Secondary structure prediction of the H5 pore of potassium channels

The ‘H5’ segment located between the putative fifthand sixth transmembrane helices is the most highly conservedregion in voltage-gated potassium channels and it is believedto constitute a major part of the ion conduction path (pore).Here we present a two-step procedure, comprising secondary structureprediction and hydrophobic moment profiling, to predict thestructure of this important region. Combined results from theapplication of the procedure to the H5 region of four voltage-gatedand five other K⁺ channel sequences lead to the prediction ofa ß-strand-turn-(3-strand structure for H5. The reasonsfor the application of these soluble protein methods to partsof membrane proteins are: (i) that pore-lining residues areaccessible to water and (ii) that a large enough database ofhighresolution membrane protein structures does not yet existThe results are compared with experimental results, in particularspectroscopic studies of two peptides based on the H5 sequenceof SHAKER potassium channel. The procedure developed here maybe applicable to wateraccessible regions of other membrane proteins.     

Maintenance of the hydrophobic face of the diphtheria toxin amphipathic transmembrane helix 1 is essential for the efficient delivery of the catalytic domain to the cytosol of target cells

Abstract The transmembrane (T) domain of diphtheria toxin (DT) comprisesnine -helices and has been shown to play an essential role inthe efficent delivery of the catalytic (C) domain ofDT acrossthe eukaryotic cell membrane and into the cytosol. We have demonstratedrecently thatthe first three amphipathic helixes of the T domain,although not necessary for either channel formation or receptorbinding, are required for the efficient transmembrane deliveryof the Cdomain.In the present study,we have performed a detailedstructure-function analysis of T domainhelix 1 (TH1) of theDT-related fusion protein DAB₃₈₉lL-2. We performed exchangeandsite-directed mutagenesis of TH1 and the resulting mutantfusion toxins were analyzed by gel electrophoresis and testedfor their efficiencies in the delivery of the C domain to thecell cytosol. We demonstrate that the overall charge distributionand hydrophobicity of amino acids in the amphipathic helix TH1,rather than a specific amino acid sequence, are critical forthe function of this helix. The insertion of a charged residuein the hydrophobic face of TH1 abolishes cytotoxic activity,whereas replacement of a hydrophobic residue by a charged aminoacid in the hydrophilic face of the helix has little, if any,effect on cytotoxic activity. In addition,we have identifiedSer220 by site-directed mutagenesis as a residue that appearsto be criticalfor correct folding of the fusion toxin. Mutationsin this position result in fusion proteins that are extremelysensitive to proteolytic attack.     

Predicting surface exposure of amino acids from protein sequence

The amino acid residues on a protein surface play a key rolein interaction with other molecules, determine many physicalproperties, and constrain the structure of the folded protein.A database of monomeric protein crystal structures was usedto teach computer-simulated neural networks rules for predictingsurface exposure from local sequence. These trained networksare able to correctly predict surface exposure for 72% of residuesin a testing set using a binary model (buried/exposed) and for54% of residues using a ternary model (buried/intermediate/exposed).In the ternary model, only 11% of the exposed residues are predictedas buried and only 5% of the buried residues are predicted asexposed. Also, since the networks are able to predict exposurewith a quantitative confidence estimate, it is possible to assignexposure for over half of the residues in a binary model with>80% accuracy. Even more accurate predictions are obtainedby making a consensus prediction of exposure for a homologousfamily. The effect of the local environment of an amino acidon its accessibility, though smaller than expected, is significantand accounts for the higher success rate of prediction thanobtained with previously used criteria. In the absence of athree-dimensional structure, the ability to predict surfaceaccessibility of amino acids directly from the sequence is avaluable tool in choosing sites of chemical modification orspecific mutations and in studies of molecular interaction.     

Membrane proteins: from sequence to structure

The prediction of protein structure from sequence has been along-standing goal of molecular biology. Integral membrane proteins,once abhorred by protein chemists and crystallographers becauseof their insolubility and stubborn refusal to yield good crystals,now appear to hold great promises for efficient structure predictionand engineering. This is mainly due to the constraints on permissiblestructures imposed by the lipid environment, and to the apparentuncoupling between an initial membrane targeting and insertionprocess which determines the overall topological arrangementof the transmembrane segments and a subsequent –condensation—of these segments into a unique folded state. Recent work suggeststhat the membrane insertion process is controlled by simplesequence elements composed of different combinations of longhydrophobic regions and flanking charged residues. In this reviewwe sketch the most unportant structural rules relating aminoacid sequence to membrane insertion to fully folded molecule,and their use for prediction and protein-engineering purposes.     

