Structure of the Human BK Ion Channel in Lipid Environment

Structural biology and molecular pharmacology of voltage-gated ion channels

Voltage-gated ion channels (VGICs), including those for Na+, Ca2+ and K+, selectively permeate ions across the cell membrane in response to changes in membrane potential, thus participating in physiological processes involving electrical signalling, such as neurotransmission, muscle contraction and hormone secretion. Aberrant function or dysregulation of VGICs is associated with a diversity of neurological, psychiatric, cardiovascular and muscular disorders, and approximately 10% of FDA-approved drugs directly target VGICs. Understanding the structure-function relationship of VGICs is crucial for our comprehension of their working mechanisms and role in diseases. In this Review, we discuss how advances in single-particle cryo-electron microscopy have afforded unprecedented structural insights into VGICs, especially on their interactions with clinical and investigational drugs. We present a comprehensive overview of the recent advances in the structural biology of VGICs, with a focus on how prototypical drugs and toxins modulate VGIC activities. We explore how these structures elucidate the molecular basis for drug actions, reveal novel pharmacological sites, and provide critical clues to future drug discovery.

Redox-dependent Cd2+ inhibition of BK-type Ca2+-activated K+ channels

Large-conductance Ca2+-activated K+ channels (BK channels) are formed by Slo1 subunits as a homotetramer. Besides Ca2+, other divalent cations, such as Cd2+, also activate BK channels when applied intracellularly by shifting the conductance-voltage relation to more negative voltages. However, we found that if the inside-out patch containing BK channels was treated with solution containing reducing agents such as dithiothreitol (DTT), then subsequent Cd2+ application completely inhibited BK currents. The DTT-dependent Cd2+ inhibition could be reversed by treating the patch with solutions containing H2O2, suggesting that a redox reaction regulates the Cd2+ inhibition of BK channels. Similar DTT-dependent Cd2+ inhibition was also observed in a mutant BK channel, Core-MT, in which the cytosolic domain of the channel is deleted, and in the proton-activated Slo3 channels but not observed in the voltage-gated Shaker K+ channels. A possible mechanism for the DTT-dependent Cd2+ inhibition is that DTT treatment breaks one or more disulfide bonds between cysteine pairs in the BK channel protein and the freed thiol groups coordinate with Cd2+ to form an ion bridge that blocks the channel or locks the channel at the closed state. However, surprisingly, none of the mutations of all cysteine residues in Slo1 affect the DTT-dependent Cd2+ inhibition. These results are puzzling, with an apparent contradiction: on one hand, a redox reaction seems to regulate Cd2+ inhibition of the channel, but on the other hand, no cysteine residue in the Slo1 subunit seems to be involved in such inhibition.

Kcnma1 alternative splicing in mouse kidney: regulation during development and by dietary K+ intake

The pore-forming α-subunit of the large-conductance K+ (BK) channel is encoded by a single gene, KCNMA1. BK channel-mediated K+ secretion in the kidney is crucial for overall renal K+ homeostasis in both physiological and pathological conditions. BK channels achieve phenotypic diversity by various mechanisms, including substantial exon rearrangements at seven major alternative splicing sites. However, KCNMA1 alternative splicing in the kidney has not been characterized. The present study aims to identify the major splice variants of mouse Kcnma1 in whole kidney and distal nephron segments. We designed primers that specifically cross exons within each alternative splice site of mouse Kcnma1 and performed real-time quantitative RT-PCR (RT-qPCR) to quantify relative abundance of each splice variant. Our data suggest that Kcnma1 splice variants within mouse kidney are less diverse than in the brain. During postnatal kidney development, most Kcnma1 splice variants at site 5 and the COOH terminus increase in abundance over time. Within the kidney, the regulation of Kcnma1 alternative exon splicing within these two sites by dietary K+ loading is both site and sex specific. In microdissected distal tubules, the Kcnma1 alternative splicing profile, as well as its regulation by dietary K+, are distinctly different than in the whole kidney, suggesting segment and/or cell type specificity in Kcnma1 splicing events. Overall, our data provide evidence that Kcnma1 alternative splicing is regulated during postnatal development and may serve as an important adaptive mechanism to dietary K+ loading in mouse kidney.NEW & NOTEWORTHY We identified the major Kcnma1 splice variants that are specifically expressed in the whole mouse kidney or aldosterone-sensitive distal nephron segments. Our data suggest that Kcnma1 alternative splicing is developmentally regulated and subject to changes in dietary K+.

