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.     

TM Finder: a prediction program for transmembrane protein segments using a combination of hydrophobicity and nonpolar phase helicity scales

Based on the principle of dual prediction by segment hydrophobicity and nonpolar phase helicity, in concert with imposed threshold values of these two parameters, we developed the automated prediction program TM Finder that can successfully locate most transmembrane (TM) segments in proteins. The program uses the results of experiments on a series of host-guest TM segment mimic peptides of prototypic sequence KK AAAXAAAAAXAAWAAXAAAKKKK-amide (where X = each of the 20 commonly occurring amino acids) through which an HPLC-derived hydropathy scale, a hydrophobicity threshold for spontaneous membrane insertion, and a nonpolar phase helical propensity scale were determined. Using these scales, the optimized prediction algorithm of TM Finder defines TM segments by first searching for competent core segments using the combination of hydrophobicity and helicity scales, and then performs a gap-joining operation, which minimizes prediction bias caused by local hydrophilic residues and/or the choice of window size. In addition, the hydrophobicity threshold requirement enables TM Finder to distinguish reliably between membrane proteins and globular proteins, thereby adding an important dimension to the program. A full web version of the TM Finder program can be accessed at http://www.bioinformatics-canada.org/TM/.     

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.     

Proteome-wide functional classification and identification of prokaryotic transmembrane proteins by transmembrane topology similarity comparison

We propose a new method for classifying and identifying transmembrane (TM) protein functions in proteome-scale by applying a single-linkage clustering method based on TM topology similarity, which is calculated simply from comparing the lengths of loop regions. In this study, we focused on 87 prokaryotic TM proteomes consisting of 31 proteobacteria, 22 gram-positive bacteria, 19 other bacteria, and 15 archaea. Prior to performing the clustering, we first categorized individual TM protein sequences as "known," "putative" (similar to "known" sequences), or "unknown" by using the homology search and the sequence similarity comparison against SWISS-PROT to assess the current status of the functional annotation of the TM proteomes based on sequence similarity only. More than three-quarters, that is, 75.7% of the TM protein sequences are functionally "unknown," with only 3.8% and 20.5% of them being classified as "known" and "putative," respectively. Using our clustering approach based on TM topology similarity, we succeeded in increasing the rate of TM protein sequences functionally classified and identified from 24.3% to 60.9%. Obtained clusters correspond well to functional superfamilies or families, and the functional classification and identification are successfully achieved by this approach. For example, in an obtained cluster of TM proteins with six TM segments, 109 sequences out of 119 sequences annotated as "ATP-binding cassette transporter" are properly included and 122 "unknown" sequences are also contained.     

PRALINETM: a strategy for improved multiple alignment of transmembrane proteins

MOTIVATION: Membrane-bound proteins are a special class of proteins. The regions that insert into the cell-membrane have a profoundly different hydrophobicity pattern compared with soluble proteins. Multiple alignment techniques use scoring schemes tailored for sequences of soluble proteins and are therefore in principle not optimal to align membrane-bound proteins. RESULTS: Transmembrane (TM) regions in protein sequences can be reliably recognized using state-of-the-art sequence prediction techniques. Furthermore, membrane-specific scoring matrices are available. We have developed a new alignment method, called PRALINETM, which integrates these two features to enhance multiple sequence alignment. We tested our algorithm on the TM alignment benchmark set by Bahr et al. (2001), and showed that the quality of TM alignments can be significantly improved compared with the quality produced by a standard multiple alignment technique. The results clearly indicate that the incorporation of these new elements into current state-of-the-art alignment methods is crucial for optimizing the alignment of TM proteins. AVAILABILITY: A webserver is available at http://www.ibi.vu.nl/programs/pralinewww.     

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

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

Effect of sequence hydrophobicity and bilayer width upon the minimum length required for the formation of transmembrane helices in membranes

