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.     

An automatic method for predicting transmembrane protein structures using cryo-EM and evolutionary data

The transmembrane (TM) domains of many integral membrane proteins are composed of alpha-helix bundles. Structure determination at high resolution (<4 A) of TM domains is still exceedingly difficult experimentally. Hence, some TM-protein structures have only been solved at intermediate (5-10 A) or low (>10 A) resolutions using, for example, cryo-electron microscopy (cryo-EM). These structures reveal the packing arrangement of the TM domain, but cannot be used to determine the positions of individual amino acids. The observation that typically, the lipid-exposed faces of TM proteins are evolutionarily more variable and less charged than their core provides a simple rule for orienting their constituent helices. Based on this rule, we developed score functions and automated methods for orienting TM helices, for which locations and tilt angles have been determined using, e.g., cryo-EM data. The method was parameterized with the aim of retrieving the native structure of bacteriorhodopsin among near- and far-from-native templates. It was then tested on proteins that differ from bacteriorhodopsin in their sequences, architectures, and functions, such as the acetylcholine receptor and rhodopsin. The predicted structures were within 1.5-3.5 A from the native state in all cases. We conclude that the computational method can be used in conjunction with cryo-EM data to obtain approximate model structures of TM domains of proteins for which a sufficiently heterogeneous set of homologs is available. We also show that in those proteins in which relatively short loops connect neighboring helices, the scoring functions can discriminate between near- and far-from-native conformations even without the constraints imposed on helix locations and tilt angles that are derived from cryo-EM.     

Fourier transform coupled to tryptophan-scanning mutagenesis: lessons from its application to the prediction of secondary structure in the acetylcholine receptor lipid-exposed transmembrane domains

Although Fourier transform (FT) and tryptophan-scanning mutagenesis (TrpScanM) have been extremely useful for predicting secondary structures of membrane proteins, they are deemed to be low-resolution techniques. Herein, we describe the combined use of FT and TrpScanM (FT-TrpScanM) as a more reliable approach for the prediction of secondary structure. Five TrpScanM studies of the acetylcholine receptor lipid-exposed transmembrane domains (LETMDs) were revisited and analyzed by FT-TrpScanM. FT analysis of the raw data from the aforementioned TrpScanM studies supports and validates the conclusions derived from their tryptophan-periodicity profiles. Furthermore, by FT-TrpScanM, we were able to determine the minimum number of consecutive tryptophan substitutions necessary for more robust prediction of alpha-helical secondary structures and evaluate the quality of structure predictions by alpha-helical character curves. Finally, this study encourages future utilization of FT-TrpScanM to more reliably predict secondary structures of the membrane protein LETMDs.     

Enhanced recognition of protein transmembrane domains with prediction-based structural profiles

MOTIVATION: Membrane domain prediction has recently been re-evaluated by several groups, suggesting that the accuracy of existing methods is still rather limited. In this work, we revisit this problem and propose novel methods for prediction of alpha-helical as well as beta-sheet transmembrane (TM) domains. The new approach is based on a compact representation of an amino acid residue and its environment, which consists of predicted solvent accessibility and secondary structure of each amino acid. A recently introduced method for solvent accessibility prediction trained on a set of soluble proteins is used here to indicate segments of residues that are predicted not to be accessible to water and, therefore, may be 'buried' in the membrane. While evolutionary profiles in the form of a multiple alignment are used to derive these simple 'structural profiles', they are not used explicitly for the membrane domain prediction and the overall number of parameters in the model is significantly reduced. This offers the possibility of a more reliable estimation of the free parameters in the model with a limited number of experimentally resolved membrane protein structures. RESULTS: Using cross-validated training on available sets of structurally resolved and non-redundant alpha and beta membrane proteins, we demonstrate that membrane domain prediction methods based on such a compact representation outperform approaches that utilize explicitly evolutionary profiles and multiple alignments. Moreover, using an external evaluation by the TMH Benchmark server we show that our final prediction protocol for the TM helix prediction is competitive with the state-of-the-art methods, achieving per-residue accuracy of approximately 89% and per-segment accuracy of approximately 80% on the set of high resolution structures used by the TMH Benchmark server. At the same time the observed rates of confusion with signal peptides and globular proteins are the lowest among the tested methods. The new method is available online at http://minnou.cchmc.org.     

Characterization of peptides corresponding to the seven transmembrane domains of human adenosine A2a receptor

Human adenosine A(2)a receptor is a member of the G-protein-coupled receptor (GPCR) superfamily of seven-helix transmembrane (TM) proteins. To test general models for membrane-protein folding and to identify specific features of folding and assembly for this representative member of an important and poorly understood class of proteins, we synthesized peptides corresponding to its seven TM domains. We assessed the ability of the peptides to insert into micelles and vesicles and measured secondary structure for each peptide in aqueous and membrane-mimetic environments. CD spectra indicate that each of the seven TM peptides form thermally stable, independent alpha-helical structures in both micelles and vesicles. The helical content of the peptides depends on the nature of the membrane-mimetic environment. Four of the peptides (TM3, TM4, TM5, and TM7) exhibit very high-helical structure, near the predicted maximum for their TM segments. The TM1 peptide also adopts relatively high alpha-helical structures. In contrast, two of peptides, TM2 and TM6, display low alpha helicity. Similarly, the ability of the peptides to insert into membrane-mimetic environments, assayed by intrinsic tryptophan fluorescence and fluorescence quenching, varied markedly. Most peptides exhibit higher alpha helicity in anionic sodium dodecyl sulfate than in neutral dodecyl-beta-D-maltoside micelles, and TM2 was disordered in zwiterionic DMPC but was alpha-helical in negatively charged DMPC/DMPG vesicles. These findings strongly suggest that electrostatic interactions between lipids and peptides control the insertion of the peptides and may be involved in membrane-protein-folding events. The measured helical content of these TM domains does not correlate with the predicted helicity based on amino acid sequence, pointing out that, while hydrophobic interactions can be a major determinant for folding of TM peptides, other factors, such as electrostatic interactions or helix-helix interactions, may play significant roles for specific TM domains. Our results represent a comprehensive analysis of helical propensities for a human GPCR and support models for membrane-protein folding in which interactions between TM domains are required for proper insertion and folding of some TM helix domains. The tendency of some peptides to self-associate, especially in aqueous environments, underscores the need to prevent improper interactions during folding and refolding of membrane proteins in vivo and in vitro.     

Transmembrane segment IV contributes a functionally important interface for oligomerization of the Class II G protein-coupled secretin receptor

Oligomerization of the Class II G protein-coupled secretin receptor has been reported, but the molecular basis for this and its functional significance have not been determined. In the current work, we have examined the possible contribution of each of the transmembrane (TM) segments of this receptor to its homo-oligomerization, using the method of competitive disruption screening for inhibition of receptor bioluminescence resonance energy transfer signal. TM IV was the only segment that was found to disrupt receptor bioluminescence resonance energy transfer. Evaluation of predicted interhelical and lipid-exposed faces of this TM segment demonstrated that its lipid-exposed face represented the determinant for oligomerization. This was further confirmed by mutagenesis of the intact secretin receptor. Morphological FRET was utilized to demonstrate that secretin receptor oligomerization occurred at the cell surface and that this oligomerization was disrupted by mutating Gly(243) and Ile(247), key residues within the lipid-exposed face of TM IV. Although disruption of the receptor oligomerization interface had no effect on secretin binding parameters, it reduced the ability of secretin to stimulate intracellular cAMP. This supports a clear functional effect of oligomerization of this receptor. Such an effect might be particularly relevant to clinical situations in which this receptor is overexpressed, such as in certain neoplasms.     

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.     