Sequence divergence analysis for the prediction of seven-helix membrane protein structures: I. Comparison with bacteriorhodopsin

A method using protein sequence divergence to predict the three-dimensionalstructure of the transmembrane domain of seven-helix membraneproteins is described. The key component in the multistep procedureis the calculation of a hydrophilic and lipophilic variabilityindex for each amino acid in an alignment of a family of homologousproteins. The variability profile, a plot of the calculatedvariability index versus alignment position, can be used topredict a tertiary model of the backbone conformation of thetransmembrane domain. This method was applied to bacteriorhodopsin(BR) and the model obtained was compared with the known structureof this protein. Using an alignment of the amino acid sequencesof BR and closely related (20% identity) proteins, the boundariesof the transmembrane regions, their secondary structures andorientations inside the membrane bilayer were predicted basedon the variability profile. Additional information about theshape of the helix bundle was also obtained from the averagevariability of each transmembrane helix with the assumptionthat the helices are packed sequentially and form a closed helixbundle. Correct features of the known structure of BR were foundin the model structure, suggesting that a similar strategy canbe used to predict transmembrane helices and the packing shapeof other membrane proteins with seven transmembrane helices,such as the opsins and other G-protein coupled receptors.     

Sequence divergence analysis for the prediction of seven-helix membrane protein structures: II. A 3-D model of human rhodopsin

A three-dimensional (3-D) model of the transmembrane domainof human rhodopsin was predicted from the sequence divergenceanalysis of 42 sequences of rhodopsins and visual pigments withouta template. The prediction steps include multiple sequence alignment,calculation of a variability profile of the aligned sequences,use of the variability profile to identify the boundaries oftransmembrane regions, their secondary structure and packingshape in a helix bundle, prediction of side-chain conformationsand structure refinement. The identification of the retinalbinding site was assisted by its known covalent linkage withK296. The structural features of the predicted 3-D model arein good agreement with a low resolution electron density mapof bovine rhodopsin and with residues in contact with retinalas determined experimentally.     

Homology modelling of transferrin-binding protein A from Neisseria meningitidis

Neisseria meningitidis, a causative agent of bacterial meningitis, obtains transferrin-bound iron by expressing two outer membrane located transferrin-binding proteins, TbpA and TbpB. TbpA is thought to be an integral outer membrane pore that facilitates iron uptake. Evidence suggests that TbpA is a useful antigen for inclusion in a vaccine effective against meningococcal disease, hence the identification of regions involved in ligand binding is of paramount importance to design strategies to block uptake of iron. The protein shares sequence and functional similarities to the Escherichia coli siderophore receptors FepA and FhuA, whose structures have been determined. These receptors are composed of two domains, a 22-stranded beta-barrel and an N-terminal plug region that sits within the barrel and occludes the transmembrane pore. A three-dimensional TbpA model was constructed using FepA and FhuA structural templates, hydrophobicity analysis and homology modelling. TbpA was found to possess a similar architecture to the siderophore receptors. In addition to providing insights into the highly immunogenic nature of TbpA and allowing the prediction of potentially important ligand-binding epitopes, the model also reveals a narrow channel through its entire length. The relevance of this channel and the spatial arrangement of external loops, to the mechanism of iron translocation employed by TbpA is discussed.     

An improved prediction of catalytic residues in enzyme structures

The protein databases contain a huge number of function unknown proteins, including many proteins with newly determined 3D structures resulted from the Structural Genomics Projects. To accelerate experiment-based assignment of function, de novo prediction of protein functional sites, like active sites in enzymes, becomes increasingly important. Here, we attempted to improve the prediction of catalytic residues in enzyme structures by seeking and refining different encodings (i.e. residue properties) as well as employing new machine learning algorithms. In particular, considering that catalytic residues can often reveal specific network centrality when representing enzyme structure as a residue contact network, the corresponding measurement (i.e. closeness centrality) was used as one of the most important encodings in our new predictor. Meanwhile, a genetic algorithm integrated neural network (GANN) was also employed. Thanks to the above strategies, our GANN predictor demonstrated a high accuracy of 91.2% in the prediction of catalytic residues based on balanced datasets (i.e. the 1:1 ratio of catalytic to non-catalytic residues). When the GANN method was optimally applied to real enzyme structures, 73.9% of the tested structures had the active site correctly located. Compared with two existing methods, the proposed GANN method also demonstrated a better performance.     

