Assembly of transmembrane helices of simple polytopic membrane proteins from sequence conservation patterns

The transmembrane (TM) domains of most membrane proteins consist of helix bundles. The seemingly simple task of TM helix bundle assembly has turned out to be extremely difficult. This is true even for simple TM helix bundle proteins, i.e., those that have the simple form of compact TM helix bundles. Herein, we present a computational method that is capable of generating native-like structural models for simple TM helix bundle proteins having modest numbers of TM helices based on sequence conservation patterns. Thus, the only requirement for our method is the presence of more than 30 homologous sequences for an accurate extraction of sequence conservation patterns. The prediction method first computes a number of representative well-packed conformations for each pair of contacting TM helices, and then a library of tertiary folds is generated by overlaying overlapping TM helices of the representative conformations. This library is scored using sequence conservation patterns, and a subsequent clustering analysis yields five final models. Assuming that neighboring TM helices in the sequence contact each other (but not that TM helices A and G contact each other), the method produced structural models of Calpha atom root-mean-square deviation (CA RMSD) of 3-5 A from corresponding crystal structures for bacteriorhodopsin, halorhodopsin, sensory rhodopsin II, and rhodopsin. In blind predictions, this type of contact knowledge is not available. Mimicking this, predictions were made for the rotor of the V-type Na(+)-adenosine triphosphatase without such knowledge. The CA RMSD between the best model and its crystal structure is only 3.4 A, and its contact accuracy reaches 55%. Furthermore, the model correctly identifies the binding pocket for sodium ion. These results demonstrate that the method can be readily applied to ab initio structure prediction of simple TM helix bundle proteins having modest numbers of TM helices.     

Differentiation between transmembrane helices and peripheral helices by the deconvolution of circular dichroism spectra of membrane proteins.

The interpretation of the circular dichroism (CD) spectra of proteins to date requires additional secondary structural information of the proteins to be analyzed, such as X-ray or NMR data. Therefore, these methods are inappropriate for a CD database whose secondary structures are unknown, as in the case of the membrane proteins. The convex constraint analysis algorithm (Perczel, A., Hollósi, M., Tusnády, G., & Fasman, G. D., 1991, Protein Eng. 4, 669-679), on the other hand, operates only on a collection of spectral data to extract the common spectral components with their spectral weights. The linear combinations of these derived "pure" CD curves can reconstruct the original data set with great accuracy. For a membrane protein data set, the five-component spectra so obtained from the deconvolution consisted of two different types of alpha helices (the alpha helix in the soluble domain and the alpha T helix, for the transmembrane alpha helix), a beta-pleated sheet, a class C-like spectrum related to beta turns, and a spectrum correlated with the unordered conformation. The deconvoluted CD spectrum for the alpha T helix was characterized by a positive red-shifted band in the range 195-200 nm (+95,000 deg cm2 dmol-1), with the intensity of the negative band at 208 nm being slightly less negative than that of the 222-nm band (-50,000 and -60,000 deg cm2 dmol-1, respectively) in comparison with the regular alpha helix, with a positive band at 190 nm and two negative bands at 208 and 222 nm with magnitudes of +70,000, -30,000, and -30,000 deg cm2 dmol-1, respectively.     

Comparative analysis of amino acid distributions in integral membrane proteins from 107 genomes

We have performed a comparative analysis of amino acid distributions in predicted integral membrane proteins from a total of 107 genomes. A procedure for identification of membrane spanning helices was optimized on a homology-reduced data set of 170 multi-spanning membrane proteins with experimentally determined topologies. The optimized method was then used for extraction of highly reliable partial topologies from all predicted membrane proteins in each genome, and the average biases in amino acid distributions between loops on opposite sides of the membrane were calculated. The results strongly support the notion that a biased distribution of Lys and Arg residues between cytoplasmic and extra-cytoplasmic segments (the positive-inside rule) is present in most if not all organisms.     

Distinct character in hydrophobicity of amino acid compositions of mitochondrial proteins

A compact mitochondrial gene contains all essential information about the synthesis of mitochondrial proteins which play their roles in a small compartment of the mitochondrium. Almost no noncoding regions have been found through the gene, but a necessary set of tRNAs for the 20 amino acids is provided for biosynthesis, some of them coding different amino acids from those in a usual cell. Since the gene is so compact that the produced proteins would have some characteristic aspects for the mitochondrium, amino acid compositions of mitochondrial proteins (mt-proteins) were examined in the 20-dimensional composition space. The results show that compositions of proteins translated from the mitochondrial genes have a distinct character having more hydrophobic content than others, which is illustrated by a clustered distribution in the multidimensional composition space. The cluster is located at the tail edge of the global distribution pattern of a Gaussian shape for other various kinds of proteins in the space. The mt-proteins are rich in hydrophobic amino acids as is a membrane protein, but are different from other membrane proteins in a lesser content of Val. A good correlation found between the base and amino acid compositions for the mitochondria was examined in comparison to those of organisms such as thermophilic bacterium having an extreme G-C-rich base composition.     

