Using hydropathy features for function prediction of membrane proteins

A novel alignment-free method for computing functional similarity of membrane proteins based on features of hydropathy distribution is presented. The features of hydropathy distribution are used to represent protein families as hydropathy profiles. The profiles statistically summarize the hydropathy distribution of member proteins. The summation is made by using hydropathy features that numerically represent structurally/functionally significant portions of protein sequences. The hydropathy profiles are numerical vectors that are points in a high dimensional ‘hydropathy’ space. Their similarities are identified by projection of the space onto principal axes. Here, the approach is applied to the secondary transporters. The analysis using the presented approach is validated by the standard classification of the secondary transporters. The presented analysis allows for prediction of function attributes for proteins of uncharacterized families of secondary transporters. The results obtained using the presented analysis may help to characterize unknown function attributes of secondary transporters. They also show that analysis of hydropathy distribution can be used for function prediction of membrane proteins.     

Classification of 29 families of secondary transport proteins into a single structural class using hydropathy profile analysis

A classification scheme for membrane proteins is proposed that clusters families of proteins into structural classes based on hydropathy profile analysis. The averaged hydropathy profiles of protein families are taken as fingerprints of the 3D structure of the proteins and, therefore, are able to detect more distant evolutionary relationships than amino acid sequences. A procedure was developed in which hydropathy profile analysis is used initially as a filter in a BLAST search of the NCBI protein database. The strength of the procedure is demonstrated by the classification of 29 families of secondary transporters into a single structural class, termed ST[3]. An exhaustive search of the database revealed that the 29 families contain 568 unique sequences. The proteins are predominantly from prokaryotic origin and most of the characterized transporters in ST[3] transport organic and inorganic anions and a smaller number are Na(+)/H(+) antiporters. All modes of energy coupling (symport, antiport, uniport) are found in structural class ST[3]. The relevance of the classification for structure/function prediction of uncharacterised transporters in the class is discussed.     

A new method for identification of protein (sub)families in a set of proteins based on hydropathy distribution in proteins

Structural similarity among proteins is reflected in the distribution of hydropathicity along the amino acids in the protein sequence. Similarities in the hydropathy distributions are obvious for homologous proteins within a protein family. They also were observed for proteins with related structures, even when sequence similarities were undetectable. Here we present a novel method that employs the hydropathy distribution in proteins for identification of (sub)families in a set of (homologous) proteins. We represent proteins as points in a generalized hydropathy space, represented by vectors of specifically defined features. The features are derived from hydropathy of the individual amino acids. Projection of this space onto principal axes reveals groups of proteins with related hydropathy distributions. The groups identified correspond well to families of structurally and functionally related proteins. We found that this method accurately identifies protein families in a set of proteins, or subfamilies in a set of homologous proteins. Our results show that protein families can be identified by the analysis of hydropathy distribution, without the need for sequence alignment.     

Membrane topology prediction by hydropathy profile alignment: membrane topology of the Na(+)-glutamate transporter GltS

Structural classification of families of membrane proteins by bioinformatics techniques has become a critical aspect of membrane protein research. We have proposed hydropathy profile alignment to identify structural homology between families of membrane proteins. Here, we demonstrate experimentally that two families of secondary transporters, the ESS and 2HCT families, indeed share similar folds. Members of the two families show highly similar hydropathy profiles but cannot be shown to be homologous by sequence similarity. A structural model was predicted for the ESS family transporters based upon an existing model of the 2HCT family transporters. In the model, the transporters fold into two domains containing five transmembrane segments and a reentrant or pore-loop each. The two pore-loops enter the membrane embedded part of the proteins from opposite sides of the membrane. The model was verified by accessibility studies of cysteine residues in single-Cys mutants of the Na+-glutamate transporter GltS of Escherichia coli, a member of the ESS family. Cysteine residues positioned in predicted periplasmic loops were accessible from the periplasm by a bulky, membrane-impermeable thiol reagent, while cysteine residues in cytoplasmic loops were not. Furthermore, two cysteine residues in the predicted pore-loop entering the membrane from the cytoplasmic side were shown to be accessible for small, membrane-impermeable thiol reagents from the periplasm, as was demonstrated before for the Na+-citrate transporter CitS of Klebsiella pneumoniae, a member of the 2HCT family. The data strongly suggests that GltS of the ESS family and CitS of the 2HCT family share the same fold as was predicted by comparing the averaged hydropathy profiles of the two families.     