The minimum hydrophobic length necessary to form a transmembrane (TM) helix in membranes was investigated using model membrane-inserted hydrophobic helices. The fluorescence of a Trp at the center of the sequence and its sensitivity to quenching were used to ascertain helix position within the membrane. Peptides with hydrophobic cores composed of poly(Leu) were compared to sequences containing a poly 1:1 Leu:Ala core (which have a hydrophobicity typical of natural TM helices). Studies varying bilayer width revealed that the poly(Leu) core peptides predominately formed a TM state when the bilayer width exceeded hydrophobic sequence length by (i.e. when negative mismatch was) up to ∼ 11-12 Å (e.g. the case of a 11-12 residue hydrophobic sequence in bilayers with a biologically relevant width, i.e. dioleoylphosphatidylcholine (DOPC) bilayers), while poly(LeuAla) core peptides formed predominantly TM state with negative mismatch of up to 9 Å (a 13 residue hydrophobic sequence in DOPC bilayers). This indicates that minimum length necessary to form a predominating amount of a TM state (minimum TM length) is only modestly hydrophobicity-dependent for the sequences studied here, and a formula that defines the minimum TM length as a function of hydrophobicity for moderately-to-highly hydrophobic sequences was derived. The minimum length able to form a stable TM helix for alternating LeuAla sequences, and that for sequences with a Leu block followed by an Ala block, was similar, suggesting that a hydrophobicity gradient along the sequence may not be an important factor in TM stability. TM stability was also similar for sequences flanked by different charged ionizable residues (Lys, His, Asp). However, ionizable flanking residues destabilized the TM configuration much more when charged than when uncharged. The ability of short hydrophobic sequences to form TM helices in membranes in the presence of substantial negative mismatch implies that lipid bilayers have a considerable ability to adjust to negative mismatch, and that short TM helices may be more common than generally believed. Factors that modulate the ability of bilayers to adjust to mismatch may strongly affect the configuration of short hydrophobic helices.     

How strongly do sequence conservation patterns and empirical scales correlate with exposure patterns of transmembrane helices of membrane proteins?

Given the difficulty in determining high-resolution structures of helical membrane proteins, sequence-based prediction methods can be useful in elucidating diverse physiological processes mediated by this important class of proteins. Predicting the angular orientations of transmembrane (TM) helices about the helix axes, based on the helix parameters from electron microscopy data, is a classical problem in this regard. This problem has triggered the development of a number of different empirical scales. Recently, sequence conservation patterns were also made use of for improved predictions. Empirical scales and sequence conservation patterns (collectively termed as "prediction scales") have also found frequent applications in other research areas of membrane proteins: for example, in structure modeling and in prediction of buried TM helices. This trend is expected to grow in the near future unless there are revolutionary developments in the experimental characterization of membrane proteins. Thus, it is timely and imperative to carry out a comprehensive benchmark test over the prediction scales proposed so far to determine their pros and cons. In the current analysis, we use exposure patterns of TM helices as a golden standard, because if one develops a prediction scale that correlates perfectly with exposure patterns of TM helices, it will enable one to predict buried residues (or buried faces) of TM helices with an accuracy of 100%. Our analysis reveals several important points. (1) It demonstrates that sequence conservation patterns are much more strongly correlated with exposure patterns of TM helices than empirical scales. (2) Scales that were specifically parameterized using structure data (structure-based scales) display stronger correlation than hydrophobicity-based scales, as expected. (3) A nonnegligible difference is observed among the structure-based scales in their correlational property, suggesting that not every learning algorithm is equally effective. (4) A straightforward framework of optimally combining sequence conservation patterns and empirical scales is proposed, which reveals that improvements gained from combining the two sources of information are not dramatic in almost all cases. In turn, this calls for the development of fundamentally different scales that capture the essentials of membrane protein folding for substantial improvements.     

The erythropoietin receptor transmembrane domain mediates complex formation with viral anemic and polycythemic gp55 proteins

Erythropoietin receptor (EpoR) activation is crucial for mature red blood cell production. The murine EpoR can also be activated by the envelope protein of the polycythemic (P) spleen focus forming virus (SFFV), gp55-P. Due to differences in the TM sequence, gp55 of the anemic (A) strain SFFV, gp55-A, cannot efficiently activate the EpoR. Using antibody-mediated immunofluorescence co-patching, we show that the majority of EpoR forms hetero-oligomers at the cell surface with gp55-P and, surprisingly, with gp55-A. The EpoR TM domain is targeted by gp55-P and -A, as only chimeric receptors containing EpoR TM sequences oligomerized with gp55 proteins. Both gp55-P and gp55-A are homodimers on the cell surface, as shown by co-patching. However, when the homomeric interactions of the isolated TM domains were assayed by TOXCAT bacterial reporter system, only the TM sequence of gp55-P was dimerized. Thus, homo-oligomerization of gp55 proteins is insufficient for full EpoR activation, and a correct conformation of the dimer in the TM region is required. This is supported by the failure of gp55-A-->P, a mutant protein whose TM domain can homo-oligomerize, to fully activate EpoR. As unliganded EpoR forms TM-dependent but inactive homodimers, we propose that the EpoR can be activated to different extents by homodimeric gp55 proteins, depending on the conformation of the gp55 protein dimer in the TM region.     