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.     

Long membrane helices and short loops predicted less accurately

Low-resolution experiments suggest that most membrane helices span over 17-25 residues and that most loops between two helices are longer than 15 residues. Both constraints have been used explicitly in the development of prediction methods. Here, we compared the largest possible sequence-unique data sets from high- and low-resolution experiments. For the high-resolution data, we found that only half of the helices fall into the expected length interval and that half of the loops were shorter than 10 residues. We compared the accuracy of detecting short loops and long helices for 28 advanced and simple prediction methods: All methods predicted short loops less accurately than longer ones. In particular, loops shorter than 7 residues appeared to be very difficult to detect by current methods. Similarly, all methods tended to be more accurate for longer than for shorter helices. However, helices with more than 32 residues were predicted less accurately than all other helices. Our findings may suggest particular strategies for improving predictions of membrane helices.     

A structural dissection of amino acid substitutions in helical transmembrane proteins

The evolution of protein folds is under strong constraints from their surrounding environment. Although folding in water‐soluble proteins is driven primarily by hydrophobic forces, the nature of the forces that determine the folding and stability of transmembrane proteins are still not fully understood. Furthermore, the chemically heterogeneous lipid bilayer has a non‐uniform effect on protein structure. In this article, we attempt to get an insight into the nature of this effect by examining the impact of various types of local structure environment on amino acid substitution, based on alignments of high‐resolution structures of polytopic helical transmembrane proteins combined with sequences of close homologs. Compared to globular proteins, burying amino acid sidechains, especially hydrophilic ones, led to a lower increase in conservation in both the lipid‐water interface region and the hydrocarbon core region. This observation is due to surface residues in HTM proteins especially in the HC region being relatively highly conserved, suggesting higher evolutionary constraints from their specific interactions with the surrounding lipid molecules. Polar and small residues, particularly Pro and Gly, show a noticeable increase in conservation as they are positioned more towards the centre of the membrane, which is consistent with their recognized key roles in structural stability. In addition, the examination of hydrogen bonds in the membrane environment identified some exposed hydrophilic residues being better conserved when not hydrogen‐bonded to other residues, supporting the importance of lipid‐protein sidechain interactions. The conclusions presented in this study highlight the distinct features of substitution matrices that take into account the membrane environment, and their potential role in improving sequence‐structure alignments of transmembrane proteins. Proteins 2010; © 2010 Wiley‐Liss, Inc.     

Modeling of the structural features of integral-membrane proteins reverse-environment prediction of integral membrane protein structure (REPIMPS)

The Profiles-3D application, an inverse-folding methodology appropriate for water-soluble proteins, has been modified to allow the determination of structural properties of integral-membrane proteins (IMPs) and for testing the validity of solved and model structures of IMPs. The modification, known as reverse-environment prediction of integral membrane protein structure (REPIMPS), takes into account the fact that exposed areas of side chains for many residues in IMPs are in contact with lipid and not the aqueous phase. This (1) allows lipid-exposed residues to be classified into the correct physicochemical environment class, (2) significantly improves compatibility scores for IMPs whose structures have been solved, and (3) reduces the possibility of rejecting a three-dimensional structure for an IMP because the presence of lipid was not included. Validation tests of REPIMPS showed that it (1) can locate the transmembrane domain of IMPs with single transmembrane helices more frequently than a range of other methodologies, (2) can rotationally orient transmembrane helices with respect to the lipid environment and surrounding helices in IMPs with multiple transmembrane helices, and (3) has the potential to accurately locate transmembrane domains in IMPs with multiple transmembrane helices. We conclude that correcting for the presence of the lipid environment surrounding the transmembrane segments of IMPs is an essential step for reasonable modeling and verification of the three-dimensional structures of these proteins.     

