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.     

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.     

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.     

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.     

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.     

NMR structure of the integral membrane protein OmpX

The structure of the integral membrane protein OmpX from Escherichia coli reconstituted in 60 kDa DHPC micelles (OmpX/DHPC) was calculated from 526 NOE upper limit distance constraints. The structure determination was based on complete sequence-specific assignments for the amide protons and the Val, Leu, and Ile(delta1) methyl groups in OmpX, which were selectively protonated on a perdeuterated background. The solution structure of OmpX in the DHPC micelles consists of a well-defined, eight-stranded antiparallel beta-barrel, with successive pairs of beta-strands connected by mobile loops. Several long-range NOEs observed outside of the transmembrane barrel characterize an extension of a four-stranded beta-sheet beyond the height of the barrel. This protruding beta-sheet is believed to be involved in intermolecular interactions responsible for the biological functions of OmpX. The present approach for de novo structure determination should be quite widely applicable to membrane proteins reconstituted in mixed micelles with overall molecular masses up to about 100 kDa, and may also provide a platform for additional functional studies.     

Prediction of secondary structural content of proteins from their amino acid composition alone. I. New analytic vector decomposition methods

The predictive limits of the amino acid composition for the secondary structural content (percentage of residues in the secondary structural states helix, sheet, and coil) in proteins are assessed quantitatively. For the first time, techniques for prediction of secondary structural content are presented which rely on the amino acid composition as the only information on the query protein. In our first method, the amino acid composition of an unknown protein is represented by the best (in a least square sense) linear combination of the characteristic amino acid compositions of the three secondary structural types computed from a learning set of tertiary structures. The second technique is a generalization of the first one and takes into account also possible compositional couplings between any two sorts of amino acids. Its mathematical formulation results in an eigenvalue/eigenvector problem of the second moment matrix describing the amino acid compositional fluctuations of secondary structural types in various proteins of a learning set. Possible correlations of the principal directions of the eigenspaces with physical properties of the amino acids were also checked. For example, the first two eigenvectors of the helical eigenspace correlate with the size and hydrophobicity of the residue types respectively. As learning and test sets of tertiary structures, we utilized representative, automatically generated subsets of Protein Data Bank (PDB) consisting of non-homologous protein structures at the resolution thresholds ≤1.8Å, ≤2.0Å, ≤2.5Å, and ≤3.0Å. We show that the consideration of compositional couplings improves prediction accuracy, albeit not dramatically. Whereas in the self-consistency test (learning with the protein to be predicted), a clear decrease of prediction accuracy with worsening resolution is observed, the jackknife test (leave the predicted protein out) yielded best results for the largest dataset (≤3.0 Å, almost no difference to the self-consistency test!), i.e., only this set, with more than 400 proteins, is sufficient for stable computation of the parameters in the prediction function of the second method. The average absolute error in predicting the fraction of helix, sheet, and coil from amino acid composition of the query protein are 13.7, 12.6, and 11.4%, respectively with r.m.s. deviations in the range of 8.6 ÷ 11.8% for the 3.0 Å dataset in a jackknife test. The absolute precision of the average absolute errors is in the range of 1 ÷ 3% as measured for other representative subsets of the PDB. Secondary structural content prediction methods found in the literature have been clustered in accordance with their prediction accuracies. To our surprise, much more complex secondary structure prediction methods utilized for the same purpose of secondary structural content prediction achieve prediction accuracies very similar to those of the present analytic techniques, implying that all the information beyond the amino acid composition is, in fact, mainly utilized for positioning the secondary structural state in the sequence but not for determination of the overall number of residues in a secondary structural type. This result implies that higher prediction accuracies cannot be achieved relying solely on the amino acid composition of an unknown query protein as prediction input. Our prediction program SSCP has been made available as a World Wide Web and E-mail service. © 1996 Wiley-Liss, Inc.     

Unique amino acid composition of proteins in halophilic bacteria

The amino acid compositions of proteins from halophilic archaea were compared with those from non-halophilic mesophiles and thermophiles, in terms of the protein surface and interior, on a genome-wide scale. As we previously reported for proteins from thermophiles, a biased amino acid composition also exists in halophiles, in which an abundance of acidic residues was found on the protein surface as compared to the interior. This general feature did not seem to depend on the individual protein structures, but was applicable to all proteins encoded within the entire genome. Unique protein surface compositions are common in both halophiles and thermophiles. Statistical tests have shown that significant surface compositional differences exist among halophiles, non-halophiles, and thermophiles, while the interior composition within each of the three types of organisms does not significantly differ. Although thermophilic proteins have an almost equal abundance of both acidic and basic residues, a large excess of acidic residues in halophilic proteins seems to be compensated by fewer basic residues. Aspartic acid, lysine, asparagine, alanine, and threonine significantly contributed to the compositional differences of halophiles from meso- and thermophiles. Among them, however, only aspartic acid deviated largely from the expected amount estimated from the dinucleotide composition of the genomic DNA sequence of the halophile, which has an extremely high G+C content (68%). Thus, the other residues with large deviations (Lys, Ala, etc.) from their non-halophilic frequencies could have arisen merely as "dragging effects" caused by the compositional shift of the DNA, which would have changed to increase principally the fraction of aspartic acid alone.     

