Biophysical dissection of membrane proteins

Validation of de novo designed water-soluble and transmembrane β-barrels by in silico folding and melting

In silico validation of de novo designed proteins with deep learning (DL)-based structure prediction algorithms has become mainstream. However, formal evidence of the relationship between a high-quality predicted model and the chance of experimental success is lacking. We used experimentally characterized de novo water-soluble and transmembrane β-barrel designs to show that AlphaFold2 and ESMFold excel at different tasks. ESMFold can efficiently identify designs generated based on high-quality (designable) backbones. However, only AlphaFold2 can predict which sequences have the best chance of experimentally folding among similar designs. We show that ESMFold can generate high-quality structures from just a few predicted contacts and introduce a new approach based on incremental perturbation of the prediction ("in silico melting"), which can reveal differences in the presence of favorable contacts between designs. This study provides a new insight on DL-based structure prediction models explainability and on how they could be leveraged for the design of increasingly complex proteins; in particular membrane proteins which have historically lacked basic in silico validation tools.

Protein engineering of pores for separation, sensing, and sequencing

Proteins are critical to cellular function and survival. They are complex molecules with precise structures and chemistries, which allow them to serve diverse functions for maintaining overall cell homeostasis. Since the discovery of the first enzyme in 1833, a gamut of advanced experimental and computational tools has been developed and deployed for understanding protein structure and function. Recent studies have demonstrated the ability to redesign/alter natural proteins for applications in industrial processes of interest and to make customized, novel synthetic proteins in the laboratory through protein engineering. We comprehensively review the successes in engineering pore-forming proteins and correlate the amino acid-level biochemistry of different pore modification strategies to the intended applications limited to nucleotide/peptide sequencing, single-molecule sensing, and precise molecular separations.

Entangled Motifs in Membrane Protein Structures

Entangled motifs are found in one-third of protein domain structures, a reference set that contains mostly globular proteins. Their properties suggest a connection with co-translational folding. Here, we wish to investigate the presence and properties of entangled motifs in membrane protein structures. From existing databases, we build a non-redundant data set of membrane protein domains, annotated with the monotopic/transmembrane and peripheral/integral labels. We evaluate the presence of entangled motifs using the Gaussian entanglement indicator. We find that entangled motifs appear in one-fifth of transmembrane and one-fourth of monotopic proteins. Surprisingly, the main features of the distribution of the values of the entanglement indicator are similar to the reference case of general proteins. The distribution is conserved across different organisms. Differences with respect to the reference set emerge when considering the chirality of entangled motifs. Although the same chirality bias is found for single-winding motifs in both membrane and reference proteins, the bias is reversed, strikingly, for double-winding motifs only in the reference set. We speculate that these observations can be rationalized in terms of the constraints exerted on the nascent chain by the co-translational bio-genesis machinery, which is different for membrane and globular proteins.

The expression characteristics of transmembrane protein genes in pancreatic ductal adenocarcinoma through comprehensive analysis of bulk and single-cell RNA sequence

Background

Transmembrane (TMEM) protein genes are a class of proteins that spans membranes and function to many physiological processes. However, there is very little known about TMEM gene expression, especially in cancer tissue. Using single-cell and bulk RNA sequence may facilitate the understanding of this poorly characterized protein genes in PDAC.

Methods

We selected the TMEM family genes through the Human Protein Atlas and characterized their expression by single-cell and bulk transcriptomic datasets. Identification of the key TMEM genes was performed through three machine learning algorithms: LASSO, SVM-RFE and RF-SRC. Then, we established TMEM gene riskscore and estimate its implication in predicting survival and response to systematic therapy. Additionally, we explored the difference and impact of TMEM gene expression in PDAC through immunohistochemistry and cell line research.

Results

5 key TMEM genes (ANO1, TMEM59, TMEM204, TMEM205, TMEM92) were selected based on the single-cell analysis and machine learning survival outcomes. Patients stratified into the high and low-risk groups based on TMEM riskscore, were observed with distinct overall survival in internal and external datasets. Moreover, through bulk RNA-sequence and immunohistochemical staining we verified the protein expression of TMEM genes in PDAC and revealed TMEM92 as an essential regulator of pancreatic cancer cell proliferation, migration, and invasion.

Conclusion

Our study on TMEM gene expression and behavior in PDAC has revealed unique characteristics, offering potential for precise therapeutic approaches. Insights into molecular mechanisms expand understanding of PDAC complexity and TMEM gene roles. Such knowledge may inform targeted therapy development, benefiting patients.

May the proton motive force be with you: A plant transporter review

As our ecosystems experience challenges associated with climate change, an improved understanding of the fundamental biochemical processes governing plant physiology is needed. Strikingly, current structural information on plant membrane transporters is severely limited compared to other kingdoms of life, with only 18 unique structures in total. To advance future breakthroughs and insight in plant cell molecular biology, structural knowledge of membrane transporters is indispensable. This review summarizes the current status of structural knowledge in the plant membrane transporter field. Plants utilize the proton motive force (PMF) to drive secondary active transport. We discuss the PMF, how it relates to secondary active transport and provide a classification of PMF driven secondary active transport, discussing recently published structures of symporters, antiporters, and uniporters from plants.