Amino acid composition analysis of human secondary transport proteins and implications for reliable membrane topology prediction

Secondary transporters in humans are a large group of proteins that transport a wide range of ions, metals, organic and inorganic solutes involved in energy transduction, control of membrane potential and osmotic balance, metabolic processes and in the absorption or efflux of drugs and xenobiotics. They are also emerging as important targets for development of new drugs and as target sites for drug delivery to specific organs or tissues. We have performed amino acid composition (AAC) and phylogenetic analyses and membrane topology predictions for 336 human secondary transport proteins and used the results to confirm protein classification and to look for trends and correlations with structural domains and specific substrates and/or function. Some proteins showed statistically high contents of individual amino acids or of groups of amino acids with similar physicochemical properties. One recurring trend was a correlation between high contents of charged and/or polar residues with misleading results in predictions of membrane topology, which was especially prevalent in Mitochondrial Carrier family proteins. We demonstrate how charged or polar residues located in the middle of transmembrane helices can interfere with their identification by membrane topology tools resulting in missed helices in the prediction. Comparison of AAC in the human proteins with that in 235 secondary transport proteins from Escherichia coli revealed similar overall trends along with differences in average contents for some individual amino acids and groups of similar amino acids that are presumed to result from a greater number of functions and complexity in the higher organism.     

MPEx: A tool for exploring membrane proteins

Hydropathy plot methods form a cornerstone of membrane protein research, especially in the early stages of biochemical and structural characterization. Membrane Protein Explorer (MPEx), described in this article, is a refined and versatile hydropathy‐plot software tool for analyzing membrane protein sequences. MPEx is highly interactive and facilitates the characterization and identification of favorable protein transmembrane regions using experiment‐based physical and biological hydrophobicity scales. Besides allowing the consequences of sequence mutations to be examined, it provides tools for aiding the design of membrane‐active peptides. MPEx is freely available as a Java Web Start application from our web site at http://blanco.biomol.uci.edu/mpex .     

E(z), a depth-dependent potential for assessing the energies of insertion of amino acid side-chains into membranes: derivation and applications to determining the orientation of transmembrane and interfacial helices

We have developed an empirical residue-based potential (E(z) potential) for protein insertion in lipid membranes. Propensities for occurrence as a function of depth in the bilayer were calculated for the individual amino acid types from their distribution in known structures of helical membrane proteins. The propensities were then fit to continuous curves and converted to a potential using a reverse-Boltzman relationship. The E(z) potential demonstrated a good correlation with experimental data such as amino acid transfer free energy scales (water to membrane center and water to interface), and it incorporates transmembrane helices of varying composition in the membrane with trends similar to those obtained with translocon-mediated insertion experiments. The potential has a variety of applications in the analysis of natural membrane proteins as well as in the design of new ones. It can help in calculating the propensity of single helices to insert in the bilayer and estimate their tilt angle with respect to the bilayer normal. It can be utilized to discriminate amphiphilic helices that assume a parallel orientation at the membrane interface, such as those of membrane-active peptides. In membrane protein design applications, the potential allows an environment-dependent selection of amino acid identities.     

Genome-wide analysis of integral membrane proteins from eubacterial,archaean, and eukaryotic organisms.

We have carried out detailed statistical analyses of integral membrane proteins of the helix-bundle class from eubacterial, archaean, and eukaryotic organisms for which genome-wide sequence data are available. Twenty to 30% of all ORFs are predicted to encode membrane proteins, with the larger genomes containing a higher fraction than the smaller ones. Although there is a general tendency that proteins with a smaller number of transmembrane segments are more prevalent than those with many, uni-cellular organisms appear to prefer proteins with 6 and 12 transmembrane segments, whereas Caenorhabditis elegans and Homo sapiens have a slight preference for proteins with seven transmembrane segments. In all organisms, there is a tendency that membrane proteins either have many transmembrane segments with short connecting loops or few transmembrane segments with large extra-membraneous domains. Membrane proteins from all organisms studied, except possibly the archaeon Methanococcus jannaschii, follow the so-called "positive-inside" rule; i.e., they tend to have a higher frequency of positively charged residues in cytoplasmic than in extra-cytoplasmic segments.     

Simultaneous prediction of protein secondary structure and transmembrane spans

Prediction of transmembrane spans and secondary structure from the protein sequence is generally the first step in the structural characterization of (membrane) proteins. Preference of a stretch of amino acids in a protein to form secondary structure and being placed in the membrane are correlated. Nevertheless, current methods predict either secondary structure or individual transmembrane states. We introduce a method that simultaneously predicts the secondary structure and transmembrane spans from the protein sequence. This approach not only eliminates the necessity to create a consensus prediction from possibly contradicting outputs of several predictors but bears the potential to predict conformational switches, i.e., sequence regions that have a high probability to change for example from a coil conformation in solution to an α‐helical transmembrane state. An artificial neural network was trained on databases of 177 membrane proteins and 6048 soluble proteins. The output is a 3 × 3 dimensional probability matrix for each residue in the sequence that combines three secondary structure types (helix, strand, coil) and three environment types (membrane core, interface, solution). The prediction accuracies are 70.3% for nine possible states, 73.2% for three‐state secondary structure prediction, and 94.8% for three‐state transmembrane span prediction. These accuracies are comparable to state‐of‐the‐art predictors of secondary structure (e.g., Psipred) or transmembrane placement (e.g., OCTOPUS). The method is available as web server and for download at www.meilerlab.org . Proteins 2013; 81:1127–1140. © 2013 Wiley Periodicals, Inc.     