A simple approach for protein structure discrimination based on the network pattern of conserved hydrophobic residues

Evolutionarily conserved hydrophobic residues at the core of protein structures are generally assumed to play a structural role in protein folding and stability. Recent studies have implicated that their importance to protein structures is uneven, with a few of them being crucial and the rest of them being secondary. In this work, we explored the possibility of employing this feature of native structures for discriminating non-native structures from native ones. First, we developed a network tool to quantitatively measure the structural contributions of individual amino acid residues. We systematically applied this method to diverse fold-type sets of native proteins. It was confirmed that this method could grasp the essential structural features of native proteins. Next, we applied it to a number of decoy sets of proteins. The results indicate that such an approach indeed identified non-native structures in most test cases. This finding should be of help for the investigation of the fundamental problem of protein structure prediction.     

A study of structural determinants in the interleukin-1 fold

The structures of interleukin-1ß, basic fibroblastgrowth factor and Erythrina trypsin inhibitor have been analysedin order to determine whether the hydrophobic core remains conserved,even when the structures have extremely low sequence similarities.We find that there are significant differences in the way eachprotein achieves a satisfactory arrangement of core residuesand that positions which contribute to the core of one structureare not guaranteed to contribute to the integrity of another.Furthermore, the side-chain packing arrangements of these coreresidues vary significantly between the three structures. Duringthis analysis the side-chain rotamers for three independentlydetermined interleukin-1ß structures were also compared.It was found that although buried residues are generally inagreement the remaining residues frequently occupy differentrotamers in the three structures. This suggests that althoughmeaningful studies are possible for buried side-chains the resultsobtained from equivalent analyses of accessible residues shouldbe treated with caution. These results are discussed with specificreference to the optimization of side-chain packing in proteinsof known structure.     

Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction

De novo protein structure prediction plays an important role in studies of helical membrane proteins as well as structure-based drug design efforts. Developing an accurate scoring function for protein structure discrimination and validation remains a current challenge. Network approaches based on overall network patterns of residue packing have proven useful in soluble protein structure discrimination. It is thus of interest to apply similar approaches to the studies of residue packing in membrane proteins. In this work, we first carried out such analysis on a set of diverse, non-redundant and high-resolution membrane protein structures. Next, we applied the same approach to three test sets. The first set includes nine structures of membrane proteins with the resolution worse than 2.5 A; the other two sets include a total of 101 G-protein coupled receptor models, constructed using either de novo or homology modeling techniques. Results of analyses indicate the two criteria derived from studying high-resolution membrane protein structures are good indicators of a high-quality native fold and the approach is very effective for discriminating native membrane protein folds from less-native ones. These findings should be of help for the investigation of the fundamental problem of membrane protein structure prediction.     

Parameter relation rows: a query system for protein structure function relationships

In the course of molecular modeling or mutant prediction oneoften wants quick answers to questions such as: ‘Are thereany residues in a beta-strand that point into an internal cavity,and are highly mutable?;’ ‘Are there large polarresidues in a helix that make a contact with a hydrophobic residuein a sheet, and don't make the maximal number of hydrogen bonds?’or ‘Which hydrophobic residues are in a helix with a largehydrophobic moment, and make a contact with a co-factor, butat the same time still have a large accessible surface?’.I describe here a method to get answers to these kinds of questionsin a very quick and easy manner. The method described is partlybased on the principles used in the design of relational databases,and its mode of operation is similar to the query methods usedin a relational database environment. Although designed foraiding in molecular modeling, its applicability is much moregeneral. The method has been implemented as part of a largemolecular modeling package which copes with the numerous problemsin systematic handling of protein structures, e.g. residue numbering.This also implies that many normal tools such as graphical analyses,I/O facilities, etc. are available on-line.     

