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.     

Computational analysis of alpha-helical membrane protein structure: implications for the prediction of 3D structural models

Relatively little has been known about the structure of alpha-helical membrane proteins, since until recently few structures had been crystallized. These limited data have restricted structural analyses to the prediction of secondary structure, rather than tertiary folds. In order to address this, this paper describes an analysis of the 23 available membrane protein structures. A number of findings are made that are of particular relevance to transmembrane helix packing: (1) on average lipid-tail-accessible transmembrane residues are significantly more hydrophobic, less conserved and contain different residue types to buried residues; (2) charged residues are not always buried and, when accessible to membrane lipid tails, few are paired with another charge and instead they often interact with phospholipid head-groups or with other residue types; (3) a significant proportion of lipid-tail-accessible charged and polar residues form hydrogen bonds only with residues one turn away in the same helix (intra-helix); (4) pore-lining residues are usually hydrophobic and it is difficult to distinguish them from buried residues in terms of either residue type or conservation; and (5) information was gained about the proportion of helices that tend to contribute to lining a pore and the resulting pore diameter. These findings are discussed with relevance to the prediction of membrane protein 3D structure.     

A knowledge-based scoring function based on residue triplets for protein structure prediction

One of the general paradigms for ab initio protein structure prediction involves sampling the conformational space such that a large set of decoy (candidate) structures are generated and then selecting native-like conformations from those decoys using various scoring functions. In this study, based on a physical/geometric approach first suggested by Banavar and colleagues, we formulate a knowledge-based scoring function, which uses the radii of curvature formed among triplets of residues in a protein conformation. By analyzing its performance on various decoy sets, we determine a good set of parameters--the distance cutoff and the number of distance bins--to use for configuring such a function. Furthermore, we investigate the effect of using various approaches for compiling the prior distribution on the performance of the knowledge-based function. Possible extensions to the current form of the residue triplet scoring function are 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.     

Grow to Fit Molecular Dynamics (G2FMD): an ab initio method for protein side-chain assignment and refinement

The rough energy landscapes and tight packing of protein interiors are two of the critical factors that have prevented the wide application of physics-based models in protein side-chain assignment and protein structure prediction in general. Complementing the rotamer-based methods, we propose an ab initio method that utilizes molecular mechanics simulations for protein side-chain assignment and refinement. By reducing the side-chain size, a smooth energy landscape was obtained owing to the increased distances between the side chains. The side chains then gradually grow back during molecular dynamics simulations while adjusting to their surrounding driven by the interaction energies. The method overcomes the barriers due to tight packing that limit conformational sampling of physics-based models. A key feature of this approach is that the resulting structures are free from steric collisions and allow the application of all-atom models in the subsequent refinement. Tests on a small set of proteins showed nearly 100% accuracy on both chi1 and chi2 of buried residues and 94% of them were within 20 degrees from the native conformation, 79% were within 10 degrees and 42% were within 5 degrees . However, the accuracy decreased when exposed side chains were involved. Further improvement and application of the method and the possible reasons that affect the accuracy on the exposed side chains are discussed.     

Protein sequence entropy is closely related to packing density and hydrophobicity

We investigated the correlation between the Shannon information entropy, 'sequence entropy', with respect to the local flexibility of native globular proteins as described by inverse packing density. These are determined at each residue position for a total set of 130 query proteins, where sequence entropies are calculated from each set of aligned residues. For the accompanying aggregate set of 130 alignments, a strong linear correlation is observed between the calculated sequence entropy and the corresponding inverse packing density determined at an associated residue position. This region of linearity spans the range of C(alpha) packing densities from 12 to 25 amino acids within a sphere of 9 angstrom radius. Three different hydrophobicity scales all mimic the behavior of the sequence entropies. This confirms the idea that the ability to accommodate mutations is strongly dependent on the available space and on the propensity for each amino acid type to be buried. Future applications of these types of methods may prove useful in identifying both core and flexible residues within a protein.     

Analysis and prediction of inter-strand packing distances between {beta}-sheets of globular proteins

Any two ß-strands belonging to two different ß-sheetsin a protein structure are considered to pack interactivelyif each ß-strand has at least one residue that undergoesa loss of one tenth or more of its solvent contact surface areaupon packing. A data set of protein 3-D structures (determinedat 2.5 Å resolution or better), corresponding to 428 proteinchains, contains 1986 non-identical pairs of ß-strandsinvolved in interactive packing. The inter-axial distance betweenthese is significantly correlated to the weighted sum of thevolumes of the interacting residues at the packing interface.This correlation can be used to predict the changes in the inter-sheetdistances in equivalent ß-sheets in homologous proteinsand, therefore, is of value in comparative modelling of proteins.     

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.     

Development of pswudoenergy potentials for assessing protein 3-D-1-D compatibility and detecting weak homologies

Recent approaches to the 3-D-l-D compatibility problem ave triedto predict protein 3-D structure from sequence. One of the criticalfactors in this issue is the evaluation of fitness between agiven 3-D structure and any sequence mounted on it. We havedeveloped an evaluation function composed of four terms, sidechain packing, hydration, hydrogen bonding and local conformationpotentials, which were empirically derived from 101 proteinsof known structure. The efficiency of the evaluation functionwas tested hi two ways. In the first test, the sequence of proteinA is mounted (without gaps) on the structure of protein B whichis greater in size than A. For 81 proteins examined, the nativestructure was always detected. In the second test, a standardsequence homology search is performed against the entire database,followed by an assessment of the alignment with its proposedstructure, using the empirical evaluation function. When thistest was applied to the 101 proteins, our evaluation functionsuccessfully discriminated truly homologous sequence pairs fromnon-homologous proteins even when the sequence similaritieswere very weak. This approach was found to have clear advantagesover conventional sequence search methods.     

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.     

Can three-dimensional contacts in protein structures be predicted by analysis of correlated mutations?

A method has been developed to detect pairs of positions withcorrelated mutations in protein multiple sequence alignments.The method is based on reconstruction of the phylogenetic treefor a set of sequences and statistical analysis of the distributionof mutations in the branches of the tree. The database of homology-derivedprotein structures (HSSP) is used as the source of multiplesequence alignments for proteins of known three-dimensionalstructure. We analyse pairs of positions with correlated mutationsin 67 protein families and show quantitatively that the presenceof such positions is a typical feature of protein families.A significant but weak tendency is observed for correlated residuepairs to be close in the three-