Sequence and hydropathy profile analysis of two classes of secondary transporters

A structural class in the MemGen classification of membrane proteins is a set of evolutionary related proteins sharing a similar global fold. A structural class contains both closely related pairs of proteins for which homology is clear from sequence comparison and very distantly related pairs, for which it is not possible to establish homology based on sequence similarity alone. In the latter case the evolutionary link is based on hydropathy profile analysis. Here, we use these evolutionary related sets of proteins to analyze the relationship between E-values in BLAST searches, sequence similarities in multiple sequence alignments and structural similarities in hydropathy profile analyses. Two structural classes of secondary transporters termed ST[3], which includes the Ion Transporter (IT) superfamily and ST[4], which includes the DAACS family (TC# 2.A.23) were extracted from the NCBI protein database. ST[3] contains 2051 unique sequences distributed over 32 families and 59 subfamilies. ST[4] is a smaller class containing 399 unique sequences distributed over 2 families and 7 subfamilies. One subfamily in ST[4] contains a new class of binding protein dependent secondary transporters. Comparison of the averaged hydropathy profiles of the subfamilies in ST[3] and ST[4] revealed that the two classes represent different folds. Divergence of the sequences in ST[4] is much smaller than observed in ST[3], suggesting different constraints on the proteins during evolution. Analysis of the correlation between the evolutionary relationship of pairs of proteins in a class and the BLAST E-value revealed that: (i) the BLAST algorithm is unable to pick up the majority of the links between proteins in structural class ST[3], (ii) "low complexity filtering" and "composition based statistics" improve the specificity, but strongly reduce the sensitivity of BLAST searches for distantly related proteins, indicating that these filters are too stringent for the proteins analyzed, and (iii) the E-value cut-off, which may be used to evaluate evolutionary significance of a hit in a BLAST search is very different for the two structural classes of membrane proteins.     

Sequence and hydropathy profile analysis of two classes of secondary transporters

A structural class in the MemGen classification of membrane proteins is a set of evolutionary related proteins sharing a similar global fold. A structural class contains both closely related pairs of proteins for which homology is clear from sequence comparison and very distantly related pairs, for which it is not possible to establish homology based on sequence similarity alone. In the latter case the evolutionary link is based on hydropathy profile analysis. Here, we use these evolutionary related sets of proteins to analyze the relationship between E-values in BLAST searches, sequence similarities in multiple sequence alignments and structural similarities in hydropathy profile analyses. Two structural classes of secondary transporters termed ST[3], which includes the Ion Transporter (IT) superfamily and ST[4], which includes the DAACS family (TC# 2.A.23) were extracted from the NCBI protein database. ST[3] contains 2051 unique sequences distributed over 32 families and 59 subfamilies. ST[4] is a smaller class containing 399 unique sequences distributed over 2 families and 7 subfamilies. One subfamily in ST[4] contains a new class of binding protein dependent secondary transporters. Comparison of the averaged hydropathy profiles of the subfamilies in ST[3] and ST[4] revealed that the two classes represent different folds. Divergence of the sequences in ST[4] is much smaller than observed in ST[3], suggesting different constraints on the proteins during evolution. Analysis of the correlation between the evolutionary relationship of pairs of proteins in a class and the BLAST E-value revealed that: (i) the BLAST algorithm is unable to pick up the majority of the links between proteins in structural class ST[3], (ii) ‘low complexity filtering’ and ‘composition based statistics’ improve the specificity, but strongly reduce the sensitivity of BLAST searches for distantly related proteins, indicating that these filters are too stringent for the proteins analyzed, and (iii) the E-value cut-off, which may be used to evaluate evolutionary significance of a hit in a BLAST search is very different for the two structural classes of membrane proteins.     

Structural features of the glutamate transporter family.

