Membrane protein structural biology in the era of single particle cryo-EM

Applications of fluorescent protein tagging in structural studies of membrane proteins

Generating active, pure, and monodisperse protein remains a major bottleneck for structural studies using X-ray crystallography and cryo-electron microscopy (cryo-EM). The current methodology heavily relies on overexpressing the recombinant protein fused with a histidine tag in conventional expression systems and evaluating the quality and stability of purified protein using size exclusion chromatography (SEC). This requires a large amount of protein and can be highly laborious and time consuming. Therefore, this approach is not suitable for high-throughput screening and low-expressing macromolecules, particularly eukaryotic membrane proteins. Using fluorescent proteins fused to the target protein (applicable to both soluble and membrane proteins) enables rapid and efficient screening of expression level and monodispersity of tens of unpurified constructs using fluorescence-based size exclusion chromatography (FSEC). Moreover, FSEC proves valuable for screening multiple detergents to identify the most stabilizing agent in the case of membrane proteins. Additionally, FSEC can facilitate nanodisc reconstitution by determining the optimal ratio of membrane scaffold protein (MSP), lipids, and target protein. The distinct advantages offered by FSEC indicate that fluorescent proteins can serve as a viable alternative to commonly used affinity tags for both characterization and purification purposes. In this review, I will summarize the advantages of this technique using examples from my own work. It should be noted that this article is not intended to provide an exhaustive review of all available literature, but rather to offer representative examples of FSEC applications.

Efficient Segmental Isotope Labeling of Integral Membrane Proteins for High-Resolution NMR Studies

High-resolution structural NMR analyses of membrane proteins are challenging due to their large size, resulting in broad resonances and strong signal overlap. Among the isotope labeling methods that can remedy this situation, segmental isotope labeling is a suitable strategy to simplify NMR spectra and retain high-resolution structural information. However, protein ligation within integral membrane proteins is complicated since the hydrophobic protein fragments are insoluble, and the removal of ligation side-products is elaborate. Here, we show that a stabilized split-intein system can be used for rapid and high-yield protein trans-splicing of integral membrane proteins under denaturing conditions. This setup enables segmental isotope labeling experiments within folded protein domains for NMR studies. We show that high-quality NMR spectra of markedly reduced complexity can be obtained in detergent micelles and lipid nanodiscs. Of note, the nanodisc insertion step specifically selects for the ligated and correctly folded membrane protein and simultaneously removes ligation byproducts. Using this tailored workflow, we show that high-resolution NMR structure determination is strongly facilitated with just two segmentally isotope-labeled membrane protein samples. The presented method will be broadly applicable to structural and dynamical investigations of (membrane-) proteins and their complexes by solution and solid-state NMR but also other structural methods where segmental labeling is beneficial.

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.

Establishing comprehensive quaternary structural proteomes from genome sequence

A critical body of knowledge has developed through advances in protein microscopy, protein-fold modeling, structural biology software, availability of sequenced bacterial genomes, large-scale mutation databases, and genome-scale models. Based on these recent advances, we develop a computational framework that; i) identifies the oligomeric structural proteome encoded by an organism's genome from available structural resources; ii) maps multi-strain alleleomic variation, resulting in the structural proteome for a species; and iii) calculates the 3D orientation of proteins across subcellular compartments with residue-level precision. Using the platform, we; iv) compute the quaternary E. coli K-12 MG1655 structural proteome; v) use a dataset of 12,000 mutations to build Random Forest classifiers that can predict the severity of mutations; and, in combination with a genome-scale model that computes proteome allocation, vi) obtain the spatial allocation of the E. coli proteome. Thus, in conjunction with relevant datasets and increasingly accurate computational models, we can now annotate quaternary structural proteomes, at genome-scale, to obtain a molecular-level understanding of whole-cell functions.

Significance

Advancements in experimental and computational methods have revealed the shapes of multi-subunit proteins. The absence of a unified platform that maps actionable datatypes onto these increasingly accurate structures creates a barrier to structural analyses, especially at the genome-scale. Here, we describe QSPACE, a computational annotation platform that evaluates existing resources to identify the best-available structure for each protein in a user's query, maps the 3D location of actionable datatypes ( e.g. , active sites, published mutations) onto the selected structures, and uses third-party APIs to determine the subcellular compartment of all amino acids of a protein. As proof-of-concept, we deployed QSPACE to generate the quaternary structural proteome of E. coli MG1655 and demonstrate two use-cases involving large-scale mutant analysis and genome-scale modelling.

Atomic force microscope kymograph analysis: A case study of two membrane proteins

Kymograph analysis is employed across the biological atomic force microscopy (AFM) community to boost temporal resolution. The method is well suited for revealing protein dynamics at the single molecule level in near-native conditions. Yet, kymograph analysis comes with limitations that depend on several factors including protein geometry and instrumental drift. This work focuses on conformational dynamics of difficult-to-study sparse distributions of membrane proteins. We compare and contrast AFM kymograph analysis for two proteins, one of which (SecDF) exhibits conformational dynamics primarily in the vertical direction (normal to the membrane surface) and the other (Pgp) exhibits a combination of lateral dynamics and vertical motion. Common experimental issues are analyzed including translational and rotational drift. Conformational transition detection is evaluated via kymograph simulations followed by state detection algorithms. We find that kymograph analysis is largely robust to lateral drift. Displacement of the AFM line scan trajectory away from the protein center of mass by a few nanometers, roughly half of the molecule diameter, does not significantly affect transition detection nor generate undue dwell time errors. On the other hand, for proteins like Pgp that exhibit significant azimuthal maximum height dependence, rotational drift can potentially produce artifactual transitions. Measuring the height of a membrane protein protrusion is generally superior to measurement of width, confirming intuition based on vertical resolution superiority. In low signal-to-noise scenarios, common state detection algorithms struggle with transition detection as opposed to infinite hidden Markov models. AFM kymography represents a valuable addition to the membrane biophysics toolkit; continued hardware and software improvements are poised to expand the method's impact in the field.

Structural insights into membrane adenylyl cyclases, initiators of cAMP signaling

Membrane adenylyl cyclases (ACs) catalyze the conversion of ATP to the ubiquitous second messenger cAMP. As effector proteins of G protein-coupled receptors and other signaling pathways, ACs receive and amplify signals from the cell surface, translating them into biochemical reactions in the intracellular space and integrating different signaling pathways. Despite their importance in signal transduction and physiology, our knowledge about the structure, function, regulation, and molecular interactions of ACs remains relatively scarce. In this review, we summarize recent advances in our understanding of these membrane enzymes.

