A molecular switch controls the impact of cholesterol on a Kir channel.

SignificanceCholesterol is one of the main components found in plasma membranes and is involved in lipid-dependent signaling enabled by integral membrane proteins such as inwardly rectifying potassium (Kir) channels. Similar to other ion channels, most of the Kir channels are down-regulated by cholesterol. One of the very few notable exceptions is Kir3.4, which is up-regulated by this important lipid. Here, we discovered and characterized a molecular switch that controls the impact (up-regulation vs. down-regulation) of cholesterol on Kir3.4. Our results provide a detailed molecular mechanism of tunable cholesterol regulation of a potassium channel.

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.

Toward Reducing hERG Affinities for DAT Inhibitors with a Combined Machine Learning and Molecular Modeling Approach.

Psychostimulant drugs, such as cocaine, inhibit dopamine reuptake via blockading the dopamine transporter (DAT), which is the primary mechanism underpinning their abuse. Atypical DAT inhibitors are dissimilar to cocaine and can block cocaine- or methamphetamine-induced behaviors, supporting their development as part of a treatment regimen for psychostimulant use disorders. When developing these atypical DAT inhibitors as medications, it is necessary to avoid off-target binding that can produce unwanted side effects or toxicities. In particular, the blockade of a potassium channel, human ether-a-go-go (hERG), can lead to potentially lethal ventricular tachycardia. In this study, we established a counter screening platform for DAT and against hERG binding by combining machine learning-based quantitative structure-activity relationship (QSAR) modeling, experimental validation, and molecular modeling and simulations. Our results show that the available data are adequate to establish robust QSAR models, as validated by chemical synthesis and pharmacological evaluation of a validation set of DAT inhibitors. Furthermore, the QSAR models based on subsets of the data according to experimental approaches used have predictive power as well, which opens the door to target specific functional states of a protein. Complementarily, our molecular modeling and simulations identified the structural elements responsible for a pair of DAT inhibitors having opposite binding affinity trends at DAT and hERG, which can be leveraged for rational optimization of lead atypical DAT inhibitors with desired pharmacological properties.

Computational membrane biophysics: From ion channel interactions with drugs to cellular function.

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Improving the LIE Method for Binding Free Energy Calculations of Protein-Ligand Complexes.

In this work, we introduced an improved linear interaction energy (LIE) method parameterization for computations of protein­ligand binding free energies. The protocol, coined LIE-D, builds on the linear relationship between the empirical coefficient γ in the standard LIE scheme and the D parameter, introduced in our work. The D-parameter encompasses the balance (difference) between electrostatic (polar) and van der Waals (nonpolar) energies in protein­ligand complexes. Leave-one-out cross-validation showed that LIE-D reproduced accurately the absolute binding free energies for our training set of protein­ligand complexes (<|error|> = 0.92 kcal/mol, SDerror = 0.66 kcal/mol, R(2) = 0.90, QLOO(2) = 0.89, and sPRESS(LOO) = 1.28 kcal/mol). We also demonstrated LIE-D robustness by predicting accurately the binding free energies for three different protein­ligand systems outside the training data set, where the electrostatic and van der Waals interaction energies were calculated with different force fields.

Lipid regulation of hERG1 channel function.

The lipid regulation of mammalian ion channel function has emerged as a fundamental mechanism in the control of electrical signalling and transport specificity in various cell types. In this work, we combine molecular dynamics simulations, mutagenesis, and electrophysiology to provide mechanistic insights into how lipophilic molecules (ceramide-sphingolipid probe) alter gating kinetics and K+ currents of hERG1. We show that the sphingolipid probe induced a significant left shift of activation voltage, faster deactivation rates, and current blockade comparable to traditional hERG1 blockers. Microseconds-long MD simulations followed by experimental mutagenesis elucidated ceramide specific binding locations at the interface between the pore and voltage sensing domains. This region constitutes a unique crevice present in mammalian channels with a non-swapped topology. The combined experimental and simulation data provide evidence for ceramide-induced allosteric modulation of the channel by a conformational selection mechanism.

Molecular Mechanism of Conductance Enhancement in Narrow Cation-Selective Membrane Channels.

Membrane proteins known as ryanodine receptors (RyRs) display large conductance of ∼1 nS and nearly ideal charge selectivity. Both properties are inversely correlated in other large-conductance but nonselective biological nanopores (i.e., α-hemolysin) used as industrial biosensors. Although recent cryo-electron microscopy structures of RyR2 show similarities to K+- and Na+-selective channels, it remains unclear whether similar ion conduction mechanisms occur in RyR2. Here, we combine microseconds of all-atom molecular dynamics (MD) simulations with mutagenesis and electrophysiology experiments to investigate large K+ conductance and charge selectivity (cation vs anion) in an open-state structure of RyR2. Our results show that a water-mediated knock-on mechanism enhances the cation permeation. The polar Q4863 ring may function as a confinement zone amplifying charge selectivity, while the cytoplasmic vestibule can contribute to the efficiency of the cation attraction. We also provide direct evidence that the rings of acidic residues at the channel vestibules are critical for both conductance and charge discrimination in RyRs.

Improved QM/MM Linear-Interaction Energy Model for Substrate Recognition in Zinc-Containing Metalloenzymes.

One of the essential challenges in the description of receptor-drug interactions in the presence of various polyvalent cations (such as zinc, magnesium, or iron) is the accurate assessment of the electronic effects due to cofactor binding. The effects can range from partial electronic polarization of the proximal atoms in a receptor and bound substrate to long-range effects related to partial charge transfer and electronic delocalization effects between the cofactor and the drug. Here, we examine the role of the explicit account for electronic effects for a panel of small-molecule inhibitors binding to the zinc-aminopeptidase PfA-M1, an essential target for antimalarial drug development. Our study on PfA-M1:inhibitor interactions at the QM level reveals that the partial charge and proton transfer due to bound zinc ion are important mechanisms in the inhibitors' recognition and catalysis. The combination of classical MD simulations with a posteriori QM/MM corrections with novel DFTB parameters for the zinc cation and the linear-interaction energy (LIE) approach offers by far the most accurate estimates for the PfA-M1:inhibitor binding affinities, opening the door for future inhibitor design.