Not all transmembrane helices are born equal: Towards the extension of the sequence homology concept to membrane proteins

Background

Sequence homology considerations widely used to transfer functional annotation to uncharacterized protein sequences require special precautions in the case of non-globular sequence segments including membrane-spanning stretches composed of non-polar residues. Simple, quantitative criteria are desirable for identifying transmembrane helices (TMs) that must be included into or should be excluded from start sequence segments in similarity searches aimed at finding distant homologues.

Results

We found that there are two types of TMs in membrane-associated proteins. On the one hand, there are so-called simple TMs with elevated hydrophobicity, low sequence complexity and extraordinary enrichment in long aliphatic residues. They merely serve as membrane-anchoring device. In contrast, so-called complex TMs have lower hydrophobicity, higher sequence complexity and some functional residues. These TMs have additional roles besides membrane anchoring such as intra-membrane complex formation, ligand binding or a catalytic role. Simple and complex TMs can occur both in single- and multi-membrane-spanning proteins essentially in any type of topology. Whereas simple TMs have the potential to confuse searches for sequence homologues and to generate unrelated hits with seemingly convincing statistical significance, complex TMs contain essential evolutionary information.

Conclusion

For extending the homology concept onto membrane proteins, we provide a necessary quantitative criterion to distinguish simple TMs (and a sufficient criterion for complex TMs) in query sequences prior to their usage in homology searches based on assessment of hydrophobicity and sequence complexity of the TM sequence segments.

Reviewers

This article was reviewed by Shamil Sunyaev, L. Aravind and Arcady Mushegian.     

On filtering false positive transmembrane protein predictions

While helical transmembrane (TM) region prediction tools achieve high (>90%) success rates for real integral membrane proteins, they produce a considerable number of false positive hits in sequences of known nontransmembrane queries. We propose a modification of the dense alignment surface (DAS) method that achieves a substantial decrease in the false positive error rate. Essentially, a sequence that includes possible transmembrane regions is compared in a second step with TM segments in a sequence library of documented transmembrane proteins. If the performance of the query sequence against the library of documented TM segment-containing sequences in this test is lower than an empirical threshold, it is classified as a non-transmembrane protein. The probability of false positive prediction for trusted TM region hits is expressed in terms of E-values. The modified DAS method, the DAS-TMfilter algorithm, has an unchanged high sensitivity for TM segments ( approximately 95% detected in a learning set of 128 documented transmembrane proteins). At the same time, the selectivity measured over a non-redundant set of 526 soluble proteins with known 3D structure is approximately 99%, mainly because a large number of falsely predicted single membrane-pass proteins are eliminated by the DAS-TMfilter algorithm.     

kPROT: a knowledge-based scale for the propensity of residue orientation in transmembrane segments. Application to membrane protein structure prediction

Modeling of integral membrane proteins and the prediction of their functional sites requires the identification of transmembrane (TM) segments and the determination of their angular orientations. Hydrophobicity scales predict accurately the location of TM helices, but are less accurate in computing angular disposition. Estimating lipid-exposure propensities of the residues from statistics of solved membrane protein structures has the disadvantage of relying on relatively few proteins. As an alternative, we propose here a scale of knowledge-based Propensities for Residue Orientation in Transmembrane segments (kPROT), derived from the analysis of more than 5000 non-redundant protein sequences. We assume that residues that tend to be exposed to the membrane are more frequent in TM segments of single-span proteins, while residues that prefer to be buried in the transmembrane bundle interior are present mainly in multi-span TMs. The kPROT value for each residue is thus defined as the logarithm of the ratio of its proportions in single and multiple TM spans. The scale is refined further by defining it for three discrete sections of the TM segment; namely, extracellular, central, and intracellular. The capacity of the kPROT scale to predict angular helical orientation was compared to that of alternative methods in a benchmark test, using a diversity of multi-span alpha-helical transmembrane proteins with a solved 3D structure. kPROT yielded an average angular error of 41 degrees, significantly lower than that of alternative scales (62 degrees -68 degrees ). The new scale thus provides a useful general tool for modeling and prediction of functional residues in membrane proteins. A WWW server (http://bioinfo.weizmann.ac.il/kPROT) is available for automatic helix orientation prediction with kPROT.     