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

In Situ Monitoring of Membrane Protein Electron Transfer via Surface-Enhanced Resonance Raman Spectroscopy

In situ analysis of membrane protein-ligand interactions under physiological conditions is of significance for both fundamental and applied science, but it is still a big challenge due to the limits in sensitivity and selectivity. Here, we demonstrate the potential of surface-enhanced resonance Raman spectroscopy (SERRS) for the investigation of membrane protein-protein interactions. Lipid biolayers are successfully coated on silver nanoparticles through electrostatic interactions, and a highly sensitive and biomimetic membrane platform is obtained in vitro. Self-assembly and immobilization of the reduced cytochrome b5 on the coated membrane are achieved and protein native biological functions are preserved. Owing to resonance effect, the Raman fingerprint of the immobilized cytochrome b5 redox center is selectively enhanced, allowing for in situ and real-time monitoring of the electron transfer process between cytochrome b5 and their partners, cytochrome c and myoglobin. This study provides a sensitive analytical approach for membrane proteins and paves the way for in situ exploration of their structural basis and functions.

Targeting structural flexibility in low density lipoprotein by integrating cryo-electron microscopy and high-speed atomic force microscopy

Low-density lipoprotein (LDL) plays a crucial role in cholesterol metabolism. Responsible for cholesterol transport from the liver to the organs, LDL accumulation in the arteries is a primary cause of cardiovascular diseases, such as atherosclerosis. This work focuses on the fundamental question of the LDL molecular structure, as well as the topology and molecular motions of apolipoprotein B-100 (apo B-100), which is addressed by single-particle cryo-electron microscopy (cryo-EM) and high-speed atomic force microscopy (HS-AFM). Our results suggest a revised model of the LDL core organization with respect to the cholesterol ester (CE) arrangement. In addition, a high-density region close to the flattened poles could be identified, likely enriched in free cholesterol. The most remarkable new details are two protrusions on the LDL surface, attributed to the protein apo B-100. HS-AFM adds the dimension of time and reveals for the first time a highly dynamic direct description of LDL, where we could follow large domain fluctuations of the protrusions in real time. To tackle the inherent flexibility and heterogeneity of LDL, the cryo-EM maps are further assessed by 3D variability analysis. Our study gives a detailed explanation how to approach the intrinsic flexibility of a complex system comprising lipids and protein.

Cryo-EM of a heterogeneous biochemical fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote

Biomolecular complexes and their interactions govern cellular structure and function. Understanding their architecture is a prerequisite for dissecting the cell's inner workings, but their higher-order assembly is often transient and challenging for structural analysis. Here, we performed cryo-EM on a single, highly heterogeneous biochemical fraction derived from Chaetomium thermophilum cell extracts to visualize the biomolecular content of the multicellular eukaryote. After cryo-EM single-particle image processing, results showed that a simultaneous three-dimensional structural characterization of multiple chemically diverse biomacromolecules is feasible. Namely, the thermophilic, eukaryotic complexes of (a) ATP citrate-lyase, (b) Hsp90, (c) 20S proteasome, (d) Hsp60 and (e) UDP-glucose pyrophosphorylase were characterized. In total, all five complexes have been structurally dissected in a thermophilic eukaryote in a total imaged sample area of 190.64 μm2, and two, in particular, 20S proteasome and Hsp60, exhibit side-chain resolution features. The C. thermophilum Hsp60 near-atomic model was resolved at 3.46 Å (FSC = 0.143) and shows a hinge-like conformational change of its equatorial domain, highly similar to the one previously shown for its bacterial orthologue, GroEL. This work demonstrates that cryo-EM of cell extracts will greatly accelerate the structural analysis of cellular complexes and provide unprecedented opportunities to annotate architectures of biomolecules in a holistic approach.

Analyzing the cellular plasma membrane by fast and efficient correlative STED and platinum replica EM

The plasma membrane of mammalian cells links transmembrane receptors, various structural components, and membrane-binding proteins to subcellular processes, allowing inter- and intracellular communication. Therefore, membrane-binding proteins, together with structural components such as actin filaments, modulate the cell membrane in their flexibility, stiffness, and curvature. Investigating membrane components and curvature in cells remains challenging due to the diffraction limit in light microscopy. Preparation of 5-15-nm-thin plasma membrane sheets and subsequent inspection by metal replica transmission electron microscopy (TEM) reveal detailed information about the cellular membrane topology, including the structure and curvature. However, electron microscopy cannot identify proteins associated with specific plasma membrane domains. Here, we describe a novel adaptation of correlative super-resolution light microscopy and platinum replica TEM (CLEM-PREM), allowing the analysis of plasma membrane sheets with respect to their structural details, curvature, and associated protein composition. We suggest a number of shortcuts and troubleshooting solutions to contemporary PREM protocols. Thus, implementation of super-resolution stimulated emission depletion (STED) microscopy offers significant reduction in sample preparation time and reduced technical challenges for imaging and analysis. Additionally, highly technical challenges associated with replica preparation and transfer on a TEM grid can be overcome by scanning electron microscopy (SEM) imaging. The combination of STED microscopy and platinum replica SEM or TEM provides the highest spatial resolution of plasma membrane proteins and their underlying membrane and is, therefore, a suitable method to study cellular events like endocytosis, membrane trafficking, or membrane tension adaptations.

Investigating protein-membrane interactions using native reverse micelles constructed from naturally sourced lipids

Advancing the study of membrane associated proteins and their interactions is dependent on accurate membrane models. While a variety of membrane models for high-resolution membrane protein study exist, most do not reflect the diversity of lipids found within biological membranes. In this work, we have developed native reverse micelles (nRMs) formulated with lipids from multiple eukaryotic sources, which encapsulate proteins and enable them to interact as they would with a biological membrane. Diverse formulations of nRMs using soy lecithin, porcine brain lipids, or bovine heart lipids combined with n-dodecylphosphocholine were developed and characterized by dynamic light scattering and 31 P-NMR. To optimize protein encapsulation, ubiquitin was used as a standard and protein NMR verified minimal changes to its structure. Peripheral membrane proteins, which bind reversibly to membranes, were encapsulated and include glutathione peroxidase 4 (GPx4), phosphatidylethanolamine-binding protein 1 (PEBP1), and fatty acid binding protein 4 (FABP4). All three proteins showed anticipated interactions with the membrane-like inner surface of the nRMs as assessed by protein NMR. The nRM formulations developed here allow for efficient, high-resolution study of membrane interacting proteins up to and beyond ~21 kDa, in a more biologically relevant context compared to other non-native membrane models. The approach outlined here may be applied to a wide range of lipid extracts, allowing study of a variety of membrane associated proteins in their specific biological context.