A 3D model of the {delta} opioid receptor and ligand-receptor complexes

A model for the 3D structure of the transmembrane domain ofthe opioid receptor was predicted from the sequence divergenceanalysis of 42 sequences of G-protein coupled peptide hormonereceptors belonging to the opioid, somatostatin and angiotensinreceptor families. No template was used in the prediction steps,which include multiple sequence alignment, calculation of avariability profile of the aligned sequences, use of the variabilityprofile to identify the boundaries of transmembrane regions,prediction of their secondary structure, optimization of thepacking shape in a helix bundle, prediction of side chain conformationsand structural refinement The general shape of the model issimilar to that of the low resolution rhodopsin structure inthat the TM3 and TM7 helices are most buried in the bundle andthe TM1 and TM4 helices are most exposed to the lipid phase.An initial assessment of this model was made by determiningto what extent a binding site identified using four structurallydisparate high affinity opioid ligands was consistent withknown mutational studies. With the assumption that the pro-tonatedamine nitrogen, a feature common to all opioid ligands, interactswith the highly conserved Aspl27 in TM3, a pocket was foundthat satisfied the criteria of complementarity to the requirementsfor receptor recognition for these four diverse ligands, two selective antagonists (the fused ring naltrindole and the peptideTyr-Tic-Phe-Phe-NH₂) and the two agonists lofentanil and BW373U86deduced from previous studies of the ligands alone. These ligandscould be accommodated in a similar region of the receptor. Thereceptor binding site identified in the optimized complexescontained many residues in positions known to affect ligandbinding in G-protein coupled receptors. These results also allowedidentification of key residues as candidates for point mutationsfor further assessment and refinement of this model as wellas preliminary indications of the requirements for recognitionof this receptor.     

Comparison of three algorithms for the assignment of secondary structure in proteins: the advantages of a consensus assignment

Accurate assignments of secondary structures in proteins arecrucial for a useful comparison with theoretical predictions.Three major programs which automatically determine the locationof helices and strands are used for this purpose, namely DSSP,P-Curve and Define. Their results have been compared for a non-redundantdatabase of 154 proteins. On a residue per residue basis, thepercentage match score is only 63% between the three methods.While these methods agree on the overall number of residuesin each of the three states (helix, strand or coil), they differon the number of helices or strands, thus implying a wide discrepancyin the length of assigned structural elements. Moreover, thelength distribution of helices and strands points to the existenceof artefacts inherent to each assignment algorithm. To overcomethese difficulties a consensus assignment is proposed whereeach residue is assigned to the state determined by at leasttwo of the three methods. With this assignment the artefactsof each algorithm are attenuated. The residues assigned in thesame state by the three methods are better predicted than theothers. This assignment will thus be useful for analysing thesuccess rate of prediction methods more accurately.     

Non-polar nuclei in fungal microbial RNases

An application of a previously proposed method for the analysisof the non-polar structure of proteins is presented. A detailedanalysis of the composition and properties of non-polar nucleiand microclusters of fungal microbial ribonucleases has beenperformed on the basis of the 3-D structures of RNase T1 andrelated proteins. Three hydrophobic nuclei were found in thesestructures. It has been shown that all residues in non-polarnuclei have high homology ({small tilde}89%). Residues in thenuclei are practically fully buried in the interior of a molecule.Detailed analysis of non-polar nuclei properties shows thatthese nuclei determine the hydrophobic core of a protein andthe location and role of each residue in the non-polar interiorof proteins. In addition it was found that there are variableresidues not only on the surface of a protein but on the surfaceof the nuclei inside the protein and between the nuclei andthat there is a consistent region in all proteins, the hydrophobic-nuclei. An evaluation of the stability of non-polar nuclei,the conservation of their compositions and their positions inthe protein globule, allows one to assume that these three nucleiplay an important functional role in the stability and foldingof molecules of RNases and possibly can be considered as independentstructural elements of 3-D structures of these proteins.     

Role of Conserved Residues and F322 in the Extracellular Vestibule of the Rat P2X7 Receptor in Its Expression,Function and Dye Uptake Ability

Activation of the P2X7 receptor results in the opening of a large pore that plays a role in immune responses, apoptosis, and many other physiological and pathological processes. Here, we investigated the role of conserved and unique residues in the extracellular vestibule connecting the agonist-binding domain with the transmembrane domain of rat P2X7 receptor. We found that all residues that are conserved among the P2X receptor subtypes respond to alanine mutagenesis with an inhibition (Y51, Q52, and G323) or a significant decrease (K49, G326, K327, and F328) of 2′,3′-O-(benzoyl-4-benzoyl)-ATP (BzATP)-induced current and permeability to ethidium bromide, while the nonconserved residue (F322), which is also present in P2X4 receptor, responds with a 10-fold higher sensitivity to BzATP, much slower deactivation kinetics, and a higher propensity to form the large dye-permeable pore. We examined the membrane expression of conserved mutants and found that Y51, Q52, G323, and F328 play a role in the trafficking of the receptor to the plasma membrane, while K49 controls receptor responsiveness to agonists. Finally, we studied the importance of the physicochemical properties of these residues and observed that the K49R, F322Y, F322W, and F322L mutants significantly reversed the receptor function, indicating that positively charged and large hydrophobic residues are important at positions 49 and 322, respectively. These results show that clusters of conserved residues above the transmembrane domain 1 (K49–Y51–Q52) and transmembrane domain 2 (G326–K327–F328) are important for receptor structure, membrane expression, and channel gating and that the nonconserved residue (F322) at the top of the extracellular vestibule is involved in hydrophobic inter-subunit interaction which stabilizes the closed state of the P2X7 receptor channel.     

Predicting leucine zipper structures from sequence

The leucine zipper structure is adopted by one family of thecoiled coil proteins. Leucine zippers have a characteristicleucine repeat: Leu–X₆–Leu–X₆–Leu–X₆–Leu(where X may be any residue). However, many sequences have theleucine repeat, but do not adopt the leucine zipper structure(we shall refer to these as non-zippers). We have found andanalyzed residue pair patterns that allow one to identify correctly90% of leucine zippers and 97% of non-zippers. Simpler analyses,based on the frequency of occurrence of residues at certainpositions, specify, at most, 65% of zippers and 80–90%of non-zippers. Both short and long patterns contribute to thesuccessful discrimination of leucine zippers from non-zippers.A number of these patterns involve hydrophobic residues thatwould be placed on the solvent-exposed surface of the helix,were the sequence to adopt a leucine zipper structure. Thus,an analysis of protein sequences has allowed us to improve discriminationbetween leucine zippers and non-zippers, and has provided somefurther insight into the physical factors influencing the leucinezipper structure.     

Context dependence of phenotype prediction and diversity in combinatorial mutagenesis

Two different combinatorial mutagenesis experiments on the light-harvestingII (LH2) protein of Rhodobacter capsulatus indicate that heuristicrules relating sequence directly to phenotype are dependenton which sets or groups of residues are mutated simultaneously.Previously reported combinatorial mutagenesis of this chromogenicprotein (based on both phylogenetic and structural models) showedthat substituting amino acids with large molar volumes at Gly^ß31caused the mutated protein to have a spectrum characteristicof light-harvesting I (LH1). The six residues that underwentcombinatorial mutagenesis were modeled to lie on one side ofa transmembrane -helix that binds bacteriochlorophyll. In asecond experiment described here, we have not used structuralmodels or phylogeny in choosing mutagenesis sites. Instead,a set of six contiguous residues was selected for combinatorialmutagenesis. In this latter experiment, the residue substitutedat Gly^ß31 was not a determining factor in whetherLH2 or LH1 spectra were obtained; therefore, we conclude thatthe heuristic rules for phenotype prediction are context dependent.While phenotype prediction is context dependent, the abilityto identify elements of primary structure causing phenotypediversity appears not to be. This strengthens the argument forperforming combinatorial mutagenesis with an arbitrary groupingof residues if structural models are unavailable.     

Hydrophobic potential by pairwise surface area sum

An approximate but rapid method for estimating hydrophobic energyis proposed. Aside from a scale factor, it is given by the pairwisesum of the surface area buried by each neighbor atom, but excludingthose atoms in the same residue or in its sequence neighborresidues. This sum is found to be linearly related to the trueburied area as calculated by the algorithm of Lee and Richards[1971, J. Mol Biol., 55, 379-400], and to the contact potentialof Miyazawa and Jernigan [1985, Macromolecules, 18, 534-552].It correlates with experimental transfer free energies to approximatelythe same degree as that calculated using the true buried area.Furthermore, in a simple test of helix packing with ROP proteinmonomer, the new hydrophobic energy clearly discriminated onestructure, with the lowest r.m.s. deviation from the crystalstructure, against an exhaustive set of others.