Advances in Membrane Mimetic Systems for Manipulation and Analysis of Membrane Proteins: Detergents, Polymers, Lipids and Scaffolds

Extracting membrane proteins from the hydrophobic environment of the biological membrane, in a physiologically relevant and stable state, suitable for downstream analysis remains a challenge. The traditional route to membrane protein extraction has been to use detergents and the last 15 years or so have seen a veritable explosion in the development of novel detergents with improved properties, making them more suitable for individual proteins and specific applications. There have also been significant advances in the development of encapsulation of membrane proteins in lipid based nanodiscs, either directly from the native membrane using polymers allowing effective capture of the protein and protein-associated membrane lipids, or via reconstitution of detergent extracted and purified protein into nanodiscs of defined lipid composition. All of these advances have been successfully applied to the study of membrane proteins via a range of techniques and there have been some spectacular membrane protein structures solved. In addition, the first detailed structural and biophysical analyses of membrane proteins retained within a biological membrane have been reported. Here we summarise and review the recent advances with respect to these new agents and systems for membrane protein extraction, reconstitution and analysis.

Incorporating physics to overcome data scarcity in predictive modeling of protein function: A case study of BK channels

Machine learning has played transformative roles in numerous chemical and biophysical problems such as protein folding where large amount of data exists. Nonetheless, many important problems remain challenging for data-driven machine learning approaches due to the limitation of data scarcity. One approach to overcome data scarcity is to incorporate physical principles such as through molecular modeling and simulation. Here, we focus on the big potassium (BK) channels that play important roles in cardiovascular and neural systems. Many mutants of BK channel are associated with various neurological and cardiovascular diseases, but the molecular effects are unknown. The voltage gating properties of BK channels have been characterized for 473 site-specific mutations experimentally over the last three decades; yet, these functional data by themselves remain far too sparse to derive a predictive model of BK channel voltage gating. Using physics-based modeling, we quantify the energetic effects of all single mutations on both open and closed states of the channel. Together with dynamic properties derived from atomistic simulations, these physical descriptors allow the training of random forest models that could reproduce unseen experimentally measured shifts in gating voltage, ∆V1/2, with a RMSE ~ 32 mV and correlation coefficient of R ~ 0.7. Importantly, the model appears capable of uncovering nontrivial physical principles underlying the gating of the channel, including a central role of hydrophobic gating. The model was further evaluated using four novel mutations of L235 and V236 on the S5 helix, mutations of which are predicted to have opposing effects on V1/2 and suggest a key role of S5 in mediating voltage sensor-pore coupling. The measured ∆V1/2 agree quantitatively with prediction for all four mutations, with a high correlation of R = 0.92 and RMSE = 18 mV. Therefore, the model can capture nontrivial voltage gating properties in regions where few mutations are known. The success of predictive modeling of BK voltage gating demonstrates the potential of combining physics and statistical learning for overcoming data scarcity in nontrivial protein function prediction.

Determining the structure of the bacterial voltage-gated sodium channel NaChBac embedded in liposomes by cryo electron tomography and subtomogram averaging

Voltage-gated sodium channels shape action potentials that propagate signals along cells. When the membrane potential reaches a certain threshold, the channels open and allow sodium ions to flow through the membrane depolarizing it, followed by the deactivation of the channels. Opening and closing of the channels is important for cellular signalling and regulates various physiological processes in muscles, heart and brain. Mechanistic insights into the voltage-gated channels are difficult to achieve as the proteins are typically extracted from membranes for structural analysis which results in the loss of the transmembrane potential that regulates their activity. Here, we report the structural analysis of a bacterial voltage-gated sodium channel, NaChBac, reconstituted in liposomes under an electrochemical gradient by cryo electron tomography and subtomogram averaging. We show that the small channel, most of the residues of which are embedded in the membrane, can be localized using a genetically fused GFP. GFP can aid the initial alignment to an average resulting in a correct structure, but does not help for the final refinement. At a moderate resolution of ˜16 Å the structure of NaChBac in an unrestricted membrane bilayer is 10% wider than the structure of the purified protein previously solved in nanodiscs, suggesting the potential movement of the peripheral voltage-sensing domains. Our study explores the limits of structural analysis of membrane proteins in membranes.