基于氨基酸和二肽组成的蛋白质四级结构分类研究

基于最近邻居算法,从蛋白质一级序列出发,利用蛋白质序列氨基酸组成、二肤组成以及混合组成方法对蛋白质单聚体、二聚体、三聚体、四聚体、五聚体、六聚体和八聚体进行分类研究。结果表明:采用二肽组成编码方法的预洲效果最好,Jackknife检验和独立测试集检验的总体预测精度分别达到90.83%和95.48%,比相同数据集上基于伪氨基酸组成和组分耦合预测的方法提高了12和15个百分点;特别是对于五聚体蛋白,预测精度分别提高了90和50个百分点;说明二肽组成对于蛋白质四级结构分类研究是一种非常有效的特征提取方法。     

The modified Mahalanobis Discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition

The outer membrane proteins (OMPs) are β-barrel membrane proteins that performed lots of biology functions. The discriminating OMPs from other non-OMPs is a very important task for understanding some biochemical process. In this study, a method that combines increment of diversity with modified Mahalanobis Discriminant, called IDQD, is presented to predict 208 OMPs, 206 transmembrane helical proteins (TMHPs) and 673 globular proteins (GPs) by using Chou's pseudo amino acid compositions as parameters. The overall accuracy of jackknife cross-validation is 93.2% and 96.1%, respectively, for three datasets (OMPs, TMHPs and GPs) and two datasets (OMPs and non-OMPs). These predicted results suggest that the method can be effectively applied to discriminate OMPs, TMHPs and GPs. And it also indicates that the pseudo amino acid composition can better reflect the core feature of membrane proteins than the classical amino acid composition.     

Application of three-dimensional molecular hydrophobicity potential to the analysis of spatial organization of membrane domains in proteins: I. Hydrophobic properties of transmembrane segments of Na+, K+-ATPase

A new computer-aided molecular modeling approach based on the concept of three-dimensional (3D) molecular hydrophobicity potential has been developed to calculate the spatial organization of intramembrane domains in proteins. The method has been tested by calculating the arrangement of membrane-spanning segments in the photoreaction center ofRhodopseudomonas viridis and comparing the results obtained with those derived from the X-ray data. We have applied this computational procedure to the analysis of interhelical packing in membrane moiety of Na⁺, K⁺-ATPase. The work consists of three parts. In Part I, 3D distributions of electrostatic and molecular hydrophobicity potentials on the surfaces of transmembrane helical peptides were computed and visualized. The hydrophobic and electrostatic properties of helices are discussed from the point of view of their possible arrangement within the protein molecule. Interlocation of helical segments connected with short extramembrane loops found by means of optimization of their hydrophobic/hydrophilic contacts is considered in Part II. The most probable 3D model of packing of helical peptides in the membrane domain of Na⁺, K⁺-ATPase is discussed in the final part of the work.     

利用伪氨基酸组分预测分枝杆菌膜蛋白类型

膜蛋白是重要的药物靶位点,对膜蛋白类型的研究有助于药物的成功设计,因此正确预测膜蛋白类型对于药物研发是十分必要的。本文采用由274条分枝杆菌膜蛋白序列组成的一致性小于40%的数据集,以经过优化的伪氨基酸组分为特征,利用支持向量机分类算法预测分枝杆菌膜蛋白类型,在Jackknife检验下,得到85.4%的总体准确率和72.2%的平均准确率。结果说明,该方法可用于分枝杆菌膜蛋白类型的识别,将有助于抗分枝杆菌药物的开发。     

Amino acid composition analysis of secondary transport proteins from Escherichia coli with relation to functional classification,ligand specificity and structure

We have performed an amino acid composition (AAC) analysis of the complete sequences for 235 secondary transport proteins from Escherichia coli, which have functions in the uptake and export of organic and inorganic metabolites, efflux of drugs and in controlling membrane potential. This revealed the trends in content for specific amino acid types and for combinations of amino acids with similar physicochemical properties. In certain proteins or groups of proteins, the so-called spikes of high content for a specific amino acid type or combination of amino acids were identified and confirmed statistically, which in some cases could be directly related to function and ligand specificity. This was prevalent in proteins with a function of multidrug or metal ion efflux. Any tool that can help in identifying bacterial multidrug efflux proteins is important for a better understanding of this mechanism of antibiotic resistance. Phylogenetic analysis based on sequence alignments and comparison of sequences at the N- and C-terminal ends confirmed transporter Family classification. Locations of specific amino acid types in some of the proteins that have crystal structures (EmrE, LacY, AcrB) were also considered to help link amino acid content with protein function. Though there are limitations, this work has demonstrated that a basic analysis of AAC is a useful tool to use in combination with other computational and experimental methods for classifying and investigating function and ligand specificity in a large group of transport or other membrane proteins, including those that are molecular targets for development of new drugs.     

