Transmembrane protein structures without X-rays

Transmembrane proteins-Different anchoring systems

Transmembrane proteins are active in amphipathic environments. To stabilize the protein in such surrounding the exposure of hydrophobic residues on the protein surface is required. Transmembrane proteins are responsible for the transport of various molecules. Therefore, they often represent structures in the form of channels. This analysis focused on the stability and local flexibility of transmembrane proteins, particularly those related to their biological activity. Different forms of anchorage were identified using the fuzzy oil-drop model (FOD) and its modified form, FOD-M. The mainly helical as well as β-barrel structural forms are compared with respect to the mechanism of stabilization in the cell membrane. The different anchoring system was found to stabilize protein molecules with possible local fluctuation.

Exploring Uniform, Dual, and Dynamic Topologies of Membrane Proteins by Substituted Cysteine Accessibility Method (SCAM™)

A described simple and advanced protocol for Substituted Cysteine Accessibility Method as applied to transmembrane (TM) orientation (SCAM™) permits a topology analysis of proteins in their native state and can be universally adapted to any membrane system to either systematically map an uniform or identify and quantify the degree of mixed topology or establish transmembrane assembly dynamics from relatively static experimental data such as endpoint topologies of membrane proteins. In this approach, noncritical individual amino acids that are thought to reside in the putative extracellular or intracellular loops of a membrane protein are replaced one at the time by cysteine residue, and the orientation with respect to the membrane is evaluated by using a pair of membrane-impermeable non-detectable and detectable thiol-reactive labeling reagents. For the most water-exposed cysteine residues in proteins, the thiol pKa lies in the range of 8-9, and formation of cysteinyl thiolate ions is optimum in aqueous rather in a nonpolar environment. These features and the ease of specific chemical modification with thiol reagents are central to SCAM™. Membrane side-specific sulfhydryl labeling allows to discriminate "exposed, protected or dynamic" cysteines strategically "implanted" at desired positions throughout cysteine less target protein template. The strategy described is widely used to map the topology of membrane protein and establish its transmembrane dynamics in intact cells of both diderm (two-membraned) Gram-negative and monoderm (one-membraned) Gram-positive bacteria, cell-derived oriented membrane vesicles, and proteoliposomes.

The Role of Transmembrane Proteins in Plant Growth, Development, and Stress Responses

Transmembrane proteins participate in various physiological activities in plants, including signal transduction, substance transport, and energy conversion. Although more than 20% of gene products are predicted to be transmembrane proteins in the genome era, due to the complexity of transmembrane domains they are difficult to reliably identify in the predicted protein, and they may have different overall three-dimensional structures. Therefore, it is challenging to study their biological function. In this review, we describe the typical structures of transmembrane proteins and their roles in plant growth, development, and stress responses. We propose a model illustrating the roles of transmembrane proteins during plant growth and response to various stresses, which will provide important references for crop breeding.

Connexins and Pannexins—Similarities and Differences According to the FOD-M Model

Connexins and pannexins are the transmembrane proteins of highly distinguished biological activity in the form of transport of molecules and electrical signals. Their common role is to connect the external environment with the cytoplasm of the cell, while connexin is also able to link two cells together allowing the transport from one to another. The analysis presented here aims to identify the similarities and differences between connexin and pannexin. As a comparative criterion, the hydrophobicity distribution in the structure of the discussed proteins was used. The comparative analysis is carried out with the use of a mathematical model, the FOD-M model (fuzzy oil drop model in its Modified version) expressing the specificity of the membrane’s external field, which in the case of the discussed proteins is significantly different from the external field for globular proteins in the polar environment of water. The characteristics of the external force field influence the structure of protein allowing the activity in a different environment.

Prediction of Metal Ion Binding Sites of Transmembrane Proteins

The metal ion binding of transmembrane proteins (TMPs) plays a fundamental role in biological processes, pharmaceutics, and medicine, but it is hard to extract enough TMP structures in experimental techniques to discover their binding mechanism comprehensively. To predict the metal ion binding sites for TMPs on a large scale, we present a simple and effective two-stage prediction method TMP-MIBS, to identify the corresponding binding residues using TMP sequences. At present, there is no specific research on the metal ion binding prediction of TMPs. Thereby, we compared our model with the published tools which do not distinguish TMPs from water-soluble proteins. The results in the independent verification dataset show that TMP-MIBS has superior performance. This paper explores the interaction mechanism between TMPs and metal ions, which is helpful to understand the structure and function of TMPs and is of great significance to further construct transport mechanisms and identify potential drug targets.

A lipophilicity-based energy function for membrane-protein modelling and design

Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsTβL, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5Å root-mean-square deviation within the top-predicted five models (available online: http://tmhop.weizmann.ac.il). Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design.

