Snorkeling preferences foster an amino acid composition bias in transmembrane helices

By analyzing transmembrane (TM) helices in known structures, we find that some polar amino acids are more frequent at the N terminus than at the C terminus. We propose the asymmetry occurs because most polar amino acids are better able to snorkel their polar atoms away from the membrane core at the N terminus than at the C terminus. Two findings lead us to this proposition: (1) side-chain conformations are influenced strongly by the N or C-terminal position of the amino acid in the bilayer, and (2) the favored snorkeling direction of an amino acid correlates well with its N to C-terminal composition bias. Our results suggest that TM helix predictions should incorporate an N to C-terminal composition bias, that rotamer preferences of TM side-chains are position-dependent, and that the ability to snorkel influences the evolutionary selection of amino acids for the helix N and C termini.     

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.     

Proline-induced distortions of transmembrane helices

Proline residues in the transmembrane (TM) alpha-helices of integral membrane proteins have long been suspected to play a key role for helix packing and signal transduction by inducing regions of helix distortion and/or dynamic flexibility (hinges). In this study we try to characterise the effect of proline on the geometric properties of TM alpha-helices. We have examined 199 transmembrane alpha-helices from polytopic membrane proteins of known structure. After examining the location of proline residues within the amino acid sequences of TM helices, we estimated the helix axes either side of a hinge and hence identified a hinge residue. This enabled us to calculate helix kink and swivel angles. The results of this analysis show that proline residues occur with a significant concentration in the centre of sequences of TM alpha-helices. In this location, they may induce formation of molecular hinges, located on average about four residues N-terminal to the proline residue. A superposition of proline-containing TM helices structures shows that the distortion induced is anisotropic and favours certain relative orientations (defined by helix kink and swivel angles) of the two helix segments.     

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.     

Motifs of serine and threonine can drive association of transmembrane helices

Known sequence motifs containing key glycine residues can drive the homo-oligomerization of transmembrane helices. To find other motifs, a randomized library of transmembrane interfaces was generated in which glycine was omitted. The TOXCAT system, which measures transmembrane helix association in the Escherichia coli inner membrane, was used to select high-affinity homo-oligomerizing sequences in this library. The two most frequently occurring motifs were SxxSSxxT and SxxxSSxxT. Isosteric mutations of any one of the serine and threonine residues to non-polar residues abolished oligomerization, indicating that the interaction between these positions is specific and requires an extended motif of serine and threonine hydroxyl groups. Computational modeling of these sequences produced several chemically plausible structures that contain multiple hydrogen bonds between the serine and threonine residues. While single serine or threonine side-chains do not appear to promote helix association, motifs can drive strong and specific association through a cooperative network of interhelical hydrogen bonds.     

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.     

Energetics, stability, and prediction of transmembrane helices

We show that the peptide backbone of an alpha-helix places a severe thermodynamic constraint on transmembrane (TM) stability. Neglect of this constraint by commonly used hydrophobicity scales underlies the notorious uncertainty of TM helix prediction by sliding-window hydropathy plots of membrane protein (MP) amino acid sequences. We find that an experiment-based whole-residue hydropathy scale (WW scale), which includes the backbone constraint, identifies TM helices of membrane proteins with an accuracy greater than 99 %. Furthermore, it correctly predicts the minimum hydrophobicity required for stable single-helix TM insertion observed in Escherichia coli. In order to improve membrane protein topology prediction further, we introduce the augmented WW (aWW) scale, which accounts for the energetics of salt-bridge formation. An important issue for genomic analysis is the ability of the hydropathy plot method to distinguish membrane from soluble proteins. We find that the method falsely predicts 17 to 43 % of a set of soluble proteins to be MPs, depending upon the hydropathy scale used.     

Asymmetric amino acid compositions of transmembrane beta-strands

In contrast to water-soluble proteins, membrane proteins reside in a heterogeneous environment, and their surfaces must interact with both polar and apolar membrane regions. As a consequence, the composition of membrane proteins' residues varies substantially between the membrane core and the interfacial regions. The amino acid compositions of helical membrane proteins are also known to be different on the cytoplasmic and extracellular sides of the membrane. Here we report that in the 16 transmembrane beta-barrel structures, the amino acid compositions of lipid-facing residues are different near the N and C termini of the individual strands. Polar amino acids are more prevalent near the C termini than near the N termini, and hydrophobic amino acids show the opposite trend. We suggest that this difference arises because it is easier for polar atoms to escape from the apolar regions of the bilayer at the C terminus of a beta-strand. This new characteristic of beta-barrel membrane proteins enhances our understanding of how a sequence encodes a membrane protein structure and should prove useful in identifying and predicting the structures of trans-membrane beta-barrels.     

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.     

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.     

Influence of assignment on the prediction of transmembrane helices in protein structures

α-Helical transmembrane proteins (TMP_α) are composed of a series of helices embedded in the lipid bilayer. Due to technical difficulties, few 3D structures are available. Therefore, the design of structural models of TMP_α is of major interest. We study the secondary structures of TMP_α by analyzing the influence of secondary structures assignment methods (SSAMs). For this purpose, a published and updated benchmark databank of TMP_α is used and several SSAMs (9) are evaluated. The analysis of the results points to significant differences in SSA depending on the methods used. Pairwise comparisons between SSAMs led to more than 10% of disagreement. Helical regions corresponding to transmembrane zones are often correctly characterized. The study of the sequence–structure relationship shows very limited differences with regard to the structural disagreement. Secondary structure prediction based on Bayes’ rule and using only a single sequence give correct prediction rates ranging from 78 to 81%. A structural alphabet approach gives a slightly better prediction, i.e., only 2% less than the best equivalent approach, whereas the prediction rate with a very different assignment bypasses 86%. This last result highlights the importance of the correct assignment choice to evaluate the prediction assessment.     

Mutagenesis data in the automated prediction of transmembrane helix dimers

We present a molecular modeling protocol that selects modeled protein structures based on experimental mutagenesis results. The computed effect of a point mutation should be consistent with its experimental effect for correct models; mutations that do not affect protein stability and function should not affect the computed energy of a correct model while destabilizing mutations should have unfavorable computed energies. On the other hand, an incorrect model will likely display computed energies that are inconsistent with experimental results. We added terms to our energy function which penalize models that are inconsistent with experimental results. This creates a selective advantage for models that are consistent with experimental results in the Monte Carlo simulated annealing protocol we use to search conformational space. We calibrated our protocol to predict the structure of transmembrane helix dimers using glycophorin A as a model system. Inclusion of mutational data in this protocol compensates for the limitations of our force field and the limitations of our conformational search. We demonstrate an application of this structure prediction protocol by modeling the transmembrane region of the BNIP3 apoptosis factor.     

Marginally hydrophobic transmembrane α‐helices shaping membrane protein folding

Cells have developed an incredible machinery to facilitate the insertion of membrane proteins into the membrane. While we have a fairly good understanding of the mechanism and determinants of membrane integration, more data is needed to understand the insertion of membrane proteins with more complex insertion and folding pathways. This review will focus on marginally hydrophobic transmembrane helices and their influence on membrane protein folding. These weakly hydrophobic transmembrane segments are by themselves not recognized by the translocon and therefore rely on local sequence context for membrane integration. How can such segments reside within the membrane? We will discuss this in the light of features found in the protein itself as well as the environment it resides in. Several characteristics in proteins have been described to influence the insertion of marginally hydrophobic helices. Additionally, the influence of biological membranes is significant. To begin with, the actual cost for having polar groups within the membrane may not be as high as expected; the presence of proteins in the membrane as well as characteristics of some amino acids may enable a transmembrane helix to harbor a charged residue. The lipid environment has also been shown to directly influence the topology as well as membrane boundaries of transmembrane helices—implying a dynamic relationship between membrane proteins and their environment.     

The role of proline residues in the dynamics of transmembrane helices: the case of bacteriorhodopsin

Proline residues in transmembrane helices have been found to have important roles in the functioning of membrane proteins. Moreover, Pro residues occur with high frequency in transmembrane α-helices, as compared to α-helices for soluble proteins. Here, we report several properties of the bacteriorhodopsin mutants P50A (helix B), P91A (helix C) and P186A (helix F). Compared to wild type, strongly perturbed behaviour has been found for these mutants. In the resting state, increased hydroxylamine accessibility and altered Asp-85 pK_a and light-dark adaptation were observed. On light activation, hydroxylamine accessibility was increased and proton transport activity, M formation kinetics and FTIR difference spectra of M and N intermediates showed clear distortions. On the basis of these alterations and the near identity of the crystalline structures of mutants with that of wild type, we conclude that the transmembrane proline residues of bacteriorhodopsin fulfil a dynamic role in both the resting and the light-activated states. Our results are consistent with the notion that mutation of Pro to Ala allows the helix to increase its flexibility towards the direction originally hindered by the steric clash between the ring Cγ and the carbonyl O of the i-4 residue, at the same time decreasing the mobility towards the opposite direction. Due to their properties, transmembrane Pro residues may serve as transmission elements of conformational changes during the transport process. We propose that these concepts can be extended to other transmembrane proteins.     

The activation energy for insertion of transmembrane alpha-helices is dependent on membrane composition

The physical mechanisms that govern the folding and assembly of integral membrane proteins are poorly understood. It appears that certain properties of the lipid bilayer affect membrane protein folding in vitro, either by modulating helix insertion or packing. In order to begin to understand the origin of this effect, we investigate the effect of lipid forces on the insertion of a transmembrane alpha-helix using a water-soluble, alanine-based peptide, KKAAAIAAAAAIAAWAAIAAAKKKK-amide. This peptide binds to preformed 1,2-dioleoyl-l-alpha-phosphatidylcholine (DOPC) vesicles at neutral pH, but spontaneous transmembrane helix insertion directly from the aqueous phase only occurs at high pH when the Lys residues are de-protonated. These results suggest that the translocation of charge is a major determinant of the activation energy for insertion. Time-resolved measurements of the insertion process at high pH indicate biphasic kinetics with time constants of ca 30 and 430 seconds. The slower phase seems to correlate with formation of a predominantly transmembrane alpha-helical conformation, as determined from the transfer of the tryptophan residue to the hydrocarbon region of the membrane. Temperature-dependent measurements showed that insertion can proceed only above a certain threshold temperature and that the Arrhenius activation energy is of the order of 90 kJ mol(-1). The kinetics, threshold temperature and the activation energy change with the mole fraction of 1,2-dioleoyl-l-alpha-phosphatidylethanolamine (DOPE) introduced into the DOPC membrane. The activation energy increases with increasing DOPE content, which could reflect the fact that this lipid drives the bilayer towards a non-bilayer transition and increases the lateral pressure in the lipid chain region. This suggests that folding events involving the insertion of helical segments across the bilayer can be controlled by lipid forces.     

The study of neighboring nucleotide composition and transition/transversion bias

Base substitution, the most common mutation thatone or more bases substitute another, is the main causethat creates individual variation, community diversityand the evolution of species. Studying the role andmechanism of base substitution could help peopl…     

The study of neighboring nucleotide composition and transition/transversion bias

Base substitution is one of the raw fuels that produce genetic variation and drive evolution. Recent studies have shown that the genome components affect mutation patterns to some extent. In order to infer the correlation between the Transition/Transversion ratio (Ts/Tv) and the number of immediately adjacent A&T nucleotides, we investigated 3611007 Oryza sativa SNPs (including 45462 coding SNPs, and 242811 intronic SNPs) and 32019 Arabidopsis SNPs. The results show that Ts/Tv is negatively correlated with the number of immediately adjacent A&T in O. Sativa and Arabidopsis. We further calculated AT₂ (the number of SNPs whose immediately adjacent nucleotides are either A or T) and AT₀ (the number of SNPs whose immediately adjacent nucleotides are either C or G) for all 6 types of SNPs. C/G SNP of O. sativa and Arabidopsis has the highest AT₂/AT₀, which denotes C/G SNP may be influenced by the adjacent A&T nucleotides mostly. For SNPs in O. sativa, the neighboring effect of A&T nucleotides is limited to 2 nucleotides on both sides; for SNPs in Arabidopsis, the effect extends no more than 4 nucleotides on both sides.     

The rigid connecting loop stabilizes hairpin folding of the two helices of the ATP synthase subunit c

We have tested the role of the polar loop of subunit c of the Escherichia coli ATP synthase in stabilizing the hairpin structure of this protein. The structure of the c(32-52) peptide corresponding to the cytoplasmic region of subunit c bound to the dodecylphosphocholine micelles was solved by high-resolution NMR. The region comprising residues 41-47 forms a well-ordered structure rather similar to the conformation of the polar loop region in the solution structure of the full-length subunit c and is flanked by short alpha-helical segments. This result suggests that the rigidity of the polar loop significantly contributes to the stability of the hairpin formed by the two helices of subunit c. This experimental system may be useful for NMR studies of interactions between subunit c and subunits gamma and epsilon, which together form the rotor of the ATP synthase.     

Unambiguous prediction of human integrin transmembrane heterodimer interactions using only homologous sequences

Part of the interaction between the alpha- and beta-subunits of integrins is known to take place at the transmembrane (TM) domain, where both heteromeric and homomeric aggregates have been reported in vivo and in vitro. In a recent computational study, totally independent from biochemical or biophysical data, we explored the plausibility of various TM homo-oligomers using evolutionary conservation data as a filter for non-native interactions. We showed that several homodimeric and homotrimeric interactions for alpha- and beta-chains are evolutionarily conserved. We report herein the results of the application of the same exhaustive approach to the integrin heterodimer. We have studied all known human TM integrin alphabeta pairs, and we show unambiguously that two models of interaction are evolutionarily conserved. These two models are consistent with those proposed previously based on mutagenesis and crosslinking. Comparison with previous experimental data strongly supports that a glycophorin A-like model is an intermediate form of interaction between the resting state and the active form, where chain separation occurs. Surprisingly, these two models are also conserved when considering most of the possible alphabeta pair combinations, suggesting that specific pairing of integrins is not determined by the TM domain, which has remained unchanged in spite of the variety of known integrin functions. This fact highlights a common ancestral mechanism for signal transduction that has remained through evolution. In a broader context, our results show that it is possible to obtain correct and detailed interactions of alpha-helical heterodimers with total independence of experimental data.     

Comprehensive analysis of the numbers,lengths and amino acid compositions of transmembrane helices in prokaryotic,eukaryotic and viral integral membrane proteins of high-resolution structure

We report a comprehensive analysis of the numbers, lengths and amino acid compositions of transmembrane helices in 235 high-resolution structures of integral membrane proteins. The properties of 1551 transmembrane helices in the structures were compared with those obtained by analysis of the same amino acid sequences using topology prediction tools. Explanations for the 81 (5.2%) missing or additional transmembrane helices in the prediction results were identified. Main reasons for missing transmembrane helices were mis-identification of N-terminal signal peptides, breaks in α-helix conformation or charged residues in the middle of transmembrane helices and transmembrane helices with unusual amino acid composition. The main reason for additional transmembrane helices was mis-identification of amphipathic helices, extramembrane helices or hairpin re-entrant loops. Transmembrane helix length had an overall median of 24 residues and an average of 24.9 ± 7.0 residues and the most common length was 23 residues. The overall content of residues in transmembrane helices as a percentage of the full proteins had a median of 56.8% and an average of 55.7 ± 16.0%. Amino acid composition was analysed for the full proteins, transmembrane helices and extramembrane regions. Individual proteins or types of proteins with transmembrane helices containing extremes in contents of individual amino acids or combinations of amino acids with similar physicochemical properties were identified and linked to structure and/or function. In addition to overall median and average values, all results were analysed for proteins originating from different types of organism (prokaryotic, eukaryotic, viral) and for subgroups of receptors, channels, transporters and others.