Estimating the length of transmembrane helices using Z-coordinate predictions

Zpred2 is an improved version of ZPRED, a predictor for the Z-coordinates of alpha-helical membrane proteins, that is, the distance of the residues from the center of the membrane. Using principal component analysis and a set of neural networks, Zpred2 analyzes data extracted from the amino acid sequence, the predicted topology, and evolutionary profiles. Zpred2 achieves an average accuracy error of 2.18 A (2.17 A when an independent test set is used), an improvement by 15% compared to the previous version. We show that this accuracy is sufficient to enable the predictions of helix lengths with a correlation coefficient of 0.41. As a comparison, two state-of-the-art HMM-based topology prediction methods manage to predict the helix lengths with a correlation coefficient of less than 0.1. In addition, we applied Zpred2 to two other problems, the re-entrant region identification and model validation. Re-entrants were able to be detected with a certain consistency, but not better than with previous approaches, while incorrect models as well as mispredicted helices of transmembrane proteins could be distinguished based on the Z-coordinate predictions.     

The topological analysis of integral cytoplasmic membrane proteins

Summary We review three general approaches to determining the topology of integral cytoplasmic membrane proteins. (i) Inspection of the amino acid sequence and use of algorithms to predict membrane spanning segments allows the construction of topological models. For many proteins, the mere identification of such segments and an analysis of the distribution of basic amino acids in hydrophilic domains leads to correct structure predictions. For others, additional factors must come into play in determining topology, (ii) Gene fusion analysis of membrane proteins, in many cases, leads to complete topological models. Such analyses have been carried out in both bacteria and in the yeast Saccharomyces cerevisiae. Conflicts between results from gene fusion analysis and other approaches can be used to explore details of the process of membrane protein assembly. For instance, anomalies in gene fusion studies contributed evidence for the important role of basic amino acids in determining topolog. (iii) Biochemical probes and the site of natural biochemical modifications of membrane proteins give information on their topology. Chemical modifiers, proteases and antibodies made to different domains of a membrane protein can identify which segments of the protein are in the cytoplasm and which are on the extracytoplasmic side of the membrane. Sites of such modifications as glycosylation and phosphorylation help to specify the location of particular hydrophilic domains. The advantages and limitations of these methods are discussed.This work was supported by a fellowship from the National Institute of General Medical Sciences to B.T., by a grant from the National Science Foundation to D.B. and by a grant from the National Institutes of Health to J.B.. J.B. is an American Cancer Society Research Professor.     

Internal gene duplication in the evolution of prokaryotic transmembrane proteins

We investigated the evolution of transmembrane (TM) topology by detecting partial sequence repeats in TM protein sequences and analyzing them in detail. A total of 377 sequences that seem to have evolved by internal gene duplication events were found among 38,124 predicted TM protein sequences (except for single-spannings) from 87 prokaryotic genomes. Various types of internal duplication patterns were identified in these sequences. The majority of them are diploid-type (including quasi-diploid-type) duplication in which a primordial protein sequence was duplicated internally to become an extant TM protein with twice as many TM segments as the primordial one, and the remaining ones are partial duplications including triploid-type. The diploid-type repeats are recognized in many 8-tms, 10-tms and 12-tms TM protein sequences, suggesting the diploid-type duplication was a principle mechanism in the evolutionary development of these types of TM proteins. The "positive-inside" rule is satisfied in whole sequences of both 10-tms and 8-tms TM proteins and in both halves of 10-tms proteins while not necessarily in the second half of 8-tms proteins, providing fit examples of "internal divergent topology evolution" likely occurred after a diploid-type internal duplication event. From analyzing the partial duplication patterns, several evolutionary pathways were recognized for 6-tms TM proteins, i.e. from primordial 2-tms, 3-tms and 4-tms TM proteins to extant 6-tms proteins. Similarly, the duplication pattern analysis revealed plausible evolution scenarios that 7-tms TM proteins have arisen from 3-tms, 4-tms and 5-tms TM protein precursors via partial internal gene duplications.     