Neuronal and glial glutamate transporters remove the excitatory neurotransmitter glutamate from the synaptic cleft and thus prevent neurotoxicity. The proteins belong to a large and widespread family of secondary transporters, including bacterial glutamate, serine, and C4-dicarboxylate transporters; mammalian neutral-amino-acid transporters; and an increasing number of bacterial, archaeal, and eukaryotic proteins that have not yet been functionally characterized. Sixty members of the glutamate transporter family were found in the databases on the basis of sequence homology. The amino acid sequences of the carriers have diverged enormously. Homology between the members of the family is most apparent in a stretch of approximately 150 residues in the C-terminal part of the proteins. This region contains four reasonably well-conserved sequence motifs, all of which have been suggested to be part of the translocation pore or substrate binding site. Phylogenetic analysis of the C-terminal stretch revealed the presence of five subfamilies with characterized members: (i) the eukaryotic glutamate transporters, (ii) the bacterial glutamate transporters, (iii) the eukaryotic neutral-amino-acid transporters, (iv) the bacterial C4-dicarboxylate transporters, and (v) the bacterial serine transporters. A number of other subfamilies that do not contain characterized members have been defined. In contrast to their amino acid sequences, the hydropathy profiles of the members of the family are extremely well conserved. Analysis of the hydropathy profiles has suggested that the glutamate transporters have a global structure that is unique among secondary transporters. Experimentally, the unique structure of the transporters was recently confirmed by membrane topology studies. Although there is still controversy about part of the topology, the most likely model predicts the presence of eight membrane-spanning alpha-helices and a loop-pore structure which is unique among secondary transporters but may resemble loop-pores found in ion channels. A second distinctive structural feature is the presence of a highly amphipathic membrane-spanning helix that provides a hydrophilic path through the membrane. Recent data from analysis of site-directed mutants and studies on the mechanism and pharmacology of the transporters are discussed in relation to the structural model.     

Structural Features of the Glutamate Transporter Family

Neuronal and glial glutamate transporters remove the excitatory neurotransmitter glutamate from the synaptic cleft and thus prevent neurotoxicity. The proteins belong to a large and widespread family of secondary transporters, including bacterial glutamate, serine, and C₄-dicarboxylate transporters; mammalian neutral-amino-acid transporters; and an increasing number of bacterial, archaeal, and eukaryotic proteins that have not yet been functionally characterized. Sixty members of the glutamate transporter family were found in the databases on the basis of sequence homology. The amino acid sequences of the carriers have diverged enormously. Homology between the members of the family is most apparent in a stretch of approximately 150 residues in the C-terminal part of the proteins. This region contains four reasonably well-conserved sequence motifs, all of which have been suggested to be part of the translocation pore or substrate binding site. Phylogenetic analysis of the C-terminal stretch revealed the presence of five subfamilies with characterized members: (i) the eukaryotic glutamate transporters, (ii) the bacterial glutamate transporters, (iii) the eukaryotic neutral-amino-acid transporters, (iv) the bacterial C₄-dicarboxylate transporters, and (v) the bacterial serine transporters. A number of other subfamilies that do not contain characterized members have been defined. In contrast to their amino acid sequences, the hydropathy profiles of the members of the family are extremely well conserved. Analysis of the hydropathy profiles has suggested that the glutamate transporters have a global structure that is unique among secondary transporters. Experimentally, the unique structure of the transporters was recently confirmed by membrane topology studies. Although there is still controversy about part of the topology, the most likely model predicts the presence of eight membrane-spanning α-helices and a loop-pore structure which is unique among secondary transporters but may resemble loop-pores found in ion channels. A second distinctive structural feature is the presence of a highly amphipathic membrane-spanning helix that provides a hydrophilic path through the membrane. Recent data from analysis of site-directed mutants and studies on the mechanism and pharmacology of the transporters are discussed in relation to the structural model.     

Identification of novel membrane proteins by searching for patterns in hydropathy profiles.

A technique has been developed to search a proteome database for new members of a functional class of membrane protein. It takes advantage of the highly conserved secondary structure of functionally related membrane proteins. Such proteins typically have the same number of transmembrane domains located at similar relative positions in their polypeptide sequence. This gives rise to a characteristic pattern of peaks in their hydropathy profiles. To conduct a search, each member of a polypeptide database is converted to a hydropathy profile, peaks are automatically detected, and the pattern of peaks is compared with a template. A template was designed for the acetylcholine (ACh) and glycine receptors of the cys-loop receptor superfamily. The key feature was a closely spaced triplet of hydropathy peaks bracketed by deep valleys. When applied to the human proteome the search procedure retrieved 153 profiles with a receptor-like triplet of peaks. The approach was highly selective with 70% of the retrieved profiles annotated as known or putative receptors. These included ACh, glycine, gamma-amino butyric acid and serotonin receptors, which are all related by sequence. However, ionotropic glutamate receptors, which have almost no sequence homology with ACh receptors, were also retrieved. Thus, the strategy can find members of a functional class that cannot be identified by sequence alignment. To demonstrate that the strategy can easily be extended to other membrane protein families, a template was developed for the neurotransmitter/Na+ symporter family, and similar results were obtained. This approach should prove a useful adjunct to sequence-based retrieval tools when searching for novel membrane proteins.     