Building Proteins in a Day: Efficient 3D Molecular Structure Estimation with Electron Cryomicroscopy

Discovering the 3D atomic-resolution structure of molecules such as proteins and viruses is one of the foremost research problems in biology and medicine. Electron Cryomicroscopy (cryo-EM) is a promising vision-based technique for structure estimation which attempts to reconstruct 3D atomic structures from a large set of 2D transmission electron microscope images. This paper presents a new Bayesian framework for cryo-EM structure estimation that builds on modern stochastic optimization techniques to allow one to scale to very large datasets. We also introduce a novel Monte-Carlo technique that reduces the cost of evaluating the objective function during optimization by over five orders of magnitude. The net result is an approach capable of estimating 3D molecular structure from large-scale datasets in about a day on a single CPU workstation.

Mapping of Membrane Protein Topology by Substituted Cysteine Accessibility Method (SCAM™)

A described simple and advanced protocol for the substituted-cysteine accessibility method as applied to transmembrane (TM) orientation (SCAM™) permits a topology analysis of proteins in their native state and can be universally adapted to any membrane system to either systematically map an uniform topology or identify and quantify the degree of mixed topology. In this approach, noncritical individual amino acids that are thought to reside in the putative extracellular or intracellular loops of a membrane protein are replaced one at a time by cysteine residue, and the orientation with respect to the membrane is evaluated using a pair of membrane-impermeable nondetectable and detectable thiol-reactive labeling reagents.

Interplay between hydrophobicity and the positive-inside rule in determining membrane-protein topology

The energetics of membrane-protein interactions determine protein topology and structure: hydrophobicity drives the insertion of helical segments into the membrane, and positive charges orient the protein with respect to the membrane plane according to the positive-inside rule. Until recently, however, quantifying these contributions met with difficulty, precluding systematic analysis of the energetic basis for membrane-protein topology. We recently developed the dsTβL method, which uses deep sequencing and in vitro selection of segments inserted into the bacterial plasma membrane to infer insertion-energy profiles for each amino acid residue across the membrane, and quantified the insertion contribution from hydrophobicity and the positive-inside rule. Here, we present a topology-prediction algorithm called TopGraph, which is based on a sequence search for minimum dsTβL insertion energy. Whereas the average insertion energy assigned by previous experimental scales was positive (unfavorable), the average assigned by TopGraph in a nonredundant set is -6.9 kcal/mol. By quantifying contributions from both hydrophobicity and the positive-inside rule we further find that in about half of large membrane proteins polar segments are inserted into the membrane to position more positive charges in the cytoplasm, suggesting an interplay between these two energy contributions. Because membrane-embedded polar residues are crucial for substrate binding and conformational change, the results implicate the positive-inside rule in determining the architectures of membrane-protein functional sites. This insight may aid structure prediction, engineering, and design of membrane proteins. TopGraph is available online (topgraph.weizmann.ac.il).

Refining the treatment of membrane proteins by coarse-grained models

Obtaining a quantitative description of the membrane proteins stability is crucial for understanding many biological processes. However the advance in this direction has remained a major challenge for both experimental studies and molecular modeling. One of the possible directions is the use of coarse-grained models but such models must be carefully calibrated and validated. Here we use a recent progress in benchmark studies on the energetics of amino acid residue and peptide membrane insertion and membrane protein stability in refining our previously developed coarse-grained model (Vicatos et al., Proteins 2014;82:1168). Our refined model parameters were fitted and/or tested to reproduce water/membrane partitioning energetics of amino acid side chains and a couple of model peptides. This new model provides a reasonable agreement with experiment for absolute folding free energies of several β-barrel membrane proteins as well as effects of point mutations on a relative stability for one of those proteins, OmpLA. The consideration and ranking of different rotameric states for a mutated residue was found to be essential to achieve satisfactory agreement with the reference data.

Lipid nanotechnologies for structural studies of membrane-associated proteins

We present a methodology of lipid nanotubes (LNT) and nanodisks technologies optimized in our laboratory for structural studies of membrane-associated proteins at close to physiological conditions. The application of these lipid nanotechnologies for structure determination by cryo-electron microscopy (cryo-EM) is fundamental for understanding and modulating their function. The LNTs in our studies are single bilayer galactosylceramide based nanotubes of ∼20 nm inner diameter and a few microns in length, that self-assemble in aqueous solutions. The lipid nanodisks (NDs) are self-assembled discoid lipid bilayers of ∼10 nm diameter, which are stabilized in aqueous solutions by a belt of amphipathic helical scaffold proteins. By combining LNT and ND technologies, we can examine structurally how the membrane curvature and lipid composition modulates the function of the membrane-associated proteins. As proof of principle, we have engineered these lipid nanotechnologies to mimic the activated platelet's phosphtaidylserine rich membrane and have successfully assembled functional membrane-bound coagulation factor VIII in vitro for structure determination by cryo-EM. The macromolecular organization of the proteins bound to ND and LNT are further defined by fitting the known atomic structures within the calculated three-dimensional maps. The combination of LNT and ND technologies offers a means to control the design and assembly of a wide range of functional membrane-associated proteins and complexes for structural studies by cryo-EM. The presented results confirm the suitability of the developed methodology for studying the functional structure of membrane-associated proteins, such as the coagulation factors, at a close to physiological environment.