Direct correlation between proteins' folding rates and their amino acid compositions: an ab initio folding rate prediction

Discovering the mechanism of protein folding, in molecular biology, is a great challenge. A key step to this end is to find factors that correlate with protein folding rates. Over the past few years, many empirical parameters, such as contact order, long-range order, total contact distance, secondary structure contents, have been developed to reflect the correlation between folding rates and protein tertiary or secondary structures. However, the correlation between proteins' folding rates and their amino acid compositions has not been explored. In the present work, we examined systematically the correlation between proteins' folding rates and their amino acid compositions for two-state and multistate folders and found that different amino acids contributed differently to the folding progress. The relation between the amino acids' molecular weight and degeneracy and the folding rates was examined, and the role of hydrophobicity in the protein folding process was also inspected. As a consequence, a new indicator called composition index was derived, which takes no structure factors into account and is merely determined by the amino acid composition of a protein. Such an indicator is found to be highly correlated with the protein's folding rate (r > 0.7). From the results of this work, three points of concluding remarks are evident. (1) Two-state folders and multistate folders have different rate-determining amino acids. (2) The main determining information of a protein's folding rate is largely reflected in its amino acid composition. (3) Composition index may be the best predictor for an ab initio protein folding rate prediction directly from protein sequence from the standpoint of practical application.     

The interplay between the clustering of transmembrane proteins and coupling of anchored membrane proteins

Clustering of membrane proteins plays an important role in many cellular activities such as protein sorting and signal transduction. In this study, we used dissipative particle dynamics simulation method to investigate the clustering of anchored membrane proteins (AMPs) in the presence of transmembrane proteins (TMPs). First, our simulation results show that clustering of AMPs and that of TMPs are in fact interdependent, and depending on their hydrophobic length, both protein mixing and protein demixing are observed. Especially, the protein demixing occurs only when the hydrophobic mismatch of TMPs is negative while that of AMPs is positive. Second, our simulation results indicate that the clustering of TMPs also modulates the coupling of the clustering of AMPs in both leaflets. On the one hand, the coupling between AMPs in different leaflets will be strongly restrained if TMPs form protein mixing with AMPs in one leaflet and protein demixing with AMPs in the other leaflet. On the other hand, the coupling between AMPs can be enhanced or mediated by TMPs when TMPs mix with AMPs in both leaflets. Our results may have some implications on our understanding of how different types of membrane proteins cluster and provide a possible explanation of how TMPs participate in signal transduction across cellular membranes.     

Effects of amino acid composition, finite size of proteins, and sparse statistics on distance-dependent statistical pair potentials

Statistical distance dependent pair potentials are frequently used in a variety of folding, threading, and modeling studies of proteins. The applicability of these types of potentials is tightly connected to the reliability of statistical observations. We explored the possible origin and extent of false positive signals in statistical potentials by analyzing their distance dependence in a variety of randomized protein-like models. While on average potentials derived from such models are expected to equal zero at any distance, we demonstrate that systematic and significant distortions exist. These distortions originate from the limited statistical counts in local environments of proteins and from the limited size of protein structures at large distances. We suggest that these systematic errors in statistical potentials are connected to the dependence of amino acid composition on protein size and to variation in protein sizes. Additionally, atom-based potentials are dominated by a false positive signal that is due to correlation among distances measured from atoms of one residue to atoms of another residue. The significance of residue-based pairwise potentials at various spatial pair separations was assessed in this study and it was found that as few as approximately 50% of potential values were statistically significant at distances below 4 A, and only at most approximately 80% of them were significant at larger pair separations. A new definition for reference state, free of the observed systematic errors, is suggested. It has been demonstrated to generate statistical potentials that compare favorably to other publicly available ones.     

Comparing side chain packing in soluble proteins,protein‐protein interfaces,and transmembrane proteins

We compare side chain prediction and packing of core and non‐core regions of soluble proteins, protein‐protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high‐resolution crystal structures of these 3 protein classes. We show that the solvent‐inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein‐protein interfaces and in the membrane‐exposed regions of transmembrane proteins can be predicted by the hard‐sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent‐inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within ) up to a relative solvent accessibility, , for all 3 protein classes. Our results show that % of the interface regions in protein complexes are “core”, that is, densely packed with side chain conformations that can be accurately predicted using the hard‐sphere model. We propose packing fraction as a metric that can be used to distinguish real protein‐protein interactions from designed, non‐binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins.