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.     

The use of functional domains to improve transmembrane protein topology prediction

Transmembrane proteins affect vital cellular functions and pathogenesis, and are a focus of drug design. It is difficult to obtain diffraction quality crystals to study transmembrane protein structure. Computational tools for transmembrane protein topology prediction fill in the gap between the abundance of transmembrane proteins and the scarcity of known membrane protein structures. Their prediction accuracy is still inadequate: TMHMM, the current state-of-the-art method, has less than 52% accuracy in topology prediction on one set of transmembrane proteins of known topology. Based on the observation that there are functional domains that occur preferentially internal or external to the membrane, we have extended the model of TMHMM to incorporate functional domains, using a probabilistic approach originally developed for computational gene finding. Our extension is better than TMHMM in predicting the topology of transmembrane proteins. As prediction of functional domain improves, our system's prediction accuracy will likely improve as well.     

Reliability measures for membrane protein topology prediction algorithms

We have developed reliability scores for five widely used membrane protein topology prediction methods, and have applied them both on a test set of 92 bacterial plasma membrane proteins with experimentally determined topologies and on all predicted helix bundle membrane proteins in three fully sequenced genomes: Escherichia coli, Saccharomyces cerevisiae and Caenorhabditis elegans. We show that the reliability scores work well for the TMHMM and MEMSAT methods, and that they allow the probability that the predicted topology is correct to be estimated for any protein. We further show that the available test set is biased towards high-scoring proteins when compared to the genome-wide data sets, and provide estimates for the expected prediction accuracy of TMHMM across the three genomes. Finally, we show that the performance of TMHMM is considerably better when limited experimental information (such as the in/out location of a protein's C terminus) is available, and estimate that at least ten percentage points in overall accuracy in whole-genome predictions can be gained in this way.     

Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes

We describe and validate a new membrane protein topology prediction method, TMHMM, based on a hidden Markov model. We present a detailed analysis of TMHMM's performance, and show that it correctly predicts 97-98 % of the transmembrane helices. Additionally, TMHMM can discriminate between soluble and membrane proteins with both specificity and sensitivity better than 99 %, although the accuracy drops when signal peptides are present. This high degree of accuracy allowed us to predict reliably integral membrane proteins in a large collection of genomes. Based on these predictions, we estimate that 20-30 % of all genes in most genomes encode membrane proteins, which is in agreement with previous estimates. We further discovered that proteins with N(in)-C(in) topologies are strongly preferred in all examined organisms, except Caenorhabditis elegans, where the large number of 7TM receptors increases the counts for N(out)-C(in) topologies. We discuss the possible relevance of this finding for our understanding of membrane protein assembly mechanisms. A TMHMM prediction service is available at http://www.cbs.dtu.dk/services/TMHMM/.     

An improved hidden Markov model for transmembrane protein detection and topology prediction and its applications to complete genomes

MOTIVATION: Knowledge of the transmembrane helical topology can help identify binding sites and infer functions for membrane proteins. However, because membrane proteins are hard to solubilize and purify, only a very small amount of membrane proteins have structure and topology experimentally determined. This has motivated various computational methods for predicting the topology of membrane proteins. RESULTS: We present an improved hidden Markov model, TMMOD, for the identification and topology prediction of transmembrane proteins. Our model uses TMHMM as a prototype, but differs from TMHMM by the architecture of the submodels for loops on both sides of the membrane and also by the model training procedure. In cross-validation experiments using a set of 83 transmembrane proteins with known topology, TMMOD outperformed TMHMM and other existing methods, with an accuracy of 89% for both topology and locations. In another experiment using a separate set of 160 transmembrane proteins, TMMOD had 84% for topology and 89% for locations. When utilized for identifying transmembrane proteins from non-transmembrane proteins, particularly signal peptides, TMMOD has consistently fewer false positives than TMHMM does. Application of TMMOD to a collection of complete genomes shows that the number of predicted membrane proteins accounts for approximately 20-30% of all genes in those genomes, and that the topology where both the N- and C-termini are in the cytoplasm is dominant in these organisms except for Caenorhabditis elegans. AVAILABILITY: http://liao.cis.udel.edu/website/servers/TMMOD/     

Transmembrane Nox4 topology revealed by topological determination by Ubiquitin Fusion Assay,a novel method to uncover membrane protein topology