The structure of the CD3 ζζ transmembrane dimer in POPC and raft-like lipid bilayer: a molecular dynamics study

Plasma membrane lipids significantly affect assembly and activity of many signaling networks. The present work is aimed at analyzing, by molecular dynamics simulations, the structure and dynamics of the CD3 ζζ dimer in palmitoyl-oleoyl-phosphatidylcholine bilayer (POPC) and in POPC/cholesterol/sphingomyelin bilayer, which resembles the raft membrane microdomain supposed to be the site of the signal transducing machinery. Both POPC and raft-like environment produce significant alterations in structure and flexibility of the CD3 ζζ with respect to nuclear magnetic resonance (NMR) model: the dimer is more compact, its secondary structure is slightly less ordered, the arrangement of the Asp6 pair, which is important for binding to the Arg residue in the alpha chain of the T cell receptor (TCR), is stabilized by water molecules. Different interactions of charged residues with lipids at the lipid-cytoplasm boundary occur when the two environments are compared. Furthermore, in contrast to what is observed in POPC, in the raft-like environment correlated motions between transmembrane and cytoplasmic regions are observed. Altogether the data suggest that when the TCR complex resides in the raft domains, the CD3 ζζ dimer assumes a specific conformation probably necessary to the correct signal transduction.

Design, synthesis, and evaluation of bioactive small molecules

Collaborative research projects between chemists, biologists, and medical scientists have inevitably produced many useful drugs, biosensors, and medical instrumentation. Organic chemistry lies at the heart of drug discovery and development. The current range of organic synthetic methodologies allows for the construction of unlimited libraries of small organic molecules for drug screening. In translational research projects, we have focused on the discovery of lead compounds for three major diseases: Alzheimer's disease (AD), breast cancer, and viral infections. In the AD project, we have taken a rational-design approach and synthesized a new class of tricyclic pyrone (TP) compounds that preserve memory and motor functions in amyloid precursor protein (APP)/presenilin-1 (PS1) mice. TPs could protect neuronal death through several possible mechanisms, including their ability to inhibit the formation of both intraneuronal and extracellular amyloid β (Aβ) aggregates, to increase cholesterol efflux, to restore axonal trafficking, and to enhance long-term potentiation (LTP) and restored LTP following treatment with Aβ oligomers. We have also synthesized a new class of gap-junction enhancers, based on substituted quinolines, that possess potent inhibitory activities against breast-cancer cells in vitro and in vivo. Although various antiviral drugs are available, the emergence of viral resistance to existing antiviral drugs and various understudied viral infections, such as norovirus and rotavirus, emphasizes the demand for the development of new antiviral agents against such infections and others. Our laboratories have undertaken these projects for the discovery of new antiviral inhibitors. The discussion of these aforementioned projects may shed light on the future development of drug candidates in the fields of AD, cancer, and viral infections.

The simulation approach to lipid-protein interactions

The interactions between lipids and proteins are crucial for a range of biological processes, from the folding and stability of membrane proteins to signaling and metabolism facilitated by lipid-binding proteins. However, high-resolution structural details concerning functional lipid/protein interactions are scarce due to barriers in both experimental isolation of native lipid-bound complexes and subsequent biophysical characterization. The molecular dynamics (MD) simulation approach provides a means to complement available structural data, yielding dynamic, structural, and thermodynamic data for a protein embedded within a physiologically realistic, modelled lipid environment. In this chapter, we provide a guide to current methods for setting up and running simulations of membrane proteins and soluble, lipid-binding proteins, using standard atomistically detailed representations, as well as simplified, coarse-grained models. In addition, we outline recent studies that illustrate the power of the simulation approach in the context of biologically relevant lipid/protein interactions.

Structure prediction of G protein-coupled receptors and their ensemble of functionally important conformations

G protein-coupled receptors (GPCRs) are integral membrane proteins whose "pleiotropic" nature enables transmembrane (TM) signal transduction, amplification, and diversification via G protein-coupled and β arrestin-coupled pathways. GPCRs appear to enable this by being structurally flexible and by existing in different conformational states with potentially different signaling and functional consequences. We describe a method for the prediction of the three-dimensional structures of these different conformations of GPCRs starting from their amino acid sequence. It combines a unique protocol of computational methods that first predict the TM regions of these receptors and TM helix shapes based on those regions, which is followed by a locally complete sampling of TM helix packings and their scoring that results in a few (~10-20) lowest energy conformations likely to play a role in binding to different ligands and signaling events. Prediction of the structures for multiple conformations of a GPCR is starting to enable the testing of multiple hypotheses related to GPCR activation and binding to ligands with different signaling profiles.