A critical evaluation of the hydropathy profile of membrane proteins

New membrane-preference scales are introduced for categories of membrane proteins with different functions. A statistical analysis is carried out with several scales to verify the relative accuracy in the prediction of the transmembrane segments of polytopic membrane proteins. The correlation between some of the scales most used and those calculated here provides criteria for selecting the most appropriate methods for a given type of protein. The parameters used in the evaluation of the hydropathy profiles have been carefully ascertained in order to develop a reliable methodology for hydropathy analysis. Finally, an integrated hydropathy analysis using different methods has been applied to several sequences of related proteins. The above analysis indicates that (a) microsomal cytochrome P450 contains only one hydrophobic region at the N-terminus that is consistently predicted to transverse the membrane: (b) only four of the six or seven putative transmembrane helices of cytochrome oxidase subunit III are predicted and correspond to helices I, III, V and VI of the previous nomenclature; (c) the product of the mitochondrial ATPase-6 gene (or the chloroplast ATPase-IV gene) of F0-F1-ATPase shows that helix IV is not consistently predicted to traverse the membrane, suggesting a four-helix model for this family of proteins.     

Secondary transporters for citrate and the Mg(2+)-citrate complex in Bacillus subtilis are homologous proteins.

Citrate uptake in Bacillus subtilis is mediated by a secondary transporter that transports the complex of citrate and divalent metal ions. The gene coding for the transporter termed CitM was cloned, sequenced, and functionally expressed in Escherichia coli. Translation of the base sequence to the primary sequence revealed a transporter that is not homologous to any known secondary transporter. However, CitM shares 60% sequence identity with the gene product of open reading frame N15CR that is on the genome of B. subtilis and for which no function is known. The hydropathy profiles of the primary sequences of CitM and the unknown gene product are very similar, and secondary structure prediction algorithms predict 12 transmembrane-spanning segments for both proteins. Open reading frame N15CR was cloned and expressed in E. coli and was shown to be a citrate transporter as well. The transporter is termed CitH. A remarkable difference between the two transporters is that citrate uptake by CitM is stimulated by the presence of Mg2+ ions, while citrate uptake by CitH is inhibited by Mg2+. It is concluded that the substrate of CitM is the Mg(2+)-citrate complex and that CitH transports the free citrate anion. Uptake experiments in right-side-out membrane vesicles derived from E. coli cells expressing either CitM or CitH showed that both transporters catalyze electrogenic proton/substrate symport.     

Genetic algorithm-based optimization of hydrophobicity tables

SUMMARY: The genomic abundance and pharmacological importance of membrane proteins have fueled efforts to identify them based solely on sequence information. Previous methods based on the physicochemical principle of a sliding window of hydrophobicity (hydropathy analysis) have been replaced by approaches based on hidden Markov models or neural networks which prevail due to their probabilistic orientation. In the current study, an optimization of the hydrophobicity tables used in hydropathy analysis is performed using a genetic algorithm. As such, the approach can be viewed as a synthesis between the physicochemically and statistically based methods. The resulting hydrophobicity tables lead to significant improvement in the prediction accuracy of hydropathy analysis. Furthermore, since hydropathy analysis is less dependent on the basis set of membrane proteins is used to hone the statistically based methods, as well as being faster, it may be valuable in the analysis of new genomes. Finally, the values obtained for each of the amino acids in the new hydrophobicity tables are discussed.     