Comprehensive classification of proteins based on structures that engage lipids by COMPOSEL

Structures can now be predicted for any protein using programs like AlphaFold and Rosetta, which rely on a foundation of experimentally determined structures of architecturally diverse proteins. The accuracy of such artificial intelligence and machine learning (AI/ML) approaches benefits from the specification of restraints which assist in navigating the universe of folds to converge on models most representative of a given protein's physiological structure. This is especially pertinent for membrane proteins, with structures and functions that depend on their presence in lipid bilayers. Structures of proteins in their membrane environments could conceivably be predicted from AI/ML approaches with user-specificized parameters that describe each element of the architecture of a membrane protein accompanied by its lipid environment. We propose the Classification Of Membrane Proteins based On Structures Engaging Lipids (COMPOSEL), which builds on existing nomenclature types for monotopic, bitopic, polytopic and peripheral membrane proteins as well as lipids. Functional and regulatory elements are also defined in the scripts, as shown with membrane fusing synaptotagmins, multidomain PDZD8 and Protrudin proteins that recognize phosphoinositide (PI) lipids, the intrinsically disordered MARCKS protein, caveolins, the β barrel assembly machine (BAM), an adhesion G-protein coupled receptor (aGPCR) and two lipid modifying enzymes - diacylglycerol kinase DGKε and fatty aldehyde dehydrogenase FALDH. This demonstrates how COMPOSEL communicates lipid interactivity as well as signaling mechanisms and binding of metabolites, drug molecules, polypeptides or nucleic acids to describe the operations of any protein. Moreover COMPOSEL can be scaled to express how genomes encode membrane structures and how our organs are infiltrated by pathogens such as SARS-CoV-2.

Towards de novo design of transmembrane α-helical assemblies using structural modelling and molecular dynamics simulation

Computational de novo protein design involves iterative processes consisting of amino acid sequence design, structural modelling and scoring, and design validation by synthesis and experimental characterisation. Recent advances in protein structure prediction and modelling methods have enabled the highly efficient and accurate design of water-soluble proteins. However, the design of membrane proteins remains a major challenge. To advance membrane protein design, considering the higher complexity of membrane protein folding, stability, and dynamic interactions between water, ions, lipids, and proteins is an important task. For introducing explicit solvents and membranes to these design methods, all-atom molecular dynamics (MD) simulations of designed proteins provide useful information that cannot be obtained experimentally. In this review, we first describe two major approaches to designing transmembrane α-helical assemblies, consensus and de novo design. We further illustrate recent MD studies of membrane protein folding related to protein design, as well as advanced treatments in molecular models and conformational sampling techniques in the simulations. Finally, we discuss the possibility to introduce MD simulations after the existing static modelling and screening of design decoys as an additional step for refinement of the design, which considers membrane protein folding dynamics and interactions with explicit 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.

Transmembrane Membrane Readers form a Novel Class of Proteins That Include Peripheral Phosphoinositide Recognition Domains and Viral Spikes

Membrane proteins are broadly classified as transmembrane (TM) or peripheral, with functions that pertain to only a single bilayer at a given time. Here, we explicate a class of proteins that contain both transmembrane and peripheral domains, which we dub transmembrane membrane readers (TMMRs). Their transmembrane and peripheral elements anchor them to one bilayer and reversibly attach them to another section of bilayer, respectively, positioning them to tether and fuse membranes while recognizing signals such as phosphoinositides (PIs) and modifying lipid chemistries in proximity to their transmembrane domains. Here, we analyze full-length models from AlphaFold2 and Rosetta, as well as structures from nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, using the Membrane Optimal Docking Area (MODA) program to map their membrane-binding surfaces. Eukaryotic TMMRs include phospholipid-binding C1, C2, CRAL-TRIO, FYVE, GRAM, GTPase, MATH, PDZ, PH, PX, SMP, StART and WD domains within proteins including protrudin, sorting nexins and synaptotagmins. The spike proteins of SARS-CoV-2 as well as other viruses are also TMMRs, seeing as they are anchored into the viral membrane while mediating fusion with host cell membranes. As such, TMMRs have key roles in cell biology and membrane trafficking, and include drug targets for diseases such as COVID-19.

Identification and subcellular localization analysis of membrane protein Ycf 1 in the microsporidian Nosema bombycis

Microsporidia are obligate intracellular parasites that can infect a wide range of vertebrates and invertebrates including humans and insects, such as silkworm and bees. The microsporidium Nosema bombycis can cause pebrine in Bombyx mori, which is the most destructive disease in the sericulture industry. Although membrane proteins are involved in a wide range of cellular functions and part of many important metabolic pathways, there are rare reports about the membrane proteins of microsporidia up to now. We screened a putative membrane protein Ycf 1 from the midgut transcriptome of the N. bombycis-infected silkworm. Gene cloning and bioinformatics analysis showed that the Ycf 1 gene contains a complete open reading frame (ORF) of 969 bp in length encoding a 322 amino acid polypeptide that has one signal peptide and one transmembrane domain. Indirect immunofluorescence results showed that Ycf 1 protein is distributed on the plasma membrane. Expression pattern analysis showed that the Ycf 1 gene expressed in all developmental stages of N. bombycis. Knockdown of the Ycf 1 gene by RNAi effectively inhibited the proliferation of N. bombycis. These results indicated that Ycf 1 is a membrane protein and plays an important role in the life cycle of N. bombycis.

RCSB Protein Data Bank: improved annotation, search and visualization of membrane protein structures archived in the PDB

MOTIVATION

Membrane proteins are encoded by approximately one fifth of human genes but account for more than half of all US FDA approved drug targets. Thanks to new technological advances, the number of membrane proteins archived in the PDB is growing rapidly. However, automatic identification of membrane proteins or inference of membrane location is not a trivial task.

RESULTS

We present recent improvements to the RCSB Protein Data Bank web portal (RCSB PDB, rcsb.org) that provide a wealth of new membrane protein annotations integrated from four external resources: OPM, PDBTM, MemProtMD and mpstruc. We have substantially enhanced the presentation of data on membrane proteins. The number of membrane proteins with annotations available on rcsb.org was increased by ∼80%. Users can search for these annotations, explore corresponding tree hierarchies, display membrane segments at the 1D amino acid sequence level, and visualize the predicted location of the membrane layer in 3D.

AVAILABILITY AND IMPLEMENTATION

Annotations, search, tree data and visualization are available at our rcsb.org web portal. Membrane visualization is supported by the open-source Mol* viewer (molstar.org and github.com/molstar/molstar).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular dynamics study of the internalization of cell-penetrating peptides containing unnatural amino acids across membranes

Peptide-based delivery systems that deliver target molecules into cells have been gaining traction. These systems need cell-penetrating peptides (CPPs), which have the remarkable ability to penetrate into biological membranes and help internalize different cargoes into cells through the cell membranes. The molecular internalization mechanism and structure-function relationships of CPPs are not clear, although the incorporation of nonproteinogenic amino acids such as α-aminoisobutyric acid (Aib) has been reported to increase their helicity, biostability and penetration efficiencies. Here, we used molecular dynamics to study two Aib-containing CPPs, poly(LysAibAla)₃ (KAibA) and poly(LysAibGly)₃ (KAibG), that previously showed high cell internalization efficiency. KAibA and KAibG displayed the lowest internalization energies among the studied CPPs, showing distinct internalization mechanisms depending on the lipid composition of the model membranes. The presence of Aib residues allows these CPPs to adopt amphipathic folding to efficiently penetrate through the membranes. Elucidating how Aib incorporation affects CPP-membrane binding and interactions is beneficial for the design of CPPs for efficient intracellular delivery.

Aberrant expression of TMEM205 signaling promotes platinum resistance in ovarian cancer: An implication for the antitumor potential of DAP compound

INTRODUCTION

TMEM205 is a novel transmembrane protein associated with platinum resistance (PR) in epithelial ovarian carcinoma (OC), however, the specific mechanisms associated with this resistance remain to be elucidated.

METHODS

TMEM205 expression was evaluated in platinum-sensitive (PS) versus platinum resistant (PR) ovarian cancer cell lines and patient serum/tissues. Exosomal efflux of platinum was evaluated with inductively coupled plasma mass spectrometry (ICP-MS) after pre-treatment with small molecule inhibitors (L-2663/L-2797) of TMEM205 prior to treatment with platinum. Cytotoxicity of combination treatment was confirmed in vitro and in an in vivo model.

RESULTS

TMEM205 expression was 10-20 fold higher in PR compared to PS ovarian cancer cell lines, serum samples, and tissues. Co-localization with CD1B was confirmed by in-situ proximity ligation assay suggesting that TMEM205 may mediate PR via the exosomal pathway. Exosomal secretion was significantly increased 5-10 fold in PR cell lines after treatment with carboplatin compared to PS cell lines. Pre-treatment with L-2663 prior to carboplatin resulted in significantly increased intracellular concentration of fluorescently-labeled cisplatin and decreased exosomal efflux of platinum. Decreased cell survival and tumor growth in vitro and in vivo was observed when PR cells were treated with a combination of L-2663 with carboplatin compared to carboplatin alone.

CONCLUSION

TMEM205 appears to be involved in the development of PR in ovarian cancer through the exosomal efflux of platinum agents. This study provides pre-clinical evidence that TMEM205 could serve as a possible biomarker for PR as well as a therapeutic target in combination with platinum agents.

Exploring the Topology of Cytoplasmic Membrane Proteins Involved in Lipopolysaccharide Biosynthesis by in Silico and Biochemical Analyses

In the absence of a tri-dimensional structure, revealing the topology of a membrane protein provides relevant information to identify the number and orientation of transmembrane helices and the localization of critical amino acid residues, contributing to a better understanding of function and intermolecular associations. Topology can be predicted in silico by bioinformatic analysis or solved by biochemical methods. In this chapter, we describe a pipeline employing bioinformatic approaches for the prediction of membrane protein topology, followed by experimental validation through the substituted-cysteine accessibility method and the analysis of the protein's oligomerization state.

Structural model of human PORCN illuminates disease-associated variants and drug-binding sites

Wnt signaling is essential for normal development and is a therapeutic target in cancer. The enzyme PORCN, or porcupine, is a membrane-bound O-acyltransferase (MBOAT) that is required for the post-translational modification of all Wnts, adding an essential mono-unsaturated palmitoleic acid to a serine on the tip of Wnt hairpin 2. Inherited mutations in PORCN cause focal dermal hypoplasia, and therapeutic inhibition of PORCN slows the growth of Wnt-dependent cancers. Based on homology to mammalian MBOAT proteins, we developed and validated a structural model of human PORCN. The model accommodates palmitoleoyl-CoA and Wnt hairpin 2 in two tunnels in the conserved catalytic core, shedding light on the catalytic mechanism. The model predicts how previously uncharacterized human variants of uncertain significance can alter PORCN function. Drugs including ETC-159, IWP-L6 and LGK-974 dock in the PORCN catalytic site, providing insights into PORCN pharmacologic inhibition. This structural model enhances our mechanistic understanding of PORCN substrate recognition and catalysis, as well as the inhibition of its enzymatic activity, and can facilitate the development of improved inhibitors and the understanding of disease-relevant PORCN mutants. This article has an associated First Person interview with the joint first authors of the paper.

Principles and Methods in Computational Membrane Protein Design

After decades of progress in computational protein design, the design of proteins folding and functioning in lipid membranes appears today as the next frontier. Some notable successes in the de novo design of simplified model membrane protein systems have helped articulate fundamental principles of protein folding, architecture and interaction in the hydrophobic lipid environment. These principles are reviewed here, together with the computational methods and approaches that were used to identify them. We provide an overview of the methodological innovations in the generation of new protein structures and functions and in the development of membrane-specific energy functions. We highlight the opportunities offered by new machine learning approaches applied to protein design, and by new experimental characterization techniques applied to membrane proteins. Although membrane protein design is in its infancy, it appears more reachable than previously thought.