Characterizing and predicting the functional and conformational diversity of seven-transmembrane proteins

The activation of seven-transmembrane receptors (7TMRs) allows cells to sense their environment and convert extracellular signals (like hormone binding) into intracellular signals (through G protein-coupled and/or β arrestin-coupled pathways). A single 7TMR is capable of transducing a wide spectrum of physiological responses inside a cell by coupling to these pathways. This intracellular pleiotropic action is enabled by multiple conformations exhibited by these receptors. Developments in membrane protein structure determination technologies have led to a rapid increase in crystal structures for many 7TMRs. Majority of these receptors have been crystallized in their inactive conformation and, for some, one of the many active conformations has also been crystallized. Given the topological constraints of a lipid bilayer that results in a single fold of seven almost parallel TM helices connected by mostly unstructured loops, these structures exhibit a diversity of conformations not only across the receptors but also across the different functional forms for receptors with structures for one of the functionally active conformations. Here we present a method to characterize this conformational diversity in terms of transmembrane helix topology (TMHTOP) parameters and how to use these helix orientation parameters to predict functionally-distinct multiple conformations for these receptors. The TMHTOP parameters enable a quantification of the structural changes that underlie 7TMR activation and also sheds a unique mechanistic light on the pleiotropic nature of these receptors. It provides a common language to describe the 7TMR activation mechanisms as well as differences across many receptors in terms of visually intuitive structural parameters. Protein structure prediction methods can use these parameters to describe 7TMR conformational ensembles, which coupled to experimental data can be used to develop testable hypotheses for the structural basis of 7TMR functions.

Enhanced Inter-helical Residue Contact Prediction in Transmembrane Proteins

In this paper, based on a recent work by McAllister and Floudas who developed a mathematical optimization model to predict the contacts in transmembrane alpha-helical proteins from a limited protein data set [1], we have enhanced this method by 1) building a more comprehensive data set for transmembrane alpha-helical proteins and this enhanced data set is then used to construct the probability sets, MIN-1N and MIN-2N, for residue contact prediction, 2) enhancing the mathematical model via modifications of several important physical constraints and 3) applying a new blind contact prediction scheme on different protein sets proposed from analyzing the contact prediction on 65 proteins from Fuchs et al. [2]. The blind contact prediction scheme has been tested on two different membrane protein sets. Firstly it is applied to five carefully selected proteins from the training set. The contact prediction of these five proteins uses probability sets built by excluding the target protein from the training set, and an average accuracy of 56% was obtained. Secondly, it is applied to six independent membrane proteins with complicated topologies, and the prediction accuracies are 73% for 2ZY9A, 21% for 3KCUA, 46% for 2W1PA, 64% for 3CN5A, 77% for 3IXZA and 83% for 3K3FA. The average prediction accuracy for the six proteins is 60.7%. The proposed approach is also compared with a support vector machine method (TMhit [3]) and it is shown that it exhibits better prediction accuracy.

Modeling and simulation of ion-coupled and ATP-driven membrane proteins

The molecular mechanisms of membrane proteins that are activated either by ions or by ATP are just beginning to come into focus, as long-awaited structural data are revealed. This information is being leveraged and supplemented to great effect by molecular modeling and computer simulation studies. Important examples include the homology modeling of eukaryotic protein structures based on distantly related templates, as well as the use of internal structural symmetry for modeling different states in conformational cycles. Molecular simulation studies have elucidated the location and coordination structure of ion binding sites, and explained their selectivity, while also providing tantalizing insights into the mechanisms that couple conformational change to ion translocation or ATP hydrolysis.

Congruency between biophysical data from multiple platforms and molecular dynamics simulation of the double-super helix model of nascent high-density lipoprotein

The predicted structure and molecular trajectories from >80 ns molecular dynamics simulation of the solvated Double-Super Helix (DSH) model of nascent high-density lipoprotein (HDL) were determined and compared with experimental data on reconstituted nascent HDL obtained from multiple biophysical platforms, including small angle neutron scattering (SANS) with contrast variation, hydrogen-deuterium exchange tandem mass spectrometry (H/D-MS/MS), nuclear magnetic resonance spectroscopy (NMR), cross-linking tandem mass spectrometry (MS/MS), fluorescence resonance energy transfer (FRET), electron spin resonance spectroscopy (ESR), and electron microscopy. In general, biophysical constraints experimentally derived from the multiple platforms agree with the same quantities evaluated using the simulation trajectory. Notably, key structural features postulated for the recent DSH model of nascent HDL are retained during the simulation, including (1) the superhelical conformation of the antiparallel apolipoprotein A1 (apoA1) chains, (2) the lipid micellar-pseudolamellar organization, and (3) the solvent-exposed Solar Flare loops, proposed sites of interaction with LCAT (lecithin cholesteryl acyltransferase). Analysis of salt bridge persistence during simulation provides insights into structural features of apoA1 that forms the backbone of the lipoprotein. The combination of molecular dynamics simulation and experimental data from a broad range of biophysical platforms serves as a powerful approach to studying large macromolecular assemblies such as lipoproteins. This application to nascent HDL validates the DSH model proposed earlier and suggests new structural details of nascent HDL.