Sequence similarity as a predictor of the transmembrane topology of membrane-intrinsic subunits of bacterial respiratory chain enzymes

Integral membrane proteins usually have a predominantly alpha-helical secondary structure in which transmembrane segments are connected by membrane-extrinsic loops. Although a number of membrane protein structures have been reported in recent years, in most cases transmembrane topologies are initially predicted using a variety of theoretical techniques, including hydropathy analyses and the "positive inside" rule. We have explored the use of plots of the distribution of sequence similarity within families of membrane proteins comprising homeomorphic domains as a new method for the prediction/verification of the orientation of transmembrane topology models within certain families of multimeric respiratory chain enzymes. Within such proteins, analyses of sequence similarity can: i) identify heme and/or quinol binding sites; ii) identify potential electron-transfer conduits to/from prosthetic groups; and iii) locate regions defining potential subunit-subunit interactions. We mined emerging bioinformatic data for sequences of 11 families of membrane-intrinsic proteins that are part of multimeric respiratory chain complexes that also have membrane-extrinsic subunits. The sequences of each family were then aligned and the resultant alignments converted into a graphical format recording an empirical measure of the sequence similarity plotted versus residue position. In each case, this plot was compared to the predicted transmembrane topology. With one exception, there is a strong correlation between the existence     

Using auto covariance method for functional discrimination of membrane proteins based on evolution information

Membrane transporters are critical in living cells. Therefore, the discrimination of the types of membrane proteins based on their functions is of great importance both for helping genome annotation and providing a supplementary role to experimental researchers to gain insight into membrane proteins’ function. There are a lot of computational methods to facilitate the identification of the functional types of membrane proteins. However, in these methods, the local sequence environment was not integrated into the constructed model. In this study, we described a new strategy to predict the functional types of membrane proteins using a model based on auto covariance and position-specific scoring matrix. The novelty of the presented approach is considering the distribution of different positions of functional conservation sites in protein sequences. Thereby, this model adequately takes into account the long-range correlation between such sites during sequential evolution. Fivefold cross-validation test shows that this method greatly improves the prediction accuracy and achieves an acceptable prediction accuracy of 87.51%. The result indicates that the current approach might be an effective tool for predicting the functional types of membrane proteins only using the primary sequences. The code and dataset used in this article are freely available at .     

Identification of novel families of membrane proteins from the model plant Arabidopsis thaliana

MOTIVATION: The completion of the Arabidopsis genome offers the first opportunity to analyze all of the membrane protein sequences of a plant. The majority of integral membrane proteins including transporters, channels, and pumps contain hydrophobic alpha-helices and can be selected based on TransMembrane Spanning (TMS) domain prediction. By clustering the predicted membrane proteins based on sequence, it is possible to sort the membrane proteins into families of known function, based on experimental evidence or homology, or unknown function. This provides a way to identify target sequences for future functional analysis. RESULTS: An automated approach was used to select potential membrane protein sequences from the set of all predicted proteins and cluster the sequences into related families. The recently completed sequence of Arabidopsis thaliana, a model plant, was analyzed. Of the 25,470 predicted protein sequences 4589 (18%) were identified as containing two or more membrane spanning domains. The membrane protein sequences clustered into 628 distinct families containing 3208 sequences. Of these, 211 families (1764 sequences) either contained proteins of known function or showed homology to proteins of known function in other species. However, 417 families (1444 sequences) contained only sequences with no known function and no homology to proteins of known function. In addition, 1381 sequences did not cluster with any family and no function could be assigned to 1337 of these.     

Membrane topology screen of secondary transport proteins in structural class ST[3] of the MemGen classification. Confirmation and structural diversity

The MemGen structural classification of membrane proteins groups families of proteins by hydropathy profile alignment. Class ST[3] of the MemGen classification contains 32 families of transporter proteins including the IT superfamily. Transporters from 19 different families in class ST[3] were evaluated by the TopScreen experimental topology screening method to verify the structural classification by MemGen. TopScreen involves the determination of the cellular disposition of three sites in the polypeptide chain of the proteins which allows for discrimination between different topology models. For nearly all transporters at least one of the predicted localizations is different in the models produced by MemGen and predictor TMHMM. Comparison to the experimental data showed that in all cases the prediction by MemGen was correct. It is concluded that the structural model available for transporters of the [st324]ESS and [st326]2HCT families is also valid for the other families in class ST[3]. The core structure of the model consists of two homologous domains, each containing 5 transmembrane segments, which have an opposite orientation in the membrane. A reentrant loop is present in between the 4th and 5th segments in each domain. Nearly all of the identified and experimentally confirmed structural variations involve additions of transmembrane segments at the boundaries of the core model, at the N- and C-termini or in between the two domains. Most remarkable is a domain swap in two subfamilies of the [st312]NHAC family that results in an inverted orientation of the proteins in the membrane.     