Mass spectrometry informs the structure and dynamics of membrane proteins involved in lipid and drug transport

Membrane proteins are important macromolecules that play crucial roles in many cellular and physiological processes. Over the past two decades, the use of mass spectrometry as a biophysical tool to characterise membrane proteins has grown steadily. By capturing these dynamic complexes in the gas phase, many unknown small molecule interactions have been revealed. One particular application of this research has been the focus on antibiotic resistance with considerable efforts being made to understand underlying mechanisms. Here we review recent advances in the application of mass spectrometry that have yielded both structural and dynamic information on the interactions of antibiotics with proteins involved in bacterial cell envelope biogenesis and drug efflux.

On the Emergence of Orientational Order in Folded Proteins with Implications for Allostery

The beautiful structures of single- and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instances that require a combination of softness and rigidity within the same molecule. By analyzing the solved protein structures, we show that orientational symmetry is broken in the aperiodic arrangement of the secondary structure elements (SSEs), which we deduce by calculating the nematic order parameter, P2. We find that the folded structures are nematic droplets with a broad distribution of P2. We argue that a non-zero value of P2, leads to an arrangement of the SSEs that can resist external forces, which is a requirement for allosteric proteins. Such proteins, which resist mechanical forces in some regions while being flexible in others, transmit signals from one region of the protein to another (action at a distance) in response to binding of ligands (oxygen, ATP, or other small molecules).

OMPdb: A Global Hub of Beta-Barrel Outer Membrane Proteins

OMPdb (www.ompdb.org) was introduced as a database for β-barrel outer membrane proteins from Gram-negative bacteria in 2011 and then included 69,354 entries classified into 85 families. The database has been updated continuously using a collection of characteristic profile Hidden Markov Models able to discriminate between the different families of prokaryotic transmembrane β-barrels. The number of families has increased ultimately to a total of 129 families in the current, second major version of OMPdb. New additions have been made in parallel with efforts to update existing families and add novel families. Here, we present the upgrade of OMPdb, which from now on aims to become a global repository for all transmembrane β-barrel proteins, both eukaryotic and bacterial.

MENSAdb: a thorough structural analysis of membrane protein dimers

Membrane proteins (MPs) are key players in a variety of different cellular processes and constitute the target of around 60% of all Food and Drug Administration-approved drugs. Despite their importance, there is still a massive lack of relevant structural, biochemical and mechanistic information mainly due to their localization within the lipid bilayer. To help fulfil this gap, we developed the MEmbrane protein dimer Novel Structure Analyser database (MENSAdb). This interactive web application summarizes the evolutionary and physicochemical properties of dimeric MPs to expand the available knowledge on the fundamental principles underlying their formation. Currently, MENSAdb contains features of 167 unique MPs (63% homo- and 37% heterodimers) and brings insights into the conservation of residues, accessible solvent area descriptors, average B-factors, intermolecular contacts at 2.5 Å and 4.0 Å distance cut-offs, hydrophobic contacts, hydrogen bonds, salt bridges, π-π stacking, T-stacking and cation-π interactions. The regular update and organization of all these data into a unique platform will allow a broad community of researchers to collect and analyse a large number of features efficiently, thus facilitating their use in the development of prediction models associated with MPs. Database URL: http://www.moreiralab.com/resources/mensadb.

Infrared spectroscopy probes ion binding geometries

Infrared (IR) spectroscopy is a well-established technique for probing the structure, behavior, and surroundings of molecules in their native environments. Its characteristics-most specifically high structural sensitivity, ready applicability to aqueous samples, and broad availability-make it a valuable enzymological technique, particularly for the interrogation of ion binding sites. While IR spectroscopy of the "garden variety" (steady state at room temperature with wild-type proteins) is versatile and powerful in its own right, the combination of IR spectroscopy with specialized experimental schemes for leveraging ultrafast time resolution, protein labeling, and other enhancements further extends this utility. This book chapter provides the fundamental physical background and literature context essential for harnessing IR spectroscopy in the general context of enzymology with specific focus on interrogation of ion binding. Studies of lanthanide ions binding to calmodulin are highlighted as illustrative examples of this process. Appropriate sample preparation, data collection, and spectral interpretation are discussed from a detail-oriented and practical perspective with the goal of facilitating the reader's rapid progression from reading words in a book to collecting and analyzing their own data in the lab.

Membrane Protein Production and Purification from Escherichia coli and Sf9 Insect Cells

A major obstacle to studying membrane proteins by biophysical techniques is the difficulty in producing sufficient amounts of materials for functional and structural studies. To overexpress the target membrane protein heterologously, especially an eukaryotic protein, a key step is to find the optimal host expression system and perform subsequent expression optimization. In this chapter, we describe protocols for screening membrane protein production using bacterial and insect cells, solubilization screening, large-scale production, and commonly used affinity chromatography purification methods. We discuss general optimization conditions, such as promoters and tags, and describe current techniques that can be used in any laboratory without specialized expensive equipment. Especially for insect cells, GFP fusions are particularly useful for localization and in-gel fluorescence detection of the proteins on SDS-PAGE. We give detailed protocols that can be used to screen the best expression and purification conditions for membrane protein study.