Identification of key residues determining species differences in inhibitor binding of microsomal prostaglandin E synthase-1

Microsomal prostaglandin E synthase-1 (MPGES1) is induced during an inflammatory reaction from low basal levels by pro-inflammatory cytokines and subsequently involved in the production of the important mediator of inflammation, prostaglandin E(2). Nonsteroidal anti-inflammatory drugs prevent prostaglandin E(2) production by inhibiting the upstream enzymes cyclooxygenases 1 and 2. In contrast to these conventional drugs, a new generation of NSAIDs targets the terminal enzyme MPGES1. Some of these compounds potently inhibit human MPGES1 but do not have an effect on the rat orthologue. We investigated this interspecies difference in a rat/human chimeric form of the enzyme as well as in several mutants and identified key residues Thr-131, Leu-135, and Ala-138 in human MPGES1, which play a crucial role as gate keepers for the active site of MPGES1. These residues are situated in transmembrane helix 4, lining the entrance to the cleft between two subunits in the protein trimer, and regulate access of the inhibitor in the rat enzyme. Exchange toward the human residues in rat MPGES1 was accompanied with a gain of inhibitor activity, whereas exchange in human MPGES1 toward the residues found in rat abrogated inhibitor activity. Our data give evidence for the location of the active site at the interface between subunits in the homotrimeric enzyme and suggest a model of how the natural substrate PGH(2), or competitive inhibitors of MPGES1, enter the active site via the phospholipid bilayer of the membrane.

C(alpha)-trace model of the transmembrane domain of human copper transporter 1, motion and functional implications

The trimeric human copper transporter 1 (hCTR1) is essential for copper uptake and is implicated in sensitivity to chemotherapy drugs. Using the cryoelectron microscopy (cryoEM) map of hCTR1 and evolutionary data, we constructed a Calpha-trace model of the membrane region. The model structure, supported by mutagenesis data, was used to investigate global dynamics through elastic network models. Identified as dominant hinge regions, hCTR1's MxxxM and GxxxG motifs were shown to have significant roles in functional movements characterized by the two slowest modes of motion. Both modes predicted significant changes at the wide cytoplasmic pore region; the slowest mode introduced a rotational motion around the pore central axis, whereas in the following mode the cytoplasmic parts of the helices approached and moved away from the pore center. In the most cooperative mode, the MxxxM motif in the extracellular narrow region remained static. The second mode of motion, however, predicted a cooperative rotational motion of this copper-binding motif, possibly reflecting activation at the pore's extracellular entrance. We suggest a molecular mechanism of copper transport in which this motif serves both as a gate and as a selectivity filter. We also suggest residues that are responsible for pH activation.

[Prediction of the spatial structure of proteins: emphasis on membrane targets]

Knowledge of the spatial structure of proteins is a prerequisite for both awareness of their functional mechanisms and the framework for rational drug discovery and design. Meanwhile, direct structural determination is often hampered or impractical due to the complexity, expensiveness, and limited capabilities of experimental techniques. These issues are especially pronounced for integral membrane proteins. On numerous occasions, the theoretical prediction of protein structures may facilitate the process by exploiting physical or empirical principles. This paper surveys modern techniques for the prediction of the spatial structure of proteins using computer algorithms, and the main emphasis is placed on the most "complex" targets - membrane proteins (MPs). The first part of the review describes de novo methods based on empirical physical principles; in the second part, a comparative modeling philosophy, which accounts for the structure of related proteins, is described. Special focus is made regarding pharmacologically relevant classes of G-coupled receptors, receptor tyrosine ki-nases, and other MPs. Algorithms for the assessment of the models quality and potential fields of application of computer models are discussed.

Model-guided mutagenesis drives functional studies of human NHA2, implicated in hypertension

Human NHA2 is a poorly characterized Na(+)/H(+) antiporter recently implicated in essential hypertension. We used a range of computational tools and evolutionary conservation analysis to build and validate a three-dimensional model of NHA2 based on the crystal structure of a distantly related bacterial transporter, NhaA. The model guided mutagenic evaluation of transport function, ion selectivity, and pH dependence of NHA2 by phenotype screening in yeast. We describe a cluster of essential, highly conserved titratable residues located in an assembly region made of two discontinuous helices of inverted topology, each interrupted by an extended chain. Whereas in NhaA, oppositely charged residues compensate for partial dipoles generated within this assembly, in NHA2, polar but uncharged residues suffice. Our findings led to a model for transport mechanism that was compared to the well-known electroneutral NHE1 and electrogenic NhaA subtypes. This study establishes NHA2 as a prototype for the poorly understood, yet ubiquitous, CPA2 antiporter family recently recognized in plants and metazoans and illustrates a structure-driven approach to derive functional information on a newly discovered transporter.