SLC12A cryo-EM: analysis of relevant ion binding sites, structural domains, and amino acids

The solute carrier family 12A (SLC12A) superfamily of membrane transporters modulates the movement of cations coupled with chloride across the membrane. In doing so, these cotransporters are involved in numerous aspects of human physiology: cell volume regulation, ion homeostasis, blood pressure regulation, and neurological action potential via intracellular chloride concentration modulation. Their physiological characterization has been largely studied; however, understanding the mechanics of their function and the relevance of structural domains or specific amino acids has been a pending task. In recent years, single-particle cryogenic electron microscopy (cryo-EM) has been successfully applied to members of the SLC12A family including all K+:Cl- cotransporters (KCCs), Na+:K+:2Cl- cotransporter NKCC1, and recently Na+:Cl- cotransporter (NCC); revealing structural elements that play key roles in their function. The present review analyzes the data provided by these cryo-EM reports focusing on structural domains and specific amino acids involved in ion binding, domain interactions, and other important SCL12A structural elements. A comparison of cryo-EM data from NKCC1 and KCCs is presented in the light of the two recent NCC cryo-EM studies, to propose insight into structural elements that might also be found in NCC and are necessary for its proper function. In the final sections, the importance of key coordination residues for substrate specificity and their implication on various pathophysiological conditions and genetic disorders is reviewed, as this could provide the basis to correlate structural elements with the development of novel and selective treatments, as well as mechanistic insight into the function and regulation of cation-coupled chloride cotransporters (CCCs).

Three Decades of REDOR in Protein Science: A Solid-State NMR Technique for Distance Measurement and Spectral Editing

Solid-state NMR (ss-NMR) is a powerful tool to investigate noncrystallizable, poorly soluble molecular systems, such as membrane proteins, amyloids, and cell walls, in environments that closely resemble their physical sites of action. Rotational-echo double resonance (REDOR) is an ss-NMR methodology, which by reintroducing heteronuclear dipolar coupling under magic angle spinning conditions provides intramolecular and intermolecular distance restraints at the atomic level. In addition, REDOR can be exploited as a selection tool to filter spectra based on dipolar couplings. Used extensively as a spectroscopic ruler between isolated spins in site-specifically labeled systems and more recently as a building block in multidimensional ss-NMR pulse sequences allowing the simultaneous measurement of multiple distances, REDOR yields atomic-scale information on the structure and interaction of proteins. By extending REDOR to the determination of 1H-X dipolar couplings in recent years, the limit of measurable distances has reached ~15-20 Å, making it an attractive method of choice for the study of complex biomolecular assemblies. Following a methodological introduction including the most recent implementations, examples are discussed to illustrate the versatility of REDOR in the study of biological systems.

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.

Cryogenic electron ptychographic single particle analysis with wide bandwidth information transfer

Advances in cryogenic transmission electron microscopy have revolutionised the determination of many macromolecular structures at atomic or near-atomic resolution. This method is based on conventional defocused phase contrast imaging. However, it has limitations of weaker contrast for small biological molecules embedded in vitreous ice, in comparison with cryo-ptychography, which shows increased contrast. Here we report a single-particle analysis based on the use of ptychographic reconstruction data, demonstrating that three dimensional reconstructions with a wide information transfer bandwidth can be recovered by Fourier domain synthesis. Our work suggests future applications in otherwise challenging single particle analyses, including small macromolecules and heterogeneous or flexible particles. In addition structure determination in situ within cells without the requirement for protein purification and expression may be possible.

Time-domain proton-detected local-field NMR for molecular structure determination in complex lipid membranes

Proton-detected local-field (PDLF) NMR spectroscopy, using magic-angle spinning and dipolar recoupling, is presently the most powerful experimental technique for obtaining atomistic structural information from small molecules undergoing anisotropic motion. Common examples include peptides, drugs, or lipids in model membranes and molecules that form liquid crystals. The measurements on complex systems are however compromised by the larger number of transients required. Retaining sufficient spectral quality in the direct dimension requires that the indirect time-domain modulation becomes too short for yielding dipolar splittings in the frequency domain. In such cases, the dipolar couplings can be obtained by fitting the experimental data; however ideal models often fail to fit PDLF data properly due to effects of radiofrequency field (RF) spatial inhomogeneity. Here, we demonstrate that by accounting for RF spatial inhomogeneity in the modeling of R-symmetry-based PDLF NMR experiments, the fitting accuracy is improved, facilitating the analysis of the experimental data. In comparison to the analysis of dipolar splittings without any fitting procedure, the accurate modeling of PDLF measurements makes possible three important improvements: the use of shorter experiments that enable the investigation of samples with a higher level of complexity, the measurement of C-H bond order parameters with smaller magnitudes | S CH | and of smaller variations of | S CH | caused by perturbations of the system, and the determination of | S CH | values with small differences from distinct sites having the same chemical shift. The increase in fitting accuracy is demonstrated by comparison with 2 H NMR quadrupolar echo experiments on mixtures of deuterated and non-deuterated dimyristoylphosphatidylcholine (DMPC) and with 1-palmitoyl-2-oleoyl-s n -glycero-3-phosphoethanolamine (POPE) membranes. Accurate modeling of PDLF NMR experiments is highly useful for investigating complex membrane systems. This is exemplified by application of the proposed fitting procedure for the characterization of membranes composed of a brain lipid extract with many distinct lipid types.

AFTM: a database of transmembrane regions in the human proteome predicted by AlphaFold

Transmembrane proteins (TMPs), with diverse cellular functions, are difficult targets for structural determination. Predictions of TMPs and the locations of transmembrane segments using computational methods could be unreliable due to the potential for false positives and false negatives and show inconsistencies across different programs. Recent advances in protein structure prediction methods have made it possible to identify TMPs and their membrane-spanning regions using high-quality structural models. We developed the AlphaFold Transmembrane proteins (AFTM) database of candidate human TMPs by identifying transmembrane regions in AlphaFold structural models of human proteins and their domains using the positioning of proteins in membranes, version 3 program, followed by automatic corrections inspired by manual analysis of the results. We compared our results to annotations from the UniProt database and the Human Transmembrane Proteome (HTP) database. While AFTM did not identify transmembrane regions in some single-pass TMPs, it identified more transmembrane regions for multipass TMPs than UniProt and HTP. AFTM also showed more consistent results with experimental structures, as benchmarked against the Protein Data Bank Transmembrane proteins (PDBTM) database. In addition, some proteins previously annotated as TMPs were suggested to be non-TMPs by AFTM. We report the results of AFTM together with those of UniProt, HTP, TmAlphaFold, PDBTM and Membranome in the online AFTM database compiled as a comprehensive resource of candidate human TMPs with structural models. Database URL http://conglab.swmed.edu/AFTM.

Mesoscale simulations: An indispensable approach to understand biomembranes

Computer simulation techniques form a versatile tool, a computational microscope, for exploring biological processes. This tool has been particularly effective in exploring different features of biological membranes. In recent years, thanks to elegant multiscale simulation schemes, some fundamental limitations of investigations by distinct simulation techniques have been resolved. As a result, we are now capable of exploring processes spanning multiple scales beyond the capacity of any single technique. In this perspective, we argue that mesoscale simulations require more attention and must be further developed to fill evident gaps in a quest toward simulating and modeling living cell membranes.

Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications

Membrane proteins mediate a wide spectrum of biological processes, such as signal transduction and cell communication. Due to the arduous and costly nature inherent to the experimental process, membrane proteins have long been devoid of well-resolved atomic-level tertiary structures and, consequently, the understanding of their functional roles underlying a multitude of life activities has been hampered. Currently, computational tools dedicated to furthering the structure-function understanding are primarily focused on utilizing intelligent algorithms to address a variety of site-wise prediction problems (e.g., topology and interaction sites), but are scattered across different computing sources. Moreover, the recent advent of deep learning techniques has immensely expedited the development of computational tools for membrane protein-related prediction problems. Given the growing number of applications optimized particularly by manifold deep neural networks, we herein provide a review on the current status of computational strategies mainly in membrane protein type classification, topology identification, interaction site detection, and pathogenic effect prediction. Meanwhile, we provide an overview of how the entire prediction process proceeds, including database collection, data pre-processing, feature extraction, and method selection. This review is expected to be useful for developing more extendable computational tools specific to membrane proteins.

Smart de novo Macromolecular Structure Modeling from Cryo-EM Maps

The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, X-ray crystallography has been the main method for structure determination, however, cryogenic electron microscopy (cryo-EM) has increasingly become more popular due to recent advancements in hardware and software. The number of cryo-EM maps deposited in the EMDataResource (formerly EMDatabase) since 2002 has been dramatically increasing and it continues to do so. De novo macromolecular complex modeling is a labor-intensive process, therefore, it is highly desirable to develop software that can automate this process. Here we discuss our automated, data-driven, and artificial intelligence approaches including map processing, feature extraction, modeling building, and target identification. Recently, we have enabled DNA/RNA modeling in our deep learning-based prediction tool, DeepTracer. We have also developed DeepTracer-ID, a tool that can identify proteins solely based on the cryo-EM map. In this paper, we will present our accumulated experiences in developing deep learning-based methods surrounding macromolecule modeling applications.

Conformational plasticity of NaK2K and TREK2 potassium channel selectivity filters

The K+ channel selectivity filter (SF) is defined by TxGYG amino acid sequences that generate four identical K+ binding sites (S1-S4). Only two sites (S3, S4) are present in the non-selective bacterial NaK channel, but a four-site K+-selective SF is obtained by mutating the wild-type TVGDGN SF sequence to a canonical K+ channel TVGYGD sequence (NaK2K mutant). Using single molecule FRET (smFRET), we show that the SF of NaK2K, but not of non-selective NaK, is ion-dependent, with the constricted SF configuration stabilized in high K+ conditions. Patch-clamp electrophysiology and non-canonical fluorescent amino acid incorporation show that NaK2K selectivity is reduced by crosslinking to limit SF conformational movement. Finally, the eukaryotic K+ channel TREK2 SF exhibits essentially identical smFRET-reported ion-dependent conformations as in prokaryotic K+ channels. Our results establish the generality of K+-induced SF conformational stability across the K+ channel superfamily, and introduce an approach to study manipulation of channel selectivity.

Protein model refinement for cryo-EM maps using AlphaFold2 and the DAQ score

As more protein structure models have been determined from cryogenic electron microscopy (cryo-EM) density maps, establishing how to evaluate the model accuracy and how to correct models in cases where they contain errors is becoming crucial to ensure the quality of the structural models deposited in the public database, the PDB. Here, a new protocol is presented for evaluating a protein model built from a cryo-EM map and applying local structure refinement in the case where the model has potential errors. Firstly, model evaluation is performed using a deep-learning-based model-local map assessment score, DAQ, that has recently been developed. The subsequent local refinement is performed by a modified AlphaFold2 procedure, in which a trimmed template model and a trimmed multiple sequence alignment are provided as input to control which structure regions to refine while leaving other more confident regions of the model intact. A benchmark study showed that this protocol, DAQ-refine, consistently improves low-quality regions of the initial models. Among 18 refined models generated for an initial structure, DAQ shows a high correlation with model quality and can identify the best accurate model for most of the tested cases. The improvements obtained by DAQ-refine were on average larger than other existing methods.

Better Cryo-EM Specimen Preparation: How to Deal with the Air-Water Interface?

Cryogenic electron microscopy (cryo-EM) is now one of the most powerful and widely used methods to determine high-resolution structures of macromolecules. A major bottleneck of cryo-EM is to prepare high-quality vitrified specimen, which still faces many practical challenges. During the conventional vitrification process, macromolecules tend to adsorb at the air-water interface (AWI), which is known unfriendly to biological samples. In this review, we outline the nature of AWI and the problems caused by it, such as unpredictable or uneven particle distribution, protein denaturation, dissociation of complex and preferential orientation. We review and discuss the approaches and underlying mechanisms to deal with AWI: 1) Additives, exemplified by detergents, forming a protective layer at AWI and thus preserving the native folds of target macromolecules. 2) Fast vitrification devices based on the idea to freeze in-solution macromolecules before their touching of AWI. 3) Thin layer of continuous supporting films to adsorb macromolecules, and when functionalized with affinity ligands, to specifically anchor the target particles away from the AWI. Among these supporting films, graphene, together with its derivatives, with negligible background noise and mechanical robustness, has emerged as a new generation of support. These strategies have been proven successful in various cases and enable us a better handling of the problems caused by the AWI in cryo-EM specimen preparation.

Characterization of heterogeneity in nanodisc samples using Feret signatures

Nanodiscs have become a popular tool in structure determination of membrane proteins using cryogenic electron microscopy and single particle analysis. However, the structure determination of small membrane proteins remains challenging. When the embedded protein is in the same size range as the nanodisc, the nanodisc can significantly contribute to the alignment and classification during the structure determination process. In those cases, it is crucial to minimize the heterogeneity in the nanodisc preparations to assure maximum accuracy in the classification and alignment steps of single particle analysis. Here, we introduce a new in-silico method for the characterization of nanodisc samples that is based on analyzing the Feret diameter distribution of their particle projection as imaged in the electron microscope. We validated the method with comprehensive simulation studies and show that Feret signatures can detect subtle differences in nanodisc morphologies and composition that might otherwise go unnoticed. We used the method to identify a specific biochemical nanodisc preparation with low size variations, allowing us to obtain a structure of the 23-kDa single-span membrane protein Bcl-xL while embedded in a nanodisc. Feret signature analysis can steer experimental data collection strategies, allowing more efficient use of high-end data collection hardware, as well as image analysis investments in studies where nanodiscs significantly contribute to the total volume of the full molecular species.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Cryo-electron Microscopic Analysis of Single-Pass Transmembrane Receptors

Single-pass transmembrane receptors (SPTMRs) represent a diverse group of integral membrane proteins that are involved in many essential cellular processes, including signal transduction, cell adhesion, and transmembrane transport of materials. Dysregulation of the SPTMRs is linked with many human diseases. Despite extensive efforts in past decades, the mechanisms of action of the SPTMRs remain incompletely understood. One major hurdle is the lack of structures of the full-length SPTMRs in different functional states. Such structural information is difficult to obtain by traditional structural biology methods such as X-ray crystallography and nuclear magnetic resonance (NMR). The recent rapid development of single-particle cryo-electron microscopy (cryo-EM) has led to an exponential surge in the number of high-resolution structures of integral membrane proteins, including SPTMRs. Cryo-EM structures of SPTMRs solved in the past few years have tremendously improved our understanding of how SPTMRs function. In this review, we will highlight these progresses in the structural studies of SPTMRs by single-particle cryo-EM, analyze important structural details of each protein involved, and discuss their implications on the underlying mechanisms. Finally, we also briefly discuss remaining challenges and exciting opportunities in the field.

Meta-Analysis of the Expansion in the Field of Structural Biology of ABC Transporters

ABC transporters are molecular machines which power the solute transport using ATP hydrolysis. The structural biology of ABC transporters has been exploding for the last few years, and this study explores timelines and trends for various attributes such as structural tools, resolution, fold, sources, and group leaders. This study also evidences the significance of mammalian expression systems, advancements in structural biology tools, and the developing interest of group leaders across the world in the remarkably progressing field. The field started in 2002 and bloomed in 2016, and COVID years were really productive to the field. Specifically, the study explores 337 structures of 58 unique ABC transporters deposited in the PDB database from which P-glycoprotein has the largest number of structures. Approximately, 62% of total structures are determined at the resolution of 3-4 Å and 53% of structures belong to fold IV type. With progressive advancements in the field, the field is shifting from prokaryotic to eukaryotic sources and X-ray crystallography to cryoelectron microscopy. In the nutshell, this study uniquely provides the detailed snapshot of the field of structural biology of ABC transporters with real-time data.

Intramolecular covalent bonds in Gram-positive bacterial surface proteins

Gram-positive bacteria experience considerable mechanical perturbation when adhering to host surfaces during colonization and infection. They have evolved various adhesion proteins that are mechanically robust to ensure strong surface adhesion. Recently, it was discovered that these adhesion proteins contain rare, extra intramolecular covalent bonds that stabilize protein structures and participate in surface bonding. These intramolecular covalent bonds include isopeptides, thioesters, and ester bonds, which often form spontaneously without the need for additional enzymes. With the development of single-molecule force spectroscopy techniques, the detailed mechanical roles of these intramolecular covalent bonds have been revealed. In this review, we summarize the recent advances in this area of research, focusing on the link between the mechanical stability and function of these covalent bonds in Gram-positive bacterial surface proteins. We also highlight the potential impact of these discoveries on the development of novel antibiotics and chemical biology tools.

Evolutionary balance between foldability and functionality of a glucose transporter

Despite advances in resolving the structures of multi-pass membrane proteins, little is known about the native folding pathways of these complex structures. Using single-molecule magnetic tweezers, we here report a folding pathway of purified human glucose transporter 3 (GLUT3) reconstituted within synthetic lipid bilayers. The N-terminal major facilitator superfamily (MFS) fold strictly forms first, serving as a structural template for its C-terminal counterpart. We found polar residues comprising the conduit for glucose molecules present major folding challenges. The endoplasmic reticulum membrane protein complex facilitates insertion of these hydrophilic transmembrane helices, thrusting GLUT3's microstate sampling toward folded structures. Final assembly between the N- and C-terminal MFS folds depends on specific lipids that ease desolvation of the lipid shells surrounding the domain interfaces. Sequence analysis suggests that this asymmetric folding propensity across the N- and C-terminal MFS folds prevails for metazoan sugar porters, revealing evolutionary conflicts between foldability and functionality faced by many multi-pass membrane proteins.

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.