Considerations for Membrane Protein Purification

Isolating membrane proteins from their native cells while maintaining structural and functional integrity is challenging. Many detergents have been developed over the years that interact favorably with membrane proteins and mimic the physical properties of the lipid bilayer. Choosing the appropriate detergent is crucial for the successful extraction of a protein in its properly folded, active conformation.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Highlighting membrane protein structure and function: A celebration of the Protein Data Bank

Biological membranes define the boundaries of cells and compartmentalize the chemical and physical processes required for life. Many biological processes are carried out by proteins embedded in or associated with such membranes. Determination of membrane protein (MP) structures at atomic or near-atomic resolution plays a vital role in elucidating their structural and functional impact in biology. This endeavor has determined 1198 unique MP structures as of early 2021. The value of these structures is expanded greatly by deposition of their three-dimensional (3D) coordinates into the Protein Data Bank (PDB) after the first atomic MP structure was elucidated in 1985. Since then, free access to MP structures facilitates broader and deeper understanding of MPs, which provides crucial new insights into their biological functions. Here we highlight the structural and functional biology of representative MPs and landmarks in the evolution of new technologies, with insights into key developments influenced by the PDB in magnifying their impact.

A 10-year meta-analysis of membrane protein structural biology: Detergents, membrane mimetics, and structure determination techniques

Structure determination of membrane proteins is critical to the molecular understanding of many life processes, yet it has historically been a technically challenging endeavor. This past decade has given rise to a number of technological advancements, techniques, and reagents, which have facilitated membrane protein structural biology, resulting in an ever-growing number of membrane protein structures determined. To collate these advances, we have mined available literature to analyze the purification and structure determination specifics for all uniquely solved membrane protein structures from 2010 to 2019. Our analyses demonstrate the strong impact of single-particle cryo-electron microscopy on the field and illustrate how this technique has affected detergent and membrane mimetic usage. Furthermore, we detail how different structure determination methods, taxonomic domains and protein classes have unique detergent/membrane mimetic profiles, highlighting the importance of tailoring their selection. Our analyses provide a quantitative overview of where the field of membrane protein structural biology stands and how it has developed over time. We anticipate that these will serve as a useful tool to streamline future membrane protein structure determination by guiding the choice of detergent/membrane mimetic.

TMEM206 is a potential prognostic marker of hepatocellular carcinoma

Transmembrane proteins are involved in the transportation of materials into and out of cells. The transmembrane protein (TMEM) family is a collection of poorly described transmembrane proteins that serve important roles in tumor development and progression. A number of TMEM proteins have been discovered. A newly discovered TMEM protein, TMEM206, transports ions across the membrane under physiological and pathological conditions, generating an acidic environment, which serves an important role in the microenvironment. However, the prognostic value and regulatory mechanisms of action of TMEM206 in tumors is unclear. The aim of the present study was to evaluate the prognostic value and regulation mechanisms of TMEM206 in tumors. Firstly, the expression of TMEM206 in tumors and normal tissues was assessed using the GEPIA and Oncomine databases and the results revealed that TMEM206 expression increased or decreased depending on the type of tumor. Subsequently, using the Human Protein Atlas and the Kaplan-Meier plotter, the findings of the present study revealed that TMEM206 is related to the prognosis of hepatocellular carcinoma. In order to explore the mechanism of TMEM206 in promoting tumor progression, GEO and cBioPortal were used to determine genes that may be co-expressed with TMEM206. MetaScape was used to identify the signaling pathways that TMEM206 may participate in. Finally, miRWalk, miRDB and TargetScan were used to identify miRNAs that may regulate the expression of TMEM206 and the findings revealed that 2 miRNA (hsa-miR-325 and hsa-miR-510-5p) were involved. In conclusion, upregulation of TMEM206 is associated with poor prognosis in patients with hepatocellular carcinoma.

Decoding the Functional Evolution of an Intramembrane Protease Superfamily by Statistical Coupling Analysis

How evolution endowed membrane enzymes with specific abilities, and then tuned them to the needs of different cells, is poorly understood. We examined whether statistical coupling analysis (SCA) can be applied to rhomboid proteases, the most widely distributed membrane proteins, to identify amino acid "sectors" that evolved independently to acquire a specific function. SCA revealed three coevolving residue networks that form two sectors. Sector 1 determines substrate specificity, but is paradoxically scattered across the protein, consistent with dynamics driving rhomboid-substrate interactions. Sector 2 is hierarchically composed of a subgroup that maintains the catalytic site, and another that maintains the overall fold, forecasting evolution of rhomboid pseudoproteases. Changing only sector 1 residues of a "recipient" rhomboid converted its substrate specificity and catalytic efficiency to that of the "donor." While used only twice over a decade ago, SCA should be generally applicable to membrane proteins, and our sector grafting approach provides an efficient strategy for designing enzymes.

Principal component analysis highlights the influence of temperature, curvature and cholesterol on conformational dynamics of lipids

Membrane lipids are inherently highly dynamic molecules. Currently, it is difficult to probe the structures of individual lipids experimentally at the timescales corresponding to atomic motions, and consequently molecular dynamics simulations are used widely. In our previous work, we have introduced the principal component analysis (PCA) as a convenient framework for comprehensive quantitative description of lipid motions. Here, we present a newly developed open source script, PCAlipids, which automates the analysis and allows us to refine the approach and test its limitations. We use PCAlipids to determine the influence of temperature, cholesterol and curvature on individual lipids, and show that the most prominent lipid tail scissoring motion is strongly affected by these factors and allows tracking of phase transition. Addition of cholesterol affects the conformations and selectively changes the dynamics of lipid molecules, impacting the large-amplitude motions. Introduction of curvature biases the conformational ensembles towards more extended structures. We hope that the developed approach will be useful for understanding the molecular basis of different processes occurring in lipid membrane systems and will stimulate development of complementary experimental techniques probing the conformations of individual lipid molecules.

Imaging and Force Spectroscopy of Single Transmembrane Proteins with the Atomic Force Microscope

The atomic force microscope (AFM) has opened avenues and provided opportunities to investigate biological soft matter and processes ranging from nanometer (nm) to millimeter (mm). The high temporal (millisecond) and spatial (nanometer) resolutions of the AFM are suited for studying many biological processes in their native conditions. The AFM cantilever-aptly termed as a "lab on a tip"-can be used as an imaging tool as well as a handle to manipulate single bonds and proteins. Recent examples have convincingly established AFM as a tool to study the mechanical properties and monitor processes of single proteins and cells with high sensitivity, thus affording insight into important mechanistic details. This chapter specifically focuses on practical and analytical protocols of single-molecule AFM methodologies related to high-resolution imaging and single-molecule force spectroscopy of transmembrane proteins in a lipid bilayer (reconstituted or native). Both these techniques are operator oriented, and require specialized working knowledge of the instrument, theory and practical skills.

Prediction and targeting of GPCR oligomer interfaces

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.

Transmembrane (TMEM) protein family members: Poorly characterized even if essential for the metastatic process

The majority of cancer-associated deaths are related to secondary tumor formation. This multistep process involves the migration of cancer cells to anatomically distant organs. Metastasis formation relies on cancer cell dissemination and survival in the circulatory system, as well as adaptation to the new tissue notably through genetic and/or epigenetic alterations. A large number of proteins are clearly identified to play a role in the metastatic process but the structures and modes of action of these proteins are essentially unknown or poorly described. In this review, we detail the involvement of members of the transmembrane (TMEM) protein family in the formation of metastases or in the mechanisms leading to cancer cell dissemination such as migration and extra-cellular matrix remodelling. While the phenotype associated with TMEM over or down-expression is clear, the mechanisms by which these proteins allow cancer cell spreading remain, for most of them, unclear. In parallel, the 3D structures of these proteins are presented. Moreover, we proposed that TMEM proteins could be used as prognostic markers in different types of cancers and could represent potential targets for cancer treatment. A better understanding of this heterogeneous family of poorly characterized proteins thus opens perspectives for better cancer patient care.

Increasing the accuracy of protein loop structure prediction with evolutionary constraints

MOTIVATION

Accurate prediction of loop structures remains challenging. This is especially true for long loops where the large conformational space and limited coverage of experimentally determined structures often leads to low accuracy. Co-evolutionary contact predictors, which provide information about the proximity of pairs of residues, have been used to improve whole-protein models generated through de novo techniques. Here we investigate whether these evolutionary constraints can enhance the prediction of long loop structures.

RESULTS

As a first stage, we assess the accuracy of predicted contacts that involve loop regions. We find that these are less accurate than contacts in general. We also observe that some incorrectly predicted contacts can be identified as they are never satisfied in any of our generated loop conformations. We examined two different strategies for incorporating contacts, and on a test set of long loops (10 residues or more), both approaches improve the accuracy of prediction. For a set of 135 loops, contacts were predicted and hence our methods were applicable in 97 cases. Both strategies result in an increase in the proportion of near-native decoys in the ensemble, leading to more accurate predictions and in some cases improving the root-mean-square deviation of the final model by more than 3 Å.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Experimental and Simulation Studies of Aquaporin 0 Water Permeability and Regulation

We begin with the history of aquaporin zero (AQP0), the most prevalent membrane protein in the eye lens, from the early days when AQP0 was a protein of unknown function known as Major Intrinsic Protein 26. We progress through its joining the aquaporin family as a water channel in its own right and discuss how regulation of its water permeability by pH and calcium came to be discovered experimentally and linked to lens homeostasis and development. We review the development of molecular dynamics (MD) simulations of lipid bilayers and membrane proteins, including aquaporins, with an emphasis on simulation studies that have elucidated the mechanisms of water conduction, selectivity, and proton exclusion by aquaporins in general. We also review experimental and theoretical progress toward understanding why mammalian AQP0 has a lower water permeability than other aquaporins and the evolution of our present understanding of how its water permeability is regulated by pH and calcium. Finally, we discuss how MD simulations have elucidated the nature of lipid interactions with AQP0.

The MemProtMD database: a resource for membrane-embedded protein structures and their lipid interactions

Integral membrane proteins fulfil important roles in many crucial biological processes, including cell signalling, molecular transport and bioenergetic processes. Advancements in experimental techniques are revealing high resolution structures for an increasing number of membrane proteins. Yet, these structures are rarely resolved in complex with membrane lipids. In 2015, the MemProtMD pipeline was developed to allow the automated lipid bilayer assembly around new membrane protein structures, released from the Protein Data Bank (PDB). To make these data available to the scientific community, a web database (http://memprotmd.bioch.ox.ac.uk) has been developed. Simulations and the results of subsequent analysis can be viewed using a web browser, including interactive 3D visualizations of the assembled bilayer and 2D visualizations of lipid contact data and membrane protein topology. In addition, ensemble analyses are performed to detail conserved lipid interaction information across proteins, families and for the entire database of 3506 PDB entries. Proteins may be searched using keywords, PDB or Uniprot identifier, or browsed using classification systems, such as Pfam, Gene Ontology annotation, mpstruc or the Transporter Classification Database. All files required to run further molecular simulations of proteins in the database are provided.

Comparative analysis of membrane protein structure databases

BACKGROUND

Membrane proteins play important roles in cell survival and cell communication, as they function as transporters, receptors, anchors and enzymes. They are also potential targets for drugs that block receptors or inhibit enzymes related to diseases. Although the number of known structures of membrane proteins is still small relative to the size of the proteome as a whole, many new membrane protein structures have been determined recently.

SCOPE OF THE ARTICLE

We compared and analyzed the widely used membrane protein databases, mpstruc, Orientations of Proteins in Membranes (OPM), and PDBTM, as well as the extended dataset of mpstruc based on sequence similarity, the PDB structures whose classification field indicates that they are "membrane proteins" and the proteins with Structural Classification of Proteins (SCOP) class-f domains. We evaluated the relationships between these databases or datasets based on the overlap in their contents and the degree of consistency in the structural, topological, and functional classifications and in the transmembrane domain assignment.

MAJOR CONCLUSIONS

The membrane databases differ from each other in their coverage, and in the criteria that they use for annotation and classification. To ensure the efficient use of these databases, it is important to understand their differences and similarities. The establishment of more detailed and consistent annotations for the sequence, structure, membrane association, and function of membrane proteins is still required.

GENERAL SIGNIFICANCE

Considering the recent growth of experimentally determined structures, a broad survey and cumulative analysis of the sum of knowledge as presented in the membrane protein structure databases can be helpful to elucidate structures and functions of membrane proteins. We also aim to provide a framework for future research and classification of membrane proteins.

Dissecting binding of a β-barrel membrane protein by phage display

Membrane proteins (MPs) constitute a third of all proteomes, and contribute to a myriad of cellular functions including intercellular communication, nutrient transport and energy generation. For example, TonB-dependent transporters (TBDTs) in the outer membrane of Gram-negative bacteria play an essential role transporting iron and other nutrients into the bacterial cell. The inherently hydrophobic surfaces of MPs complicates protein expression, purification, and characterization. Thus, dissecting the functional contributions of individual amino acids or structural features through mutagenesis can be a challenging ordeal. Here, we apply a new approach for the expedited protein characterization of the TBDT ShuA from Shigella dysenteriae, and elucidate the protein's initial steps during heme-uptake. ShuA variants were displayed on the surface of an M13 bacteriophage as fusions to the P8 coat protein. Each ShuA variant was analyzed for its ability to display on the bacteriophage surface, and functionally bind to hemoglobin. This technique streamlines isolation of stable MP variants for rapid characterization of binding to various ligands. Site-directed mutagenesis studies targeting each extracellular loop region of ShuA demonstrate no specific extracellular loop is required for hemoglobin binding. Instead two residues, His420 and His86 mediate this interaction. The results identify a loop susceptible to antibody binding, and also a small molecule motif capable of disrupting ShuA from S. dysenteriae. The approach is generalizable to the dissection of other phage-displayed TBDTs and MPs.

Tandem malonate-based glucosides (TMGs) for membrane protein structural studies

High-resolution membrane protein structures are essential for understanding the molecular basis of diverse biological events and important in drug development. Detergents are usually used to extract these bio-macromolecules from the membranes and maintain them in a soluble and stable state in aqueous solutions for downstream characterization. However, many eukaryotic membrane proteins solubilized in conventional detergents tend to undergo structural degradation, necessitating the development of new amphiphilic agents with enhanced properties. In this study, we designed and synthesized a novel class of glucoside amphiphiles, designated tandem malonate-based glucosides (TMGs). A few TMG agents proved effective at both stabilizing a range of membrane proteins and extracting proteins from the membrane environment. These favourable characteristics, along with synthetic convenience, indicate that these agents have potential in membrane protein research.

Atomic-level analysis of membrane-protein structure

Membrane proteins are substantially more challenging than natively soluble proteins as subjects for structural analysis. Thus, membrane proteins are greatly underrepresented in structural databases. Recently, focused consortium efforts and advances in methodology for protein production, crystallographic analysis and cryo-EM analysis have accelerated the pace of atomic-level structure determination of membrane proteins.

Membrane proteins: always an insoluble problem?

Membrane proteins play crucial roles in cellular processes and are often important pharmacological drug targets. The hydrophobic properties of these proteins make full structural and functional characterization challenging because of the need to use detergents or other solubilizing agents when extracting them from their native lipid membranes. To aid membrane protein research, new methodologies are required to allow these proteins to be expressed and purified cheaply, easily, in high yield and to provide water soluble proteins for subsequent study. This mini review focuses on the relatively new area of water soluble membrane proteins and in particular two innovative approaches: the redesign of membrane proteins to yield water soluble variants and how adding solubilizing fusion proteins can help to overcome these challenges. This review also looks at naturally occurring membrane proteins, which are able to exist as stable, functional, water soluble assemblies with no alteration to their native sequence.

Removable Backbone Modification Method for the Chemical Synthesis of Membrane Proteins

Chemical synthesis can produce water-soluble globular proteins bearing specifically designed modifications. These synthetic molecules have been used to study the biological functions of proteins and to improve the pharmacological properties of protein drugs. However, the above advances notwithstanding, membrane proteins (MPs), which comprise 20-30% of all proteins in the proteomes of most eukaryotic cells, remain elusive with regard to chemical synthesis. This difficulty stems from the strong hydrophobic character of MPs, which can cause considerable handling issues during ligation, purification, and characterization steps. Considerable efforts have been made to improve the solubility of transmembrane peptides for chemical ligation. These methods can be classified into two main categories: the manipulation of external factors and chemical modification of the peptide. This Account summarizes our research advances in the development of chemical modification especially the two generations of removable backbone modification (RBM) strategy for the chemical synthesis of MPs. In the first RBM generation, we install a removable modification group at the backbone amide of Gly within the transmembrane peptides. In the second RBM generation, the RBM group can be installed into all primary amino acid residues. The second RBM strategy combines the activated intramolecular O-to-N acyl transfer reaction, in which a phenyl group remains unprotected during the coupling process, which can play a catalytic role to generate the activated phenyl ester to assist in the formation of amide. The key feature of the RBM group is its switchable stability in trifluoroacetic acid. The stability of these backbone amide N-modifications toward TFA can be modified by regulating the electronic effects of phenol groups. The free phenol group is acylated to survive the TFA deprotection step, while the acyl phenyl ester will be quantitatively hydrolyzed in a neutral aqueous solution, and the free phenol group increases the electron density of the benzene ring to make the RBM labile to TFA. The transmembrane peptide segment bearing RBM groups behaves like a water-soluble peptide during fluorenylmethyloxycarbonyl based solid-phase peptide synthesis (Fmoc SPPS), ligation, purification, and characterization. The quantitative removal of the RBM group can be performed to obtain full-length MPs. The RBM strategy was used to prepare the core transmembrane domain Kir5.1[64-179] not readily accessible by recombinant protein expression, the influenza A virus M2 proton channel with phosphorylation, the cation-specific ion channel p7 from the hepatitis C virus with site-specific NMR isotope labels, and so on. The RBM method enables the practical engineering of small- to medium-sized MPs or membrane protein domains to address fundamental questions in the biochemical, biophysical, and pharmaceutical sciences.

Lactococcus lactis is an Efficient Expression System for Mammalian Membrane Proteins Involved in Liver Detoxification, CYP3A4, and MGST1

Despite the great importance of human membrane proteins involved in detoxification mechanisms, their wide use for biochemical approaches is still hampered by several technical difficulties considering eukaryotic protein expression in order to obtain the large amounts of protein required for functional and/or structural studies. Lactococcus lactis has emerged recently as an alternative heterologous expression system to Escherichia coli for proteins that are difficult to express. The aim of this work was to check its ability to express mammalian membrane proteins involved in liver detoxification, i.e., CYP3A4 and two isoforms of MGST1 (rat and human). Genes were cloned using two different strategies, i.e., classical or Gateway-compatible cloning, and we checked the possible influence of two affinity tags (6×-His-tag and Strep-tag II). Interestingly, all proteins could be successfully expressed in L. lactis at higher yields than those previously obtained for these proteins with classical expression systems (E. coli, Saccharomyces cerevisiae) or those of other eukaryotic membrane proteins expressed in L. lactis. In addition, rMGST1 was fairly active after expression in L. lactis. This study highlights L. lactis as an attractive system for efficient expression of mammalian detoxification membrane proteins at levels compatible with further functional and structural studies.

TMSEG: Novel prediction of transmembrane helices

Transmembrane proteins (TMPs) are important drug targets because they are essential for signaling, regulation, and transport. Despite important breakthroughs, experimental structure determination remains challenging for TMPs. Various methods have bridged the gap by predicting transmembrane helices (TMHs), but room for improvement remains. Here, we present TMSEG, a novel method identifying TMPs and accurately predicting their TMHs and their topology. The method combines machine learning with empirical filters. Testing it on a non-redundant dataset of 41 TMPs and 285 soluble proteins, and applying strict performance measures, TMSEG outperformed the state-of-the-art in our hands. TMSEG correctly distinguished helical TMPs from other proteins with a sensitivity of 98 ± 2% and a false positive rate as low as 3 ± 1%. Individual TMHs were predicted with a precision of 87 ± 3% and recall of 84 ± 3%. Furthermore, in 63 ± 6% of helical TMPs the placement of all TMHs and their inside/outside topology was correctly predicted. There are two main features that distinguish TMSEG from other methods. First, the errors in finding all helical TMPs in an organism are significantly reduced. For example, in human this leads to 200 and 1600 fewer misclassifications compared to the second and third best method available, and 4400 fewer mistakes than by a simple hydrophobicity-based method. Second, TMSEG provides an add-on improvement for any existing method to benefit from. Proteins 2016; 84:1706-1716. © 2016 Wiley Periodicals, Inc.

Helix perturbations in membrane proteins assist in inter-helical interactions and optimal helix positioning in the bilayer

Transmembrane (TM) helices in integral membrane proteins are primarily α-helical in structure. Here we analyze 1134 TM helices in 90 high resolution membrane proteins and find that apart from the widely prevalent α-helices, TM regions also contain stretches of 3₁₀ (3 to 8 residues) and π-helices (5 to 19 residues) with distinct sequence signatures. The various helix perturbations in TM regions comprise of helices with kinked geometry, as well as those with an interspersed 3₁₀/π-helical fragment and show high occurrence in a few membrane proteins. Proline is frequently present at sites of these perturbations, but it is neither a necessary nor a sufficient requirement. Helix perturbations are also conserved within a family of membrane proteins despite low sequence identity in the perturbed region. Furthermore, a perturbation influences the geometry of the TM helix, mediates inter-helical interactions within and across protein chains and avoids hydrophobic mismatch of the helix termini with the bilayer. An analysis of π-helices in the TM regions of the heme copper oxidase superfamily shows that interspersed π-helices can vary in length from 6 to 19 amino acids or be entirely absent, depending upon the protein function. The results presented here would be helpful for prediction of 3₁₀ and π-helices in TM regions and can assist the computational design of membrane proteins.

Biological membranes

Biological membranes allow life as we know it to exist. They form cells and enable separation between the inside and outside of an organism, controlling by means of their selective permeability which substances enter and leave. By allowing gradients of ions to be created across them, membranes also enable living organisms to generate energy. In addition, they control the flow of messages between cells by sending, receiving and processing information in the form of chemical and electrical signals. This essay summarizes the structure and function of membranes and the proteins within them, and describes their role in trafficking and transport, and their involvement in health and disease. Techniques for studying membranes are also discussed.

Microscopic Characterization of Membrane Transporter Function by In Silico Modeling and Simulation

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory.