Nav1.5.

Epigallocatechin-3-Gallate (EGCG) has been extensively studied for its protective effect against cardiovascular disorders. This effect has been attributed to its action on multiple molecular pathways and transmembrane proteins, including the cardiac Nav1.5 channels, which are inhibited in a dose-dependent manner. However, the molecular mechanism underlying this effect remains to be unveiled. To this aim, we have characterized the EGCG effect on Nav1.5 using electrophysiology and molecular dynamics (MD) simulations. EGCG superfusion induced a dose-dependent inhibition of Nav1.5 expressed in tsA201 cells, negatively shifted the steady-state inactivation curve, slowed the inactivation kinetics, and delayed the recovery from fast inactivation. However, EGCG had no effect on the voltage-dependence of activation and showed little use-dependent block on Nav1.5. Finally, MD simulations suggested that EGCG does not preferentially stay in the center of the bilayer, but that it spontaneously relocates to the membrane headgroup region. Moreover, no sign of spontaneous crossing from one leaflet to the other was observed, indicating a relatively large free energy barrier associated with EGCG transport across the membrane. These results indicate that EGCG may exert its biophysical effect via access to its binding site through the cell membrane or via a bilayer-mediated mechanism.

Effect of Ca2+ on the promiscuous target-protein binding of calmodulin.

Calmodulin (CaM) is a calcium sensing protein that regulates the function of a large number of proteins, thus playing a crucial part in many cell signaling pathways. CaM has the ability to bind more than 300 different target peptides in a Ca2+-dependent manner, mainly through the exposure of hydrophobic residues. How CaM can bind a large number of targets while retaining some selectivity is a fascinating open question. Here, we explore the mechanism of CaM selective promiscuity for selected target proteins. Analyzing enhanced sampling molecular dynamics simulations of Ca2+-bound and Ca2+-free CaM via spectral clustering has allowed us to identify distinct conformational states, characterized by interhelical angles, secondary structure determinants and the solvent exposure of specific residues. We searched for indicators of conformational selection by mapping solvent exposure of residues in these conformational states to contacts in structures of CaM/target peptide complexes. We thereby identified CaM states involved in various binding classes arranged along a depth binding gradient. Binding Ca2+ modifies the accessible hydrophobic surface of the two lobes and allows for deeper binding. Apo CaM indeed shows shallow binding involving predominantly polar and charged residues. Furthermore, binding to the C-terminal lobe of CaM appears selective and involves specific conformational states that can facilitate deep binding to target proteins, while binding to the N-terminal lobe appears to happen through a more flexible mechanism. Thus the long-ranged electrostatic interactions of the charged residues of the N-terminal lobe of CaM may initiate binding, while the short-ranged interactions of hydrophobic residues in the C-terminal lobe of CaM may account for selectivity. This work furthers our understanding of the mechanism of CaM binding and selectivity to different target proteins and paves the way towards a comprehensive model of CaM selectivity.

Sharing Data from Molecular Simulations.

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/ ). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.