Ratiocinative screen of eukaryotic integral membrane protein expression and solubilization for structure determination

Persistent hurdles impede the successful determination of high-resolution crystal structures of eukaryotic integral membrane proteins (IMP). We designed a high-throughput structural genomics oriented pipeline that seeks to minimize effort in uncovering high-quality, responsive non-redundant targets for crystallization. This “discovery-oriented” pipeline sidesteps two significant bottlenecks in the IMP structure determination pipeline: expression and membrane extraction with detergent. In addition, proteins that enter the pipeline are then rapidly vetted by their presence in the included volume on a size-exclusion column—a hallmark of well-behaved IMP targets. A screen of 384 rationally selected eukaryotic IMPs in baker’s yeast Saccharomyces cerevisiae is outlined to demonstrate the results expected when applying this discovery-oriented pipeline to whole-organism membrane proteomes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Franklin A. Hays and Zygy Roe-Zurz have contributed equally to this work.     

Comparative analysis and "expression space" coverage of the production of prokaryotic membrane proteins for structural genomics

Membrane proteins comprise up to one-third of prokaryotic and eukaryotic genomes, but only a very small number of membrane protein structures are known. Membrane proteins are challenging targets for structural biology, primarily due to the difficulty in producing and purifying milligram quantities of these proteins. We are evaluating different methods to produce and purify large numbers of prokaryotic membrane proteins for subsequent structural and functional analysis. Here, we present the comparative expression data for 37 target proteins, all of them secondary transporters, from the mesophilic organism Salmonella typhimurium and the two hyperthermophilic organisms Aquifex aeolicus and Pyrococcus furiosus in three different Escherichia coli expression vectors. In addition, we study the use of Lactococcus lactis as a host for integral membrane protein expression. Overall, 78% of the targets were successfully produced under at least one set of conditions. Analysis of these results allows us to assess the role of different variables in increasing "expression space" coverage for our set of targets. This analysis implies that to maximize the number of nonhomologous targets that are expressed, orthologous targets should be chosen and tested in two vectors with different types of promoters, using C-terminal tags. In addition, E. coli is shown to be a robust host for the expression of prokaryotic transporters, and is superior to L. lactis. These results therefore suggest appropriate strategies for high-throughput heterologous overproduction of membrane proteins.     

Constructing amino acid residue substitution classes maximally indicative of local protein structure

Using an information theoretic formalism, we optimize classes of amino acid substitution to be maximally indicative of local protein structure. Our statistically-derived classes are loosely identifiable with the heuristic constructions found in previously published work. However, while these other methods provide a more rigid idealization of physicochemically constrained residue substitution, our classes provide substantially more structural information with many fewer parameters. Moreover, these substitution classes are consistent with the paradigmatic view of the sequence-to-structure relationship in globular proteins which holds that the three-dimensional architecture is predominantly determined by the arrangement of hydrophobic and polar side chains with weak constraints on the actual amino acid identities. More specific constraints are imposed on the placement of prolines, glycines, and the charged residues. These substitution classes have been used in highly accurate predictions of residue solvent accessibility. They could also be used in the identification of homologous proteins, the construction and refinement of multiple sequence alignments, and as a means of condensing and codifying the information in multiple sequence alignments for secondary structure prediction and tertiary fold recognition. © 1996 Wiley-Liss, Inc.     

Molecular modeling of c-erbB2 receptor dimerization: Coiled-coil structure of wild and oncogenic transmembrane domains—Stabilization by interhelical hydrogen bonds in the oncogenic form

Dimerization models of c-erbB2 transmembrane domains (Leu651-Ile675) are studied by molecular mechanics and molecular dynamics simulations. Both wild and Glu mutated transmembrane helices exhibit the same relative orientation for favorable associations and dimerize preferentially in left-handed coiled-coil structures. The mutation point 659 belongs to the interfacing residues, and in the transforming domain, symmetric hydrogen bonds between Glu carboxylic groups stabilize the dimeric structure. The same helix packing found for the wild dimers, except side-chain—side-chain hydrogen bonds, suggests that the transmembrane domains dimerize according to similar process. Structural and energetical characterization of the models are presented. © 1997 John Wiley & Sons, Inc. Biopoly 42: 157–168, 1997