Recent Technical Advances in Sample Preparation for Single-Particle Cryo-EM

Cryo-sample preparation is a vital step in the process of obtaining high-resolution structures of macromolecules by using the single-particle cryo–electron microscopy (cryo-EM) method; however, cryo-sample preparation is commonly hampered by high uncertainty and low reproducibility. Specifically, the existence of air-water interfaces during the sample vitrification process could cause protein denaturation and aggregation, complex disassembly, adoption of preferred orientations, and other serious problems affecting the protein particles, thereby making it challenging to pursue high-resolution 3D reconstruction. Therefore, sample preparation has emerged as a critical research topic, and several new methods for application at various preparation stages have been proposed to overcome the aforementioned hurdles. Here, we summarize the methods developed for enhancing the quality of cryo-samples at distinct stages of sample preparation, and we offer insights for developing future strategies based on diverse viewpoints. We anticipate that cryo-sample preparation will no longer be a limiting step in the single-particle cryo-EM field as increasing numbers of methods are developed in the near future, which will ultimately benefit the entire research community.

Deciphering a hexameric protein complex with Angstrom optical resolution

Cryogenic optical localization in three dimensions (COLD) was recently shown to resolve up to four binding sites on a single protein. However, because COLD relies on intensity fluctuations that result from the blinking behavior of fluorophores, it is limited to cases where individual emitters show different brightness. This significantly lowers the measurement yield. To extend the number of resolved sites as well as the measurement yield, we employ partial labeling and combine it with polarization encoding in order to identify single fluorophores during their stochastic blinking. We then use a particle classification scheme to identify and resolve heterogenous subsets and combine them to reconstruct the three-dimensional arrangement of large molecular complexes. We showcase this method (polarCOLD) by resolving the trimer arrangement of proliferating cell nuclear antigen (PCNA) and six different sites of the hexamer protein Caseinolytic Peptidase B (ClpB) of Thermus thermophilus in its quaternary structure, both with Angstrom resolution. The combination of polarCOLD and single-particle cryogenic electron microscopy (cryoEM) promises to provide crucial insight into intrinsic heterogeneities of biomolecular structures. Furthermore, our approach is fully compatible with fluorescent protein labeling and can, thus, be used in a wide range of studies in cell and membrane biology.

Membrane-Mimicking Reverse Micelles for High-Resolution Interfacial Study of Proteins and Membranes

Despite substantial advances, the study of proteins interacting with membranes remains a significant challenge. While integral membrane proteins have been a major focus of recent efforts, peripheral membrane proteins (PMPs) and their interactions with membranes and lipids have far less high-resolution information available. Their small size and the dynamic nature of their interactions have stalled detailed interfacial study using structural methods like cryo-EM and X-ray crystallography. A major roadblock for the structural analysis of PMP interactions is limitations in membrane models to study the membrane recruited state. Commonly used membrane mimics such as liposomes, bicelles, nanodiscs, and micelles are either very large or composed of non-biological detergents, limiting their utility for the NMR study of PMPs. While there have been previous successes with integral and peripheral membrane proteins, currently employed reverse micelle (RM) compositions are optimized for their inertness with proteins rather than their ability to mimic membranes. Applying more native, membrane-like lipids and surfactants promises to be a valuable advancement for the study of interfacial interactions between proteins and membranes. Here, we describe the development of phosphocholine-based RM systems that mimic biological membranes and are compatible with high-resolution protein NMR. We demonstrate new formulations that are able to encapsulate the model soluble protein, ubiquitin, with minimal perturbations of the protein structure. Furthermore, one formula, DLPC:DPC, allowed the encapsulation of the PMPs glutathione peroxidase 4 (GPx4) and phosphatidylethanolamine-binding protein 1 (PEBP1) and enabled the embedment of these proteins, matching the expected interactions with biological membranes. Dynamic light scattering and small-angle X-ray scattering characterization of the RMs reveals small, approximately spherical, and non-aggregated particles, a prerequisite for protein NMR and other avenues of study. The formulations presented here represent a new tool for the study of elusive PMP interactions and other membrane interfacial investigations.

Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins

One of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures.

The distribution of residues on protein surfaces is largely determined by the surrounding environment. For soluble proteins, most of the residues on the outer surface are hydrophilic, and people use the quantity “solvent accessibility” to describe and predict these surface residues. In contrast, for membrane proteins that are embedded in a lipid bilayer, many of their surface residues are hydrophobic and membrane-contacting, but there is yet a widely-accepted quantity for the description or prediction of this characteristic property. Here, we propose a new quantity termed “membrane contact probability (MCP)”, which can be used to describe and predict the membrane-contacting surface residues of proteins. We also propose a machine learning-based method to predict MCP from protein sequences, utilizing the dataset generated by physics-based computer simulations. We demonstrate that a quantity such as MCP is helpful for protein structure prediction, and we believe that it will find broad applications in the structure and function studies of membrane proteins.

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

High-resolution Single-molecule Magnetic Tweezers

Single-molecule magnetic tweezers deliver magnetic force and torque to single target molecules, permitting the study of dynamic changes in biomolecular structures and their interactions. Because the magnetic tweezer setups can generate magnetic fields that vary slowly over tens of millimeters-far larger than the nanometer scale of the single molecule events being observed-this technique can maintain essentially constant force levels during biochemical experiments while generating a biologically meaningful force on the order of 1-100 pN. When using bead-tether constructs to pull on single molecules, smaller magnetic beads and shorter submicrometer tethers improve dynamic response times and measurement precision. In addition, employing high-speed cameras, stronger light sources, and a graphics programming unit permits true high-resolution single-molecule magnetic tweezers that can track nanometer changes in target molecules on a millisecond or even submillisecond time scale. The unique force-clamping capacity of the magnetic tweezer technique provides a way to conduct measurements under near-equilibrium conditions and directly map the energy landscapes underlying various molecular phenomena. High-resolution single-molecule magnetic tweezers can thus be used to monitor crucial conformational changes in single-protein molecules, including those involved in mechanotransduction and protein folding. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Insights into lipid-protein interactions from computer simulations

Lipid-protein interactions play an important direct role in the function of many membrane proteins. We argue they are key players in membrane structure, modulate membrane proteins in more subtle ways than direct binding, and are important for understanding the mechanism of classes of hydrophobic drugs. By directly comparing membrane proteins from different families in the same, complex lipid mixture, we found a unique lipid environment for every protein. Extending this work, we identified both differences and similarities in the lipid environment of GPCRs, dependent on which family they belong to and in some cases their conformational state, with particular emphasis on the distribution of cholesterol. More recently, we have been studying modes of coupling between protein conformation and local membrane properties using model proteins. In more applied approaches, we have used similar methods to investigate specific hypotheses on interactions of lipid and lipid-like molecules with ion channels. We conclude this perspective with some considerations for future work, including a new more sophisticated coarse-grained force field (Martini 3), an interactive visual exploration framework, and opportunities to improve sampling.

Untangling the complexity of membrane protein folding

Delineating the folding steps of helical-bundle membrane proteins has been a challenging task. Many questions remain unanswered, including the conformation and stability of the states populated during folding, the shape of the energy barriers between the states, and the role of lipids as a solvent in mediating the folding. Recently, theoretical frames have matured to a point that permits detailed dissection of the folding steps, and advances in experimental techniques at both single-molecule and ensemble levels enable selective modulation of specific steps for quantitative determination of the folding energy landscapes. We also discuss how lipid molecules would play an active role in shaping the folding energy landscape of membrane proteins, and how folding of multi-domain membrane proteins can be understood based on our current knowledge. We conclude this review by offering an outlook for emerging questions in the study of membrane protein folding.

Production and Preparation of Isotopically Labeled Human Membrane Proteins in Pichia pastoris for Fast-MAS-NMR Analyses

Membrane proteins (MPs) comprise about one-third of the human proteome, playing critical roles in many physiological processes and associated disorders. Consistently, they represent one of the largest classes of targets for the pharmaceutical industry. Their study at the molecular level is however particularly challenging, resulting in a severe lack of structural and dynamic information that is hindering their detailed functional characterization and the identification of novel potent drug candidates.Magic Angle Spinning (MAS) NMR is a reliable and efficient method for the determination of protein structures and dynamics and for the identification of ligand binding sites and equilibria. MAS-NMR is particularly well suited for MPs since they can be directly analysed in a native-like lipid bilayer environment but used to require aggravating large amounts of isotope enriched material. The frequent toxicity of human MP overexpression in bacterial cultures poses an additional hurdle, resulting in the need for alternative (and often more costly) expression systems. The recent development of very fast (up to 150 kHz) MAS probes has revolutionized the field of biomolecular solid-state NMR enabling higher spectral resolution with significant reduction of the required sample, rendering eukaryotic expression systems cost-effective.Here is presented a set of accessible procedures validated for the production and preparation of eukaryotic MPs for Fast-MAS ¹H-detected NMR analysis. The methodology is illustrated with the human copper uptake protein hCTR1 recombinantly produced and ¹³C-¹⁵N uniformly labeled with the versatile and affordable Pichia pastoris system. Subsequent purification procedures allow the recovery of mg amounts that are then reconstituted into liposome formulations compatible with solid-state NMR handling and analysis.

Insights into the mechanism of high lipid–detergent crystallization of membrane proteins

Obtaining well diffracting crystals of membrane proteins is often challenging, but chances can be improved by crystallizing them in lipidic conditions that mimic their natural membrane environments. One approach is the high lipid–detergent (HiLiDe) method, which works by mixing the target protein with high concentrations of lipid and detergent prior to crystallization. Although this approach is convenient and flexible, understanding the effects of systematically varying lipid/detergent ratios and a characterization of the lipid phases that form during crystallization would be useful. Here, a HiLiDe phase diagram is reported for the model membrane protein MhsT, which tracks the precipitation and crystallization zones as a function of lipid and detergent concentrations, and is augmented with data on crystal sizes and diffraction properties. Additionally, the crystallization of SERCA1a solubilized directly with native lipids is characterized as a function of detergent concentration. Finally, HiLiDe crystallization drops are analysed with transmission electron microscopy, which among other features reveals liposomes, stacked lamellae that may represent crystal precursors, and mature crystals with clearly discernible packing arrangements. The results emphasize the significance of optimizing lipid/detergent ratios over broad ranges and provide insights into the mechanism of HiLiDe crystallization.

Towards a native environment: structure and function of membrane proteins in lipid bilayers by NMR

Solid-state NMR (ssNMR) is a versatile technique that can be used for the characterization of various materials, ranging from small molecules to biological samples, including membrane proteins. ssNMR can probe both the structure and dynamics of membrane proteins, revealing protein function in a near-native lipid bilayer environment. The main limitation of the method is spectral resolution and sensitivity, however recent developments in ssNMR hardware, including the commercialization of 28 T magnets (1.2 GHz proton frequency) and ultrafast MAS spinning (<100 kHz) promise to accelerate acquisition, while reducing sample requirement, both of which are critical to membrane protein studies. Here, we review recent advances in ssNMR methodology used for structure determination of membrane proteins in native and mimetic environments, as well as the study of protein functions such as protein dynamics, and interactions with ligands, lipids and cholesterol.

Cyclodextrins for structural and functional studies of mechanosensitive channels

Mechanosensitive (MS) channels that are activated by the 'force-from-lipids' (FFL) principle rest in the membrane in a closed state but open a transmembrane pore in response to changes in the transmembrane pressure profile. The molecular implementations of the FFL principle vary widely between different MS channel families. The function of MS channels is often studied by patch-clamp electrophysiology, in which mechanical force or amphipathic molecules are used to activate the channels. Structural studies of MS channels in states other than the closed resting state typically relied on the use of mutant channels. Cyclodextrins (CDs) were recently introduced as a relatively easy and convenient approach to generate membrane tension. The principle is that CDs chelate hydrophobic molecules and can remove lipids from membranes, thus forcing the remaining lipids to cover more surface area and creating tension for membrane proteins residing in the membranes. CDs can be used to study the structure of MS channels in a membrane under tension by using single-particle cryo-electron microscopy to image the channels in nanodiscs after incubation with CDs as well as to characterize the function of MS channels by using patch-clamp electrophysiology to record the effect of CDs on channels inserted into membrane patches excised from proteoliposomes. Importantly, because incubation of membrane patches with CDs results in the activation of MscL, an MS channel that opens only shortly before membrane rupture, CD-mediated lipid removal appears to generate sufficient force to open most if not all types of MS channels that follow the FFL principle.

Modeling lipid-protein interactions for coarse-grained lipid and Cα protein models

Biological membranes that play major roles in diverse functions are composed of numerous lipids and proteins, making them an important target for coarse-grained (CG) molecular dynamics (MD) simulations. Recently, we have developed the CG implicit solvent lipid force field (iSoLF) that has a resolution compatible with the widely used Cα protein representation [D. Ugarte La Torre and S. Takada, J. Chem. Phys. 153, 205101 (2020)]. In this study, we extended it and developed a lipid-protein interaction model that allows the combination of the iSoLF and the Cα protein force field, AICG2+. The hydrophobic-hydrophilic interaction is modeled as a modified Lennard-Jones potential in which parameters were tuned partly to reproduce the experimental transfer free energy and partly based on the free energy profile normal to the membrane surface from previous all-atom MD simulations. Then, the obtained lipid-protein interaction is tested for the configuration and placement of transmembrane proteins, water-soluble proteins, and peripheral proteins, showing good agreement with prior knowledge. The interaction is generally applicable and is implemented in the publicly available software, CafeMol.

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.

Relative Affinities of Protein-Cholesterol Interactions from Equilibrium Molecular Dynamics Simulations

Specific interactions of lipids with membrane proteins contribute to protein stability and function. Multiple lipid interactions surrounding a membrane protein are often identified in molecular dynamics (MD) simulations and are, increasingly, resolved in cryo-electron microscopy (cryo-EM) densities. Determining the relative importance of specific interaction sites is aided by determination of lipid binding affinities using experimental or simulation methods. Here, we develop a method for determining protein-lipid binding affinities from equilibrium coarse-grained MD simulations using binding saturation curves, designed to mimic experimental protocols. We apply this method to directly obtain affinities for cholesterol binding to multiple sites on a range of membrane proteins and compare our results with free energies obtained from density-based equilibrium methods and with potential of mean force calculations, getting good agreement with respect to the ranking of affinities for different sites. Thus, our binding saturation method provides a robust, high-throughput alternative for determining the relative consequence of individual sites seen in, e.g., cryo-EM derived membrane protein structures surrounded by an array of ancillary lipid densities.

An improved fluorescent noncanonical amino acid for measuring conformational distributions using time-resolved transition metal ion FRET

With the recent explosion in high-resolution protein structures, one of the next frontiers in biology is elucidating the mechanisms by which conformational rearrangements in proteins are regulated to meet the needs of cells under changing conditions. Rigorously measuring protein energetics and dynamics requires the development of new methods that can resolve structural heterogeneity and conformational distributions. We have previously developed steady-state transition metal ion fluorescence resonance energy transfer (tmFRET) approaches using a fluorescent noncanonical amino acid donor (Anap) and transition metal ion acceptor to probe conformational rearrangements in soluble and membrane proteins. Here, we show that the fluorescent noncanonical amino acid Acd has superior photophysical properties that extend its utility as a donor for tmFRET. Using maltose-binding protein (MBP) expressed in mammalian cells as a model system, we show that Acd is comparable to Anap in steady-state tmFRET experiments and that its long, single-exponential lifetime is better suited for probing conformational distributions using time-resolved FRET. These experiments reveal differences in heterogeneity in the apo and holo conformational states of MBP and produce accurate quantification of the distributions among apo and holo conformational states at subsaturating maltose concentrations. Our new approach using Acd for time-resolved tmFRET sets the stage for measuring the energetics of conformational rearrangements in soluble and membrane proteins in near-native conditions.

Graphene Oxide-Supported Microwell Grids for Preparing Cryo-EM Samples with Controlled Ice Thickness

Cryogenic-electron microscopy (cryo-EM) is the preferred method to determine 3D structures of proteins and to study diverse material systems that intrinsically have radiation or air sensitivity. Current cryo-EM sample preparation methods provide limited control over the sample quality, which limits the efficiency and high throughput of 3D structure analysis. This is partly because it is difficult to control the thickness of the vitreous ice that embeds specimens, in the range of nanoscale, depending on the size and type of materials of interest. Thus, there is a need for fine regulation of the thickness of vitreous ice to deliver consistent high signal-to-noise ratios for low-contrast biological specimens. Herein, an advanced silicon-chip-based device is developed which has a regular array of micropatterned holes with a graphene oxide (GO) window on freestanding silicon nitride (Si_x N_y ). Accurately regulated depths of micropatterned holes enable precise control of vitreous ice thickness. Furthermore, GO window with affinity for biomolecules can facilitate concentration of the sample molecules at a higher level. Incorporation of micropatterned chips with a GO window enhances cryo-EM imaging for various nanoscale biological samples including human immunodeficiency viral particles, groEL tetradecamers, apoferritin octahedral, aldolase homotetramer complexes, and tau filaments, as well as inorganic materials.

Catalytic machinery of methane oxidation in particulate methane monooxygenase (pMMO)

In this focused review, we portray the recently reported 2.5 Å cyro-EM structure of the particulate methane monooxygenase (pMMO) from M. capsulatus (Bath). The structure of the functional holo-pMMO near atomic resolution has uncovered the sites of the copper cofactors including the location of the active site in the enzyme. The three coppers seen in the original X-ray crystal structures of the enzyme are now augmented by additional coppers in the transmembrane domain as well as in the water-exposed C-terminal subdomain of the PmoB subunit. The cryo-EM structure offers the first glimpse of the catalytic machinery capable of methane oxidation with high selectivity and efficiency. The findings are entirely consistent with the biochemical and biophysical findings previously reported in the literature, including the chemistry of hydrocarbon hydroxylation, regeneration of the catalyst for multiple turnovers, and the mechanism of aborting non-productive cycles to ensure kinetic competence.

Structure and efflux mechanism of the yeast pleiotropic drug resistance transporter Pdr5

Pdr5, a member of the extensive ABC transporter superfamily, is representative of a clinically relevant subgroup involved in pleiotropic drug resistance. Pdr5 and its homologues drive drug efflux through uncoupled hydrolysis of nucleotides, enabling organisms such as baker’s yeast and pathogenic fungi to survive in the presence of chemically diverse antifungal agents. Here, we present the molecular structure of Pdr5 solved with single particle cryo-EM, revealing details of an ATP-driven conformational cycle, which mechanically drives drug translocation through an amphipathic channel, and a clamping switch within a conserved linker loop that acts as a nucleotide sensor. One half of the transporter remains nearly invariant throughout the cycle, while its partner undergoes changes that are transmitted across inter-domain interfaces to support a peristaltic motion of the pumped molecule. The efflux model proposed here rationalises the pleiotropic impact of Pdr5 and opens new avenues for the development of effective antifungal compounds.

Pdr5 is an ABC transporter conferring multidrug resistance to pathogenic fungi. Here, structural analysis of Pdr5 provides insights into the transport mechanism featuring asymmetric movements of Pdr5 domain and enabling efflux of a broad spectrum of compounds.