The NADPH oxidase Nox4 is a multi-pass membrane protein responsible for the generation of reactive oxygen species that are implicated in cellular signaling but may also cause pathological situations when dysregulated. Although topological organization of integral membrane protein dictates its function, only limited experimental data describing Nox4's topology are available.To provide deeper insight on Nox4 structural organization, we developed a novel method to determinate membrane protein topology in their cellular environment, named Topological Determination by Ubiquitin Fusion Assay (ToDUFA). It is based on the proteolytic capacity of the deubiquitinase enzymes to process ubiquitin fusion proteins. This straightforward method, validated on two well-known protein's topologies (IL1RI and Nox2), allowed us to discriminate rapidly the topological orientation of protein's domains facing either the nucleocytosolic or the exterior/luminal compartments. Using this method, we were able for the first time to determine experimentally the topology of Nox4 which consists of 6 transmembrane domains with its N- and C-terminus moieties facing the cytosol. While the first, third and fifth loops of Nox4 protein are extracellular; the second and fourth loops are located in the cytosolic side. This approach can be easily extended to characterize the topology of all others members of the NADPH oxidase family or any multi-pass membrane proteins.Considering the importance of protein topology knowledge in cell biology research and pharmacological development, we believe that this novel method will represent a widely useful technique to easily uncover complex membrane protein's topology.     

Transmembrane topology of the Acr3 family arsenite transporter from Bacillus subtilis

The transmembrane topology of the Acr3 family arsenite transporter Acr3 from Bacillus subtilis was analysed experimentally using translational fusions with alkaline phosphatase and green fluorescent protein and in silico by topology modelling. Initial topology prediction resulted in two models with 9 and 10 TM helices respectively. 32 fusion constructs were made between truncated forms of acr3 and the reporter genes at 17 different sites throughout the acr3 sequence to discriminate between these models. Nine strong reporter protein signals provided information about the majority of the locations of the cytoplasmic and extracellular loops of Acr3 and showed that both the N- and the C-termini are located in the cytoplasm. Two ambiguous data points indicated the possibility of an alternative 8 helix topology. This possibility was investigated using another 10 fusion variants, but no experimental support for the 8 TM topology was obtained. We therefore conclude that Acr3 has 10 transmembrane helices. Overall, the loops which connect the membrane spanning segments are short, with cytoplasmic loops being somewhat longer than the extracellular loops. The study provides the first ever experimentally derived structural information on a protein of the Acr3 family which constitutes one of the largest classes of arsenite transporters.     

A combined transmembrane topology and signal peptide prediction method

An inherent problem in transmembrane protein topology prediction and signal peptide prediction is the high similarity between the hydrophobic regions of a transmembrane helix and that of a signal peptide, leading to cross-reaction between the two types of predictions. To improve predictions further, it is therefore important to make a predictor that aims to discriminate between the two classes. In addition, topology information can be gained when successfully predicting a signal peptide leading a transmembrane protein since it dictates that the N terminus of the mature protein must be on the non-cytoplasmic side of the membrane. Here, we present Phobius, a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states. Training was done on a newly assembled and curated dataset. Compared to TMHMM and SignalP, errors coming from cross-prediction between transmembrane segments and signal peptides were reduced substantially by Phobius. False classifications of signal peptides were reduced from 26.1% to 3.9% and false classifications of transmembrane helices were reduced from 19.0% to 7.7%. Phobius was applied to the proteomes of Homo sapiens and Escherichia coli. Here we also noted a drastic reduction of false classifications compared to TMHMM/SignalP, suggesting that Phobius is well suited for whole-genome annotation of signal peptides and transmembrane regions. The method is available at as well as at     

Viral Membrane Protein Topology Is Dictated by Multiple Determinants in Its Sequence

The targeting, insertion, and topology of membrane proteins have been extensively studied in both prokaryotes and eukaryotes. However, the mechanisms used by viral membrane proteins to generate the correct topology within cellular membranes are less well understood. Here, the effect of flanking charges and the hydrophobicity of the N-terminal hydrophobic segment on viral membrane protein topogenesis are examined systematically. Experimental data reveal that the classical topological determinants have only a minor effect on the overall topology of p9, a plant viral movement protein. Since only a few individual sequence alterations cause an inversion of p9 topology, its topological stability is robust. This result further indicates that the protein has multiple, and perhaps redundant, structural features that ensure that it always adopts the same topology. These critical topogenic sequences appear to be recognized and acted upon from the initial stages of protein biosynthesis, even before the ribosome ends protein translation.     

Improved membrane protein topology prediction by domain assignments

Topology predictions for integral membrane proteins can be substantially improved if parts of the protein can be constrained to a given in/out location relative to the membrane using experimental data or other information. Here, we have identified a set of 367 domains in the SMART database that, when found in soluble proteins, have compartment-specific localization of a kind relevant for membrane protein topology prediction. Using these domains as prediction constraints, we are able to provide high-quality topology models for 11% of the membrane proteins extracted from 38 eukaryotic genomes. Two-thirds of these proteins are single spanning, a group of proteins for which current topology prediction methods perform particularly poorly.     

Probing possible downhill folding: native contact topology likely places a significant constraint on the folding cooperativity of proteins with approximately 40 residues

Experiments point to appreciable variations in folding cooperativity among natural proteins with approximately 40 residues, indicating that the behaviors of these proteins are valuable for delineating the contributing factors to cooperative folding. To explore the role of native topology in a protein's propensity to fold cooperatively and how native topology might constrain the degree of cooperativity achievable by a given set of physical interactions, we compared folding/unfolding kinetics simulated using three classes of native-centric C^α chain models with different interaction schemes. The approach was applied to two homologous 45-residue fragments from the peripheral subunit-binding domain family and a 39-residue fragment of the N-terminal domain of ribosomal protein L9. Free-energy profiles as functions of native contact number were computed to assess the heights of thermodynamic barriers to folding. In addition, chevron plots of folding/unfolding rates were constructed as functions of native stability to facilitate comparison with available experimental data. Although common Gō-like models with pairwise Lennard-Jones-type interactions generally fold less cooperatively than real proteins, the rank ordering of cooperativity predicted by these models is consistent with experiment for the proteins investigated, showing increasing folding cooperativity with increasing nonlocality of a protein's native contacts. Models that account for water-expulsion (desolvation) barriers and models with many-body (nonadditive) interactions generally entail higher degrees of folding cooperativity indicated by more linear model chevron plots, but the rank ordering of cooperativity remains unchanged. A robust, experimentally valid rank ordering of model folding cooperativity independent of the multiple native-centric interaction schemes tested here argues that native topology places significant constraints on how cooperatively a protein can fold.     

Membrane topology of transmembrane proteins: determinants and experimental tools

Membrane topology refers to the two-dimensional structural information of a membrane protein that indicates the number of transmembrane (TM) segments and the orientation of soluble domains relative to the plane of the membrane. Since membrane proteins are co-translationally translocated across and inserted into the membrane, the TM segments orient themselves properly in an early stage of membrane protein biogenesis. Each membrane protein must contain some topogenic signals, but the translocation components and the membrane environment also influence the membrane topology of proteins. We discuss the factors that affect membrane protein orientation and have listed available experimental tools that can be used in determining membrane protein topology.     

Membrane insertion and topology of the translocating chain-associating membrane protein (TRAM)

The translocating chain-associating membrane protein (TRAM) is a glycoprotein involved in the translocation of secreted proteins into the endoplasmic reticulum (ER) lumen and in the insertion of integral membrane proteins into the lipid bilayer. As a major step toward elucidating the structure of the functional ER translocation/insertion machinery, we have characterized the membrane integration mechanism and the transmembrane topology of TRAM using two approaches: photocross-linking and truncated C-terminal reporter tag fusions. Our data indicate that TRAM is recognized by the signal recognition particle and translocon components, and suggest a membrane topology with eight transmembrane segments, including several poorly hydrophobic segments. Furthermore, we studied the membrane insertion capacity of these poorly hydrophobic segments into the ER membrane by themselves. Finally, we confirmed the main features of the proposed membrane topology in mammalian cells expressing full-length TRAM.     

Transmembrane topology of the Acr3 family arsenite transporter from Bacillus subtilis

The transmembrane topology of the Acr3 family arsenite transporter Acr3 from Bacillus subtilis was analysed experimentally using translational fusions with alkaline phosphatase and green fluorescent protein and in silico by topology modelling. Initial topology prediction resulted in two models with 9 and 10 TM helices respectively. 32 fusion constructs were made between truncated forms of acr3 and the reporter genes at 17 different sites throughout the acr3 sequence to discriminate between these models. Nine strong reporter protein signals provided information about the majority of the locations of the cytoplasmic and extracellular loops of Acr3 and showed that both the N- and the C-termini are located in the cytoplasm. Two ambiguous data points indicated the possibility of an alternative 8 helix topology. This possibility was investigated using another 10 fusion variants, but no experimental support for the 8 TM topology was obtained. We therefore conclude that Acr3 has 10 transmembrane helices. Overall, the loops which connect the membrane spanning segments are short, with cytoplasmic loops being somewhat longer than the extracellular loops. The study provides the first ever experimentally derived structural information on a protein of the Acr3 family which constitutes one of the largest classes of arsenite transporters.     

Evaluation of methods for the prediction of membrane spanning regions.

MOTIVATION: A variety of tools are available to predict the topology of transmembrane proteins. To date no independent evaluation of the performance of these tools has been published. A better understanding of the strengths and weaknesses of the different tools would guide both the biologist and the bioinformatician to make better predictions of membrane protein topology. RESULTS: Here we present an evaluation of the performance of the currently best known and most widely used methods for the prediction of transmembrane regions in proteins. Our results show that TMHMM is currently the best performing transmembrane prediction program.     

膜蛋白的拓扑学

膜蛋白的拓扑学是研究膜蛋白三维结构的出发点．利用融合蛋白和化学修饰等实验技术已确定了很多膜蛋白的拓扑学．对膜蛋白的转运与插膜的研究确定可能存在两类插膜元件．对已知拓扑学的膜蛋白的统计分析以及蛋白质工程的研究表明存在膜蛋白拓扑学的内正规则．目前已形成预测膜蛋白的拓扑学的比较可靠的策略,这在反向生物学上具有重要意义.但要进行三维结构的预测还有许多路要走．     

Prediction of partial membrane protein topologies using a consensus approach

We have developed a method to reliably identify partial membrane protein topologies using the consensus of five topology prediction methods. When evaluated on a test set of experimentally characterized proteins, we find that approximately 90% of the partial consensus topologies are correctly predicted in membrane proteins from prokaryotic as well as eukaryotic organisms. Whole-genome analysis reveals that a reliable partial consensus topology can be predicted for approximately 70% of all membrane proteins in a typical bacterial genome and for approximately 55% of all membrane proteins in a typical eukaryotic genome. The average fraction of sequence length covered by a partial consensus topology is 44% for the prokaryotic proteins and 17% for the eukaryotic proteins in our test set, and similar numbers are found when the algorithm is applied to whole genomes. Reliably predicted partial topologies may simplify experimental determinations of membrane protein topology.     

Prediction of the transmembrane regions of beta-barrel membrane proteins with a neural network-based predictor

A method based on neural networks is trained and tested on a nonredundant set of beta-barrel membrane proteins known at atomic resolution with a jackknife procedure. The method predicts the topography of transmembrane beta strands with residue accuracy as high as 78% when evolutionary information is used as input to the network. Of the transmembrane beta-strands included in the training set, 93% are correctly assigned. The predictor includes an algorithm of model optimization, based on dynamic programming, that correctly models eight out of the 11 proteins present in the training/testing set. In addition, protein topology is assigned on the basis of the location of the longest loops in the models. We propose this as a general method to fill the gap of the prediction of beta-barrel membrane proteins.     

High-throughput analysis of rat liver plasma membrane proteome by a nonelectrophoretic in-gel tryptic digestion coupled with mass spectrometry identification

In-gel digestion is commonly used after proteins are resolved by polyacrylamide gel electrophoresis (SDS-PAGE, 2-DE). It can also be used on its own in conjunction with tandem mass spectrometry (MS/MS) for the direct analysis of complex proteins. Here, we describe a strategy combining isolation of purified plasma membrane, efficient digestion of plasma membrane proteins in polyacrylamide gel, and high-sensitivity analysis by advanced mass spectrometry to create a new rapid and high-throughput method. The plasma membrane protein mixture is directly incorporated into a polyacrylamide gel matrix, After formation of the gel, proteins in the gel section are digested with trypsin, and the resulting peptides are subjected to reversed-phase, high-performance liquid chromatography followed by electrospray ion-trap tandem mass analysis. Using this optimized strategy, we have identified 883 rat liver membrane proteins, of which 490 had a gene ontology (GO) annotation indicating a cellular component, and 294 (60%) of the latter were known integral membrane proteins or membrane proteins. In total, 333 proteins are predicted by the TMHMM 2.0 algorithm to have transmembrane domains (TMDs) and 52% (175 of 333) proteins to contain 2-16 TMDs. The identified membrane proteins provide a broad representation of the rat plasma membrane proteome with little bias evident due to protein p I and molecular weight (MW). Also, membrane proteins with a high GRAVY score (grand average hydrophobicity score) were identified, and basic and acidic membrane proteins were evenly represented. This study not only offered an efficient and powerful method in shotgun proteomics for the identification of proteins of complex plasma membrane samples but also allowed in-depth study of liver membrane proteomes, such as of rat models of liver-related disease. This work represents one of the most comprehensive proteomic analyses of the membrane subproteome of rat liver plasma membrane in general.     

Experimentally based topology models for E. coli inner membrane proteins

Membrane protein topology predictions can be markedly improved by the inclusion of even very limited experimental information. We have recently introduced an approach for the production of reliable topology models based on a combination of experimental determination of the location (cytoplasmic or periplasmic) of a protein's C terminus and topology prediction. Here, we show that determination of the location of a protein's C terminus, rather than some internal loop, is the best strategy for large-scale topology mapping studies. We further report experimentally based topology models for 31 Escherichia coli inner membrane proteins, using methodology suitable for genome-scale studies.