Incorporating physics to overcome data scarcity in predictive modeling of protein function: a case study of BK channels

Machine learning has played transformative roles in numerous chemical and biophysical problems such as protein folding where large amount of data exists. Nonetheless, many important problems remain challenging for data-driven machine learning approaches due to the limitation of data scarcity. One approach to overcome data scarcity is to incorporate physical principles such as through molecular modeling and simulation. Here, we focus on the big potassium (BK) channels that play important roles in cardiovascular and neural systems. Many mutants of BK channel are associated with various neurological and cardiovascular diseases, but the molecular effects are unknown. The voltage gating properties of BK channels have been characterized for 473 site-specific mutations experimentally over the last three decades; yet, these functional data by themselves remain far too sparse to derive a predictive model of BK channel voltage gating. Using physics-based modeling, we quantify the energetic effects of all single mutations on both open and closed states of the channel. Together with dynamic properties derived from atomistic simulations, these physical descriptors allow the training of random forest models that could reproduce unseen experimentally measured shifts in gating voltage, ΔV 1/2 , with a RMSE ∼ 32 mV and correlation coefficient of R ∼ 0.7. Importantly, the model appears capable of uncovering nontrivial physical principles underlying the gating of the channel, including a central role of hydrophobic gating. The model was further evaluated using four novel mutations of L235 and V236 on the S5 helix, mutations of which are predicted to have opposing effects on V 1/2 and suggest a key role of S5 in mediating voltage sensor-pore coupling. The measured ΔV 1/2 agree quantitatively with prediction for all four mutations, with a high correlation of R = 0.92 and RMSE = 18 mV. Therefore, the model can capture nontrivial voltage gating properties in regions where few mutations are known. The success of predictive modeling of BK voltage gating demonstrates the potential of combining physics and statistical learning for overcoming data scarcity in nontrivial protein function prediction.

Author Summary

Deep machine learning has brought many exciting breakthroughs in chemistry, physics and biology. These models require large amount of training data and struggle when the data is scarce. The latter is true for predictive modeling of the function of complex proteins such as ion channels, where only hundreds of mutational data may be available. Using the big potassium (BK) channel as a biologically important model system, we demonstrate that a reliable predictive model of its voltage gating property could be derived from only 473 mutational data by incorporating physics-derived features, which include dynamic properties from molecular dynamics simulations and energetic quantities from Rosetta mutation calculations. We show that the final random forest model captures key trends and hotspots in mutational effects of BK voltage gating, such as the important role of pore hydrophobicity. A particularly curious prediction is that mutations of two adjacent residues on the S5 helix would always have opposite effects on the gating voltage, which was confirmed by experimental characterization of four novel mutations. The current work demonstrates the importance and effectiveness of incorporating physics in predictive modeling of protein function with scarce data.

Membrane protein isolation and structure determination in cell-derived membrane vesicles

Integral membrane protein structure determination traditionally requires extraction from cell membranes using detergents or polymers. Here, we describe the isolation and structure determination of proteins in membrane vesicles derived directly from cells. Structures of the ion channel Slo1 from total cell membranes and from cell plasma membranes were determined at 3.8 Å and 2.7 Å resolution, respectively. The plasma membrane environment stabilizes Slo1, revealing an alteration of global helical packing, polar lipid, and cholesterol interactions that stabilize previously unresolved regions of the channel and an additional ion binding site in the Ca2+ regulatory domain. The two methods presented enable structural analysis of both internal and plasma membrane proteins without disrupting weakly interacting proteins, lipids, and cofactors that are essential to biological function.

Regulation of Neurotransmitter Release by K+ Channels

K+ channels play potent roles in the process of neurotransmitter release by influencing the action potential waveform and modulating neuronal excitability and release probability. These diverse effects of K+ channel activation are ensured by the wide variety of K+ channel genes and their differential expression in different cell types. Accordingly, a variety of K+ channels have been implicated in regulating neurotransmitter release, including the Ca2+- and voltage-gated K+ channel Slo1 (also known as BK channel), voltage-gated K+ channels of the Kv3 (Shaw-type), Kv1 (Shaker-type), and Kv7 (KCNQ) families, G-protein-gated inwardly rectifying K+ (GIRK) channels, and SLO-2 (a Ca2+-. Cl-, and voltage-gated K+ channel in C. elegans). These channels vary in their expression patterns, subcellular localization, and biophysical properties. Their roles in neurotransmitter release may also vary depending on the synapse and physiological or experimental conditions. This chapter summarizes key findings about the roles of K+ channels in regulating neurotransmitter release.