A comparative computational analysis of protein sequences and literature mining classify 'orphan' neurotransmitter transporters

Various sources of protein data, such as knowledgebases and scientific literature, are currently available, as are numerous tools for their analysis. The matter becomes one of choosing the tools that are most appropriate for the specific task and for the specific proteins. A combination of standard and alternative tools may lead to biologically significant results.Here, a computational classification of proteins is made using standard multiple sequence alignment in combination with an alternative method for analysis of hydropathy distribution in proteins. Both of these methods are applied to the Na⁺/Cl⁻-dependent neurotransmitter symporters (NSSs), resulting in two alternative classifications. The classifications are validated and interpreted biologically by literature and knowledgebase annotation mining, producing a consensus classification. The classification leads to the identification and functional characterization of three families of largely structurally and functionally uncharacterized orphan NSSs. The literature and knowledgebase annotations are mined to functionally characterize the NSSs in these families. The presented work also demonstrates that, in specific cases, the analysis of the hydropathy distribution in proteins is capable of revealing functional properties of proteins.     

The LysE superfamily: topology of the lysine exporter LysE of Corynebacterium glutamicum, a paradyme for a novel superfamily of transmembrane solute translocators

In Corynebacterium glutamicum the LysE carrier protein exhibits the unique function of exporting L-lysine. We here analyze the membrane topology of LysE, a protein of 236 amino acyl residues, using PhoA- and LacZ-fusions. The amino-terminal end of LysE is located in the cytoplasm whereas the carboxy-terminal end is found in the periplasm. Although 6 hydrophobic domains were identified based on hydropathy analyses, only five transmembrane spanning helices appear to be present. The additional hydrophobic segment may dip into the membrane or be surface localized. We show that LysE is a member of a family of proteins found, for example, in Escherichia coil, Bacillus subtilis, Mycobacterium tuberculosis and Helicobacter pylori. This family, which we have designated the LysE family, is distantly related to two additional protein families which we have designated the YahN and CadD families. These three families, the members of which exhibit similar sizes, hydropathy profiles, and sequence motifs comprise the LysE superfamily. Functionally characterized members of the LysE superfamily export L-lysine, cadmium and possibly quarternary amines. We suggest that LysE superfamily members will prove to catalyze export of a variety of biologically important solutes.     

The major amino acid transporter superfamily has a similar core structure as Na+-galactose and Na+-leucine transporters

The sodium solute symporters (SSS) and neurotransmitter sodium symporters (NSS) are two families of secondary transporters that are not related in amino acid sequence. Nonetheless, recent crystal structures showed that the Na⁺/galactose (SSS) and Na⁺/leucine (NSS) transporters have similar core structures. The structural relatedness highlights the need for classification methods for membrane protein structures based on other criteria than amino acid similarity. Here, we demonstrate that a method based on hydropathy profile alignments convincingly identifies structural similarity between the NSS and SSS families. Most importantly, the method shows that one of the largest transporter families for which a crystal structure is elusive (the amino acid/polyamine/organocation or APC superfamily), also shares the similar core structure observed for the Na⁺/galactose and Na⁺/leucine transporters. The APC superfamily contains the major amino acid transporter families that are found throughout life. Insight into their structure will significantly facilitate the studies of this important group of transporters.     

Domain structure and pore loops in the 2-hydroxycarboxylate transporter family

The 2-hydroxycarboxylate transporter (2HCT) family is a family of bacterial secondary transporters for substrates like citrate, malate and lactate. The family is in class ST[3] of the MemGen classification system that groups membrane proteins in structural classes based on hydropathy profile analysis. The combination of computational analysis of the proteins in class ST[3] and available experimental data on members of the 2HCT family has yielded a detailed structural model of the transporters. The core of the model is formed by two homologous domains with opposite orientation in the membrane. Each domain consists of 5 trans membrane segments and contains a pore loop between the 4th and 5th segment. The two pore loops enter the membrane-embedded part from opposite sides of the membrane (trans pore loops) and are believed to form the translocation pathway in the 3D structure. A genome wide study of the cellular location of the C-terminus of all Escherichia coli membrane proteins [Daley et al., 2005. Science 308:1321-1323] showed that the C-termini of the 19 E. coli proteins in class ST[3] were correctly predicted by the structural model.