Structure and dynamics of the second and third transmembrane domains of human glycine receptor

A 61-residue polypeptide resembling the second and third transmembrane domains (TM23) of the alpha-1 subunit of human glycine receptor and its truncated form, both with the wild-type loop linking the two TM domains (the "23" loop), were studied using high-resolution NMR. Well-defined domain structures can be identified for the TM2, 23 loop, and TM3 regions. Contrary to the popular model of a long and straight alpha-helical structure for the pore-lining TM2 domain for the Cys-loop receptor family, the last three residues of the TM2 domain and the first eight residues of the 23 loop (S16-S26) seem to be intrinsically nonhelical and highly flexible even in trifluoroethanol, a solvent known to promote and stabilize alpha-helical structures. The six remaining residues of the 23 loop and most of the TM3 domain exhibit helical structures with a kinked pi-helix (or a pi-turn) from W34 to C38 and a kink angle of 159 +/- 3 degrees . The tertiary fold of TM3 relative to TM2 is defined by several unambiguously identified long-range NOE cross-peaks within the loop region and between TM2 and TM3 domains. The 20 lowest-energy structures show a left-handed tilt of TM3 relative to TM2 with a tilting angle of 44 +/- 2 degrees between TM2 (V1-Q14) and TM3 (L39-E48) helix axes. This left-handed TM2-TM3 arrangement ensures a neatly packed right-handed quaternary structure of five subunits to form an ion-conducting pore. This is the first time that two TM domains of the glycine receptor linked by the important 23 loop have ever been analyzed at atomistic resolution. Many structural characteristics of the receptor can be inferred from the structural and dynamical features identified in this study.     

TMPDB: a database of experimentally-characterized transmembrane topologies

TMPDB is a database of experimentally-characterized transmembrane (TM) topologies. TMPDB release 6.2 contains a total of 302 TM protein sequences, in which 276 are alpha-helical sequences, 17 beta-stranded, and 9 alpha-helical sequences with short pore-forming helices buried in the membrane. The TM topologies in TMPDB were determined experimentally by means of X-ray crystallography, NMR, gene fusion technique, substituted cysteine accessibility method, N-linked glycosylation experiment and other biochemical methods. TMPDB would be useful as a test and/or training dataset in improving the proposed TM topology prediction methods or developing novel methods with higher performance, and as a guide for both the bioinformaticians and biologists to better understand TM proteins. TMPDB and its subsets are freely available at the following web site: http://bioinfo.si.hirosaki-u.ac.jp/~TMPDB/.     

Retention of native-like oligomerization states in transmembrane segment peptides: application to the Escherichia coli aspartate receptor

Biophysical study of the transmembrane (TM) domains of integral membrane proteins has traditionally been impeded by their hydrophobic nature. As a result, an understanding of the details of protein-protein interactions within membranes is often lacking. We have demonstrated previously that model TM segments with flanking cationic residues spontaneously fold into alpha-helices upon insertion into membrane-mimetic environments. Here, we extend these studies to investigate whether such constructs consisting of TM helices from biological systems retain their native secondary structures and oligomeric states. Single-spanning TM domains from the epidermal growth factor receptor (EGFR), glycophorin A (GPA), and the influenza A virus M2 ion channel (M2) were designed and synthesized with three to four lysine residues at both N- and C-termini. Each construct was shown to adopt an alpha-helical conformation upon insertion into sodium dodecyl sulfate micelles. Furthermore, micelle-inserted TM segments associated on SDS-PAGE gels according to their respective native-like oligomeric states: EGFR was monomeric, GPA was dimeric, and M2 was tetrameric. This approach was then used to investigate whether one or both of the TM segments (Tar-1 and Tar-2) from the Escherichia coli aspartate receptor were responsible for its homodimeric nature. Our results showed that Tar-1 formed SDS-resistant homodimers, while Tar-2 was monomeric. Furthermore, no heterooligomerization between Tar-1 and Tar-2 was detected, implicating the Tar-1 helix as the oligomeric determinant for the Tar protein. The overall results indicate that this approach can be used to elucidate the details of TM domain folding for both single-spanning and multispanning membrane proteins.     

Combining hydrophobicity and helicity: a novel approach to membrane protein structure prediction

In spite of the overwhelming numbers and critical biological functions of membrane proteins, only a few have been characterized by high-resolution structural techniques. From the structures that are known, it is seen that their transmembrane (TM) segments tend to fold most often into alpha-helices. To evaluate systematically the features of these TM segments, we have taken two approaches: (1) using the experimentally-measured residence behavior of specifically designed hydrophobic peptides in RP-HPLC, a scale was derived based directly on the properties of individual amino acids incorporated into membrane-interactive helices: and (2) the relative alpha-helical propensity of each of the 20 amino acids was measured in the organic non-polar environment of n-butanol. By combining the resulting hydrophobicity and helical propensity data, in conjunction with consideration of the 'threshold hydrophobicity' required for spontaneous membrane integration of protein segments, an approach was developed for prediction of TM segments wherein each must fulfill the dual requirements of hydrophobicity and helicity. Evaluated against the available high-resolution structural data on membrane proteins, the present combining method is shown to provide accurate predictions for the locations of TM helices. In contrast, no segment in soluble proteins was predicted as a 'TM helix'.     

Charged single alpha-helix: a versatile protein structural motif

A few highly charged natural peptide sequences were recently suggested to form stable alpha-helical structures in water. In this article we show that these sequences represent a novel structural motif called "charged single alpha-helix" (CSAH). To obtain reliable candidate CSAH motifs, we developed two conceptually different computational methods capable of scanning large databases: SCAN4CSAH is based on sequence features characteristic for salt bridge stabilized single alpha-helices, whereas FT_CHARGE applies Fourier transformation to charges along sequences. Using the consensus of the two approaches, a remarkable number of proteins were found to contain putative CSAH domains. Recombinant fragments (50-60 residues) corresponding to selected hits obtained by both methods (myosin 6, Golgi resident protein GCP60, and M4K4 protein kinase) were produced and shown by circular dichroism spectroscopy to adopt largely alpha-helical structure in water. CSAH segments differ substantially both from coiled-coil and intrinsically disordered proteins, despite the fact that current prediction methods recognize them as either or both. Analysis of the proteins containing CSAH motif revealed possible functional roles of the corresponding segments. The suggested main functional features include the formation of relatively rigid spacer/connector segments between functional domains as in caldesmon, extension of the lever arm in myosin motors and mediation of transient interactions by promoting dimerization in a range of proteins.     

Role of structural and sequence information in the prediction of protein stability changes: comparison between buried and partially buried mutations.

Predicting mutation-induced changes in protein stability is one of the greatest challenges in molecular biology. In this work, we analyzed the correlation between stability changes caused by buried and partially buried mutations and changes in 48 physicochemical, energetic and conformational properties. We found that properties reflecting hydrophobicity strongly correlated with stability of buried mutations, and there was a direct relation between the property values and the number of carbon atoms. Classification of mutations based on their location within helix, strand, turn or coil segments improved the correlation of mutations with stability. Buried mutations within beta-strand segments correlated better than did those in alpha-helical segments, suggesting stronger hydrophobicity of the beta-strands. The stability changes caused by partially buried mutations in ordered structures (helix, strand and turn) correlated most strongly and were mainly governed by hydrophobicity. Due to the disordered nature of coils, the mechanism underlying their stability differed from that of the other secondary structures: the stability changes due to mutations within the coil were mainly influenced by the effects of entropy. Further classification of mutations within coils, based on their hydrogen-bond forming capability, led to much stronger correlations. Hydrophobicity was the major factor in determining the stability of buried mutations, whereas hydrogen bonds, other polar interactions and hydrophobic interactions were all important determinants of the stability of partially buried mutations. Information about local sequence and structural effects were more important for the prediction of stability changes caused by partially buried mutations than for buried mutations; they strengthened correlations by an average of 27% among all data sets.     

Prediction of buried helices in multispan alpha helical membrane proteins

Analysis of a database of structures of membrane proteins shows that membrane proteins composed of 10 or more transmembrane (TM) helices often contain buried helices that are inaccessible to phospholipids. We introduce a method for identifying TM helices that are least phospholipid accessible and for prediction of fully buried TM helices in membrane proteins from sequence information alone. Our method is based on the calculation of residue lipophilicity and evolutionary conservation. Given that the number of buried helices in a membrane protein is known, our method achieves an accuracy of 78% and a Matthew's correlation coefficient of 0.68. A server for this tool (RANTS) is available online at http://gila.bioengr.uic.edu/lab/.     

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/.     

Spectroscopic studies of fibrinogen and its plasmin-derived fragments.

The secondary structure of human fibrinogen and its plasmin-fragments have been studied by FTIR spectroscopy. The quantitative results for fibrinogen are in good agreement with previous studies using circular dichroism spectroscopy. After treatment of fibrinogen with plasmin in buffer containing Ca2+, two major fragments are produced: fragment E (Mw 45,000) and fragment D (Mw 100,000). Fragment E is shown to contain 50% alpha-helical values, attributed to its coiled-coil portions, and minor beta-strands and turn structures. Its deuteration gives evidence of the presence of solvent-exposed alpha-helical structures. On the other hand, fragment D contains a distribution of secondary structure values of 35% alpha-helix, 29% beta-sheet segments and 17% turn structures. Fragment D itself has two domains: a portion of the original coiled-coil and also a thermally labile globular domain. The coiled-coil portion (Mw 27,000) was isolated and showed a high alpha-helical content (around 70%). The globular domain is estimated to be rich in beta-sheet structures. The spectra of fibrin clots formed in Ca(2+)-containing buffer have a lower amide I/amide II ratio than fibrinogen spectra, which is interpreted as being due to aggregation.     

waveTM: wavelet-based transmembrane segment prediction

waveTM is a web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. Prediction is performed by a dynamic programming algorithm on wavelet-denoised 'hydropathy' signals. Users submit a protein sequence and receive interactively the results. Topology prediction can also be obtained in conjunction with the algorithm OrienTM. A web server that implements the waveTM algorithm is freely available at http://bioinformatics.biol.uoa.gr/waveTM.     

Transmembrane organization of the Bacillus subtilis chemoreceptor McpB deduced by cysteine disulfide crosslinking

The Bacillus subtilis chemoreceptor McpB is a dimer of identical subunits containing two transmembrane (TM) segments (TM1, residues 17-34: TM2, residues 280-302) in each monomer with a 2-fold axis of symmetry. To study the organization of the TM domains, the wild-type receptor was mutated systematically at the membrane bilayer/extracytoplasmic interface with 15 single cysteine (Cys) substitutions in each of the two TM domains. Each single Cys substitution was capable of complementing a null allele in vivo, suggesting that no significant perturbation of the native tertiary or quaternary structure of the chemoreceptor was introduced by the mutations. On the basis of patterns of disulfide crosslinking between subunits of the dimeric receptor, an alpha-helical interface was identified between TM1 and TM1' (containing residues 32, 36, 39, and 43) and between TM2 and TM2' (containing residues 276, 277, 280, 283 and 286). Pairs of cysteine substitutions (positions 34/280 and 38/273) in TM1 and TM2 were used to further elucidate specific contacts within a monomer subunit, enabling a model to be constructed defining the organization of the TM domain. Crosslinking of residues that were 150-180 degrees removed from position 32 (positions 37, 41, and 44) suggested that the receptors may be organized as an array of trimers of dimers in vivo. All crosslinking was unaffected by deletion of cheB and cheR (loss of receptor demethylation/methylation enzymes) or by deletion of cheW and cheV (loss of proteins that couple receptors with the autophosphorylating kinase). These findings indicate that the organization of the transmembrane region and the stability of the quaternary complex of receptors are independent of covalent modifications of the cytoplasmic domain and conformations in the cytoplasmic domain induced by the coupling 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.