3D structural models of transmembrane proteins

Transmembrane proteins are macromolecules implicated in major biological processes and diseases. Because of their specific neighborhood, few transmembrane protein structures are currently available. The building of structural models of transmembrane proteins is a major research area. Because of the lack of available 3D structures, automatic homology modeling is not an efficient way of proposing pertinent structural models. Hence, most of the structural models of transmembrane proteins are developed through a more complex protocol that comprises the use of secondary structure prediction to complete the comparative modeling process. Then, refinement and assessment steps are performed go often to a novel comparative modeling process. Nowadays, it is also possible to take attention to the helix-helix and helix-lipid interactions, and even build quaternary structures. In all cases, the most important factor when proceeding to correct structural models is taking the experimental data into account.

Bioinformatic approaches for the structure and function of membrane proteins

Membrane proteins play important roles in the biology of the cell, including intercellular communication and molecular transport. Their well-established importance notwithstanding, the high-resolution structures of membrane proteins remain elusive due to difficulties in protein expression, purification and crystallization. Thus, accurate prediction of membrane protein topology can increase the understanding of membrane protein function. Here, we provide a brief review of the diverse computational methods for predicting membrane protein structure and function, including recent progress and essential bioinformatics tools. Our hope is that this review will be instructive to users studying membrane protein biology in their choice of appropriate bioinformatics methods.

Double superhelix model of high density lipoprotein

High density lipoprotein (HDL), the carrier of so-called "good" cholesterol, serves as the major athero-protective lipoprotein and has emerged as a key therapeutic target for cardiovascular disease. We applied small angle neutron scattering (SANS) with contrast variation and selective isotopic deuteration to the study of nascent HDL to obtain the low resolution structure in solution of the overall time-averaged conformation of apolipoprotein AI (apoA-I) versus the lipid (acyl chain) core of the particle. Remarkably, apoA-I is observed to possess an open helical shape that wraps around a central ellipsoidal lipid phase. Using the low resolution SANS shapes of the protein and lipid core as scaffolding, an all-atom computational model for the protein and lipid components of nascent HDL was developed by integrating complementary structural data from hydrogen/deuterium exchange mass spectrometry and previously published constraints from multiple biophysical techniques. Both SANS data and the new computational model, the double superhelix model, suggest an unexpected structural arrangement of protein and lipids of nascent HDL, an anti-parallel double superhelix wrapped around an ellipsoidal lipid phase. The protein and lipid organization in nascent HDL envisages a potential generalized mechanism for lipoprotein biogenesis and remodeling, biological processes critical to sterol and lipid transport, organismal energy metabolism, and innate immunity.

Interaction and conformational dynamics of membrane-spanning protein helices

Within 1 or 2 decades, the reputation of membrane-spanning alpha-helices has changed dramatically. Once mostly regarded as dull membrane anchors, transmembrane domains are now recognized as major instigators of protein-protein interaction. These interactions may be of exquisite specificity in mediating assembly of stable membrane protein complexes from cognate subunits. Further, they can be reversible and regulatable by external factors to allow for dynamic changes of protein conformation in biological function. Finally, these helices are increasingly regarded as dynamic domains. These domains can move relative to each other in different functional protein conformations. In addition, small-scale backbone fluctuations may affect their function and their impact on surrounding lipid shells. Elucidating the ways by which these intricate structural features are encoded by the amino acid sequences will be a fascinating subject of research for years to come.

New vistas in GPCR 3D structure prediction

Human G-protein coupled receptors (hGPCRs) comprise the most prominent family of validated drug targets. More than 50% of approved drugs reveal their therapeutic effects by targeting this family. Accurate models would greatly facilitate the process of drug discovery and development. However, 3-D structure prediction of GPCRs remains a challenge due to limited availability of resolved structure. The X-ray structures have been solved for only four such proteins. The identity between hGPCRs and the potential templates is mostly less than 30%, well below the level at which sequence alignment can be done regularly. In this study, we analyze a large database of human G-protein coupled receptors that are members of family A in order to optimize usage of the available crystal structures for molecular modeling of hGPCRs. On the basis of our findings in this study, we propose to regard specific parts from the trans-membrane domains of the reference receptor helices as appropriate template for constructing models of other GPCRs, while other residues require other techniques for their remodeling and refinement. The proposed hypothesis in the current study has been tested by modeling human beta2-adrenergic receptor based on crystal structures of bovine rhodopsin (1F88) and human A2A adenosine receptor (3EML). The results have shown some improvement in the quality of the predicted models compared to Modeller software.

RHYTHM--a server to predict the orientation of transmembrane helices in channels and membrane-coils

RHYTHM is a web server that predicts buried versus exposed residues of helical membrane proteins. Starting from a given protein sequence, secondary and tertiary structure information is calculated by RHYTHM within only a few seconds. The prediction applies structural information from a growing data base of precalculated packing files and evolutionary information from sequence patterns conserved in a representative dataset of membrane proteins ('Pfam-domains'). The program uses two types of position specific matrices to account for the different geometries of packing in channels and transporters ('channels') or other membrane proteins ('membrane-coils'). The output provides information on the secondary structure and topology of the protein and specifically on the contact type of each residue and its conservation. This information can be downloaded as a graphical file for illustration, a text file for analysis and statistics and a PyMOL file for modeling purposes. The server can be freely accessed at: URL: http://proteinformatics.de/rhythm.

Gas-phase behavior of noncovalent transmembrane segment complexes

Specific helix oligomerization between transmembrane segments (TMSs) is often promoted by motifs like GxxxG. Disruption of this motif in the transmembrane segments of vesicular stomatitis virus G-protein and of glycophorin A results in a reduced dimerization level studied by in vivo systems like ToxR. This paper reports the influence of sequence motifs like GxxxG in solution and the gas phase.The transmembrane segments may behave differently in the gas and liquid phase, because of the absence of surrounding solvent molecules in the gas phase. Comparison of experiments depending on peptide properties performed in the gas and liquid phase discloses that the peptides retain 'some memory' of their liquid-phase structure in the gas phase. A direct correlation has been found between helicity in solution as determined by circular dichroism and dimerization in the gas phase monitored by electrospray mass spectrometry. These results show that a proper folding in solution is required for oligomerization.On the other hand, sequence-specific oligomerization depending on the GxxxG motif was not observed with the mass spectrometric detection. Further on, neither concentration-dependent complex studies nor studies regarding complex stability in the gas phase - via collision-induced dissociation (CID) - led to sequence-specific differences.Finally, the findings show that in mass spectrometric measurements noncovalent interactions of studied TMSs is rather more dependent on the secondary structure and proper folding than on their primary structure.

Self-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channel

The transmembrane (TM) domain of the M2 channel protein from influenza A is a homotetrameric bundle of alpha-helices and provides a model system for computational approaches to self-assembly of membrane proteins. Coarse-grained molecular dynamics (CG-MD) simulations have been used to explore partitioning into a membrane of M2 TM helices during bilayer self-assembly from lipids. CG-MD is also used to explore tetramerization of preinserted M2 TM helices. The M2 helix monomer adopts a membrane spanning orientation in a lipid (DPPC) bilayer. Multiple extended CG-MD simulations (5 x 5 micros) were used to study the tetramerization of inserted M2 helices. The resultant tetramers were evaluated in terms of the most populated conformations and the dynamics of their interconversion. This analysis reveals that the M2 tetramer has 2x rotationally symmetrical packing of the helices. The helices form a left-handed bundle, with a helix tilt angle of approximately 16 degrees. The M2 helix bundle generated by CG-MD was converted to an atomistic model. Simulations of this model reveal that the bundle's stability depends on the assumed protonation state of the H37 side chains. These simulations alongside comparison with recent x-ray (3BKD) and NMR (2RLF) structures of the M2 bundle suggest that the model yielded by CG-MD may correspond to a closed state of the channel.

Transmembrane helix prediction using amino acid property features and latent semantic analysis

Background

Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of free parameters in their models which are tuned to fit the little data available for training. Further, they are often restricted to the generally accepted topology "cytoplasmic-transmembrane-extracellular" and cannot adapt to membrane proteins that do not conform to this topology. Recent crystal structures of channel proteins have revealed novel architectures showing that the above topology may not be as universal as previously believed. Thus, there is a need for methods that can better predict TM helices even in novel topologies and families.

Results

Here, we describe a new method "TMpro" to predict TM helices with high accuracy. To avoid overfitting to existing topologies, we have collapsed cytoplasmic and extracellular labels to a single state, non-TM. TMpro is a binary classifier which predicts TM or non-TM using multiple amino acid properties (charge, polarity, aromaticity, size and electronic properties) as features. The features are extracted from sequence information by applying the framework used for latent semantic analysis of text documents and are input to neural networks that learn the distinction between TM and non-TM segments. The model uses only 25 free parameters. In benchmark analysis TMpro achieves 95% segment F-score corresponding to 50% reduction in error rate compared to the best methods not requiring an evolutionary profile of a protein to be known. Performance is also improved when applied to more recent and larger high resolution datasets PDBTM and MPtopo. TMpro predictions in membrane proteins with unusual or disputed TM structure (K⁺ channel, aquaporin and HIV envelope glycoprotein) are discussed.

Conclusion

TMpro uses very few free parameters in modeling TM segments as opposed to the very large number of free parameters used in state-of-the-art membrane prediction methods, yet achieves very high segment accuracies. This is highly advantageous considering that high resolution transmembrane information is available only for very few proteins. The greatest impact of TMpro is therefore expected in the prediction of TM segments in proteins with novel topologies. Further, the paper introduces a novel method of extracting features from protein sequence, namely that of latent semantic analysis model. The success of this approach in the current context suggests that it can find potential applications in other sequence-based analysis problems.

Availability

and

Breaking the bottleneck: Eukaryotic membrane protein expression for high-resolution structural studies

The recombinant expression of eukaryotic membrane proteins has been a major stumbling block in efforts to determine their structures. In the last two years, however, five such proteins have yielded high-resolution X-ray or electron diffraction data, opening the prospect of increased throughput for eukaryotic membrane protein structure determination. Here, we summarize the major expression systems available, and highlight technical advances that should facilitate more systematic screening of expression conditions for this physiologically important class of targets.

Membrane protein structural biology--how far can the bugs take us?

Membrane proteins are core components of many essential cellular processes, and high-resolution structural data is therefore highly sought after. However, owing to the many bottlenecks associated with membrane protein crystallization, progress has been slow. One major problem is our inability to obtain sufficient quantities of membrane proteins for crystallization trials. Traditionally, membrane proteins have been isolated from natural sources, or for prokaryotic proteins, expressed by recombinant techniques. We are however a long way away from a streamlined overproduction of eukaryotic proteins. With this technical limitation in mind, we have probed the question as to how far prokaryotic homologues can take us towards a structural understanding of the eukaryotic/human membrane proteome(s).

Computational prediction of atomic structures of helical membrane proteins aided by EM maps

Integral membrane proteins pose a major challenge for protein-structure prediction because only approximately 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane alpha-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of alpha-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the alpha-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.

Retinoid Chromophores as Probes of Membrane Lipid Order

There is a great need for development of independent methods to study the structure and function of membrane-associated proteins and peptides. Polarized light spectroscopy (linear dichroism, LD) using shear-aligned lipid vesicles as model membranes has emerged as a promising tool for the characterization of the binding geometry of membrane-bound biomolecules. Here we explore the potential of retinoic acid, retinol, and retinal to function as probes of the macroscopic alignment of shear-deformed 100 nm liposomes. The retinoids display negative LD, proving their preferred alignment perpendicular to the membrane surface. The magnitude of the LD indicates the order retinoic acid > retinol > retinal regarding the degree of orientation in all tested lipid vesicle types. It is concluded that mainly nonspecific electrostatic interactions govern the apparent orientation of the retinoids within the bilayer. We propose a simple model for how the effective orientation may be related to the polarity of the end groups of the retinoid probes, their insertion depths, and their angular distribution of configurations around the membrane normal. Further, we provide evidence that the retinoids can sense subtle structural differences due to variations in membrane composition and we explore the pH sensitivity of retinoic acid, which manifests in variations in absorption maximum wavelength in membranes of varying surface charge. Based on LD measurements on cholesterol-containing liposomes, the influence of membrane constituents on bending rigidity and vesicle deformation is considered in relation to the macroscopic alignment, as well as to lipid chain order on the microscopic scale.

Molecular dynamics simulation approach for the prediction of transmembrane helix–helix heterodimers assembly

Computational methods are useful to identify favorable structures of transmembrane (TM) helix oligomers when experimental data are not available or when they cannot help to interpret helix-helix association. We report here a global search method using molecular dynamics (MD) simulations to predict the structures of transmembrane homo and heterodimers. The present approach is based only on sequence information without any experimental data and is first applied to glycophorin A to validate the protocol and to the HER2-HER3 heterodimer receptor. The method successfully reproduces the experimental structures of the TM domain of glycophorin A (GpA(TM)) with a root mean square deviation of 1.5 A. The search protocol identifies three energetically stable models of the TM domain of HER2-HER3 receptor with favorable helix-helix arrangement, including right-handed and left-handed coiled-coils. The predicted TM structures exhibit the GxxxG-like motif at the dimer interface which is presumed to drive receptor oligomerization. We demonstrate that native structures of TM domain can be predicted without quantitative experimental data. This search protocol could help to predict structures of the TM domain of HER heterodimer family.

Membrane Protein Structure: Prediction versus Reality

Since high-resolution structural data are still scarce, different kinds of theoretical structure prediction algorithms are of major importance in membrane protein biochemistry. But how well do the current prediction methods perform? Which structural features can be predicted and which cannot? And what can we expect in the next few years?