Non-native interhelical hydrogen bonds in the cystic fibrosis transmembrane conductance regulator domain modulated by polar mutations

Polar residues comprise about 15% of the transmembrane (TM) domains of proteins, where they can stabilize structure via native side chain-side chain interhelical hydrogen bonds between TM helices. However, non-native H-bonds may be implicated in disease states, through limiting protein dynamics during transport and/or misfolding the protein by inducing non-native rotational positions about TM helical axes. Here we have undertaken an investigation of the presence and strength of H-bond interactions within a series of helix-loop-helix ("hairpin") constructs derived from TM helices 3 and 4 (italic) of the cystic fibrosis transmembrane conductance regulator (CFTR) (prototypic sequence G(194)LALAHFVWIAPLQ(207)VALLMGLIWELLQASAFAGLGFLIV(232)LALFQ(237)AGLG(241)) in which wild-type Q207 in TM3 forms an interhelical H-bond with CF-phenotypic mutant V232D in TM4 [Therien, A. G., Grant, F. E., and Deber, C. M. (2001) Nat. Struct. Biol 8, 597-601]. In the present work, a library of 21 TM3/4 constructs was prepared, where Asp residues were placed individually at TM4 positions 221-241. Using gel shift assays-in which H-bond-linked hairpins (closed conformation) migrate faster than the elongated forms (open conformation)-we found that Q207 in TM3 is able to "capture" all 21 TM4 D mutations into measurable populations of interhelical H-bonds. A similar library of TM4 D mutants-but also containing Q207L-reverted to wild-type migration rates, confirming Q207 as the polar partner for TM4 D residues. In view of the broad capture range of Q207, these results emphasize the potential consequences to folding and dynamics of introducing polar mutations into the TM domains of membrane proteins in the vicinity of a native polar TM residue.     

Nuclear trafficking of FGFR1: a role for the transmembrane domain

Several members of the fibroblast growth factor (FGF) family lack signal peptide (SP) sequences and are present only in trace amounts outside the cell. However, these proteins contain nuclear localization signals (NLS) and accumulate in the cell nucleus. Our studies have shown that full length FGF receptor 1 (FGFR1) accumulates within the nuclear interior in parallel with FGF-2. We tested the hypothesis that an atypical transmembrane domain (TM) plays a role in FGFR1 trafficking into the nuclear interior. With FGFR1 destined for constitutive fusion with the plasma membrane due to its SP, how the receptor may enter the nucleus is unclear. Sequence analysis identified that FGFR1 has an atypical TM containing short stretches of hydrophobic amino acids (a.a.) interrupted by polar a.a. The beta-sheet is the predicted conformation of the FGFR1 TM, in contrast to the alpha-helical conformation of other single TM tyrosine kinase receptors, including FGFR4. Receptor trafficking in live cells was studied by confocal microscopy via C-terminal FGFR1 fusions to enhanced green fluorescent protein (EGFP) and confirmed by subcellular fractionation and Western immunoblotting. Nuclear entry of FGFR1-EGFP was independent of karyokinessis, and was observed in rapidly proliferating human TE671 cells, in slower proliferating glioma SF763 and post-mitotic bovine adrenal medullary cells (BAMC). In contrast, a chimeric FGFR1/R4-EGFP, where the TM of FGFR1 was replaced with that of FGFR4, was associated with membranes (golgi-ER, plasma, and nuclear), but was absent from the nucleus and cytosol. FGFR1delta-EGFP mutants, with hydrophobic TM a.a. replaced with polar a.a., showed reduced association with membranes and increased cytosolic/nuclear accumulation with an increase in TM hydrophilicity. FGFR1(TM-)-EGFP (TM deleted), was detected in the golgi-ER vesicles, cytosol, and nuclear interior; thus demonstrating that the FGFR1 TM does not function as a NLS. To test whether cytosolic FGFR1 provides a source of nuclear FGFR1, cells were transfected with FGFR1(SP-) (SP was deleted), resulting in cytosolic, non-membrane, protein accumulation in the cytosol and the cell nucleus. Our results indicate that an unstable association with cellular membranes is responsible for the release of FGFR1 into the cytosol and cytosolic FGFR1 constitutes the source of the nuclear receptor.     

A knowledge-based scale for amino acid membrane propensity

In this article, a membrane-propensity scale for amino acids is derived using only two ingredients: (i) a set of transmembrane helices segments from membrane protein crystal structures and (ii) the request that each component of the set has a free energy lower than that of a typical soluble protein sequence of the same length. Although the most widely used hydropathy scales satisfy this request, we use an optimization procedure that allows for extraction of an optimal scale, which correlates equally well with those scales. We show that, if the choice of the sequence database is accurate, significant knowledge-based scales, which are robust with respect to changes in the learning set, can be easily derived. The obtained scales can be used for transmembrane helices prediction. The predictive power of one of these scales is tested on membrane proteins, soluble proteins, and signal peptides databases, finding that its performances is comparable with those of the hydropathy scales.     

Local sequence patterns of hydrophobicity and solvent accessibility in soluble globular proteins

We examined the variation in the solvent accessibility and hydrophobicity of the amino acids along the sequences of 58 soluble globular proteins with known tertiary structure. We found that there is a significant tendency for the accessibilities to run in clusters along the sequence but that the hydrophobicities are distributed without such nonrandom clusters. Theseresults suggest severe limitations on the power of sequence analysis tools that use average hydrophobicity scores of overlapping subsequences to predict accessibility.     

A novel scoring function for predicting the conformations of tightly packed pairs of transmembrane alpha-helices

Pairs of helices in transmembrane (TM) proteins are often tightly packed. We present a scoring function and a computational methodology for predicting the tertiary fold of a pair of alpha-helices such that its chances of being tightly packed are maximized. Since the number of TM protein structures solved to date is small, it seems unlikely that a reliable scoring function derived statistically from the known set of TM protein structures will be available in the near future. We therefore constructed a scoring function based on the qualitative insights gained in the past two decades from the solved structures of TM and soluble proteins. In brief, we reward the formation of contacts between small amino acid residues such as Gly, Cys, and Ser, that are known to promote dimerization of helices, and penalize the burial of large amino acid residues such as Arg and Trp. As a case study, we show that our method predicts the native structure of the TM homodimer glycophorin A (GpA) to be, in essence, at the global score optimum. In addition, by correlating our results with empirical point mutations on this homodimer, we demonstrate that our method can be a helpful adjunct to mutation analysis. We present a data set of canonical alpha-helices from the solved structures of TM proteins and provide a set of programs for analyzing it (http://ashtoret.tau.ac.il/~sarel). From this data set we derived 11 helix pairs, and conducted searches around their native states as a further test of our method. Approximately 73% of our predictions showed a reasonable fit (RMS deviation <2A) with the native structures compared to the success rate of 8% expected by chance. The search method we employ is less effective for helix pairs that are connected via short loops (<20 amino acid residues), indicating that short loops may play an important role in determining the conformation of alpha-helices in TM proteins.     

Defining the transmembrane helix of M2 protein from influenza A by molecular dynamics simulations in a lipid bilayer

Integral membrane proteins containing at least one transmembrane (TM) alpha-helix are believed to account for between 20% and 30% of most genomes. There are several algorithms that accurately predict the number and position of TM helices within a membrane protein sequence. However, these methods tend to disagree over the beginning and end residues of TM helices, posing problems for subsequent modeling and simulation studies. Molecular dynamics (MD) simulations in an explicit lipid and water environment are used to help define the TM helix of the M2 protein from influenza A virus. Based on a comparison of the results of five different secondary structure prediction algorithms, three different helix lengths (an 18mer, a 26mer, and a 34mer) were simulated. Each simulation system contained 127 POPC molecules plus approximately 3500-4700 waters, giving a total of approximately 18,000-21,000 atoms. Two simulations, each of 2 ns duration, were run for the 18mer and 26mer, and five separate simulations were run for the 34mer, using different starting models generated by restrained in vacuo MD simulations. The total simulation time amounted to 11 ns. Analysis of the time-dependent secondary structure of the TM segments was used to define the regions that adopted a stable alpha-helical conformation throughout the simulation. This analysis indicates a core TM region of approximately 20 residues (from residue 22 to residue 43) that remained in an alpha-helical conformation. Analysis of atomic density profiles suggested that the 18mer helix revealed a local perturbation of the lipid bilayer. Polar side chains on either side of this region form relatively long-lived H-bonds to lipid headgroups and water molecules.     

Designing transmembrane alpha-helices that insert spontaneously

Direct measurement of the free energies of transfer of hydrophobic membrane-spanning alpha-helices from water to membranes is important for the determination of an accurate experiment-based hydrophobicity scale for membrane proteins. An important objective of such a scale is to account for the presently unknown thermodynamic cost of partitioning hydrogen-bonded peptide bonds into the membrane hydrocarbon core. We describe here the physical properties of a transmembrane (TM) peptide, TMX-1, designed to test the feasibility of engineering peptides that spontaneously insert across bilayers but that have the important property of measurable monomeric water solubility. TMX-1, Ac-WNALAAVAAAL-AAVAAALAAVAAGKSKSKS-NH(2), is a 31-residue sequence with a 21-residue nonpolar core, N- and C-caps to favor helix formation, and a highly polar C-terminus to improve solubility and to control directionality of insertion into lipid vesicles. TMX-1 appeared to be soluble in water up to a concentration of at least 1 mg/mL (0.3 mM). However, fluorescence spectroscopy, fluorescence quenching, and circular dichroism (CD) spectroscopy indicated that the high solubility was due to the formation of molecular aggregates that persisted at peptide concentrations down to at least 0.1 microM peptide. Nevertheless, aqueous TMX-1 partitioned strongly into membrane vesicles with apparent mole-fraction free-energy values of -7.1 kcal mol(-1) for phosphatidylcholine (POPC) vesicles and -8.2 kcal mol(-1) for phosphatidylglycerol (POPG) vesicles. CD spectroscopy of TMX-1 in oriented multilayers formed from either lipid disclosed a very strong preference for a transmembrane alpha-helical conformation. When TMX-1 was added to preformed vesicles, it was fully helical. A novel fluorescence resonance energy transfer (FRET) method demonstrated that at least 50% of the TMX-1 insered spontaneously across the vesicle membranes. Binding and insertion were found to be fully reversible for POPC vesicles but not POPG vesicles. TMX-1 was thus found to have many of the properties required for thermodynamic measurements of TM peptide insertion. Importantly, the results obtained delineate the experimental problems that must be considered in the design of peptides that can partition spontaneously and reversibly as monomers into and across membranes. Our success with TMX-1 suggests that these problems are not insurmountable.     

Mammalian Prion protein expression in yeast; a model for transmembrane insertion

The prion protein (PrP), a GPI-anchored glycoprotein, is inefficiently secreted by mammalian microsomes, 50% being found as transmembrane (TM) proteins with the central TM1 segment spanning the membrane. TM1 hydrophobicity is marginal for lateral membrane insertion, which is primarily driven by hydrophobic interaction between the ER translocon and substrates in transit. Most inserted TM1 has its N-terminus in the ER lumen (Ntm orientation), as expected for arrest of normal secretion. However, 20% is found in inverted Ctm orientation. These are minor species in vivo, presumably a consequence of efficient quality control. PrP mutations that increase TM1 hydrophobicity result in increased Ctm insertion, both in vitro and in mouse brain, and a strong correlation is found between CtmPrP insertion and neuropathology in transgenic mice; a copper-dependent pathogenicity mechanism is suggested. PrP fusions with a C-terminal epitope tag, when expressed in yeast cells at moderate levels, appear to interact efficiently with the translocon, providing a useful model for testing the effects of PrP mutations on TM insertion and orientation. However, secretion of PrP by the mammalian translocon requires the TRAP complex, absent in yeast, where essentially all PrP ends up as TM species, 85–90% Ntm and 10–15% Ctm. Although yeast is, therefore, an incomplete mimic of mammalian PrP trafficking, effects on Ctm insertion of mutations increasing TM1 hydrophobicity closely reflect those seen in vitro. Electrostatic substrate-translocon interactions are a major determinant of TM protein insertion orientation and the yeast model was used to investigate the role of the large negative charge difference across TM1, a likely cause of translocation delay that would favor TM insertion and Ctm orientation. An increase in ΔCh from −5 to −7 caused a marked increase in Ctm insertion, while a decrease to −3 or −1 allowed 35 and about 65% secretion, respectively. Utility of the yeast model and the role of this charge difference in driving PrP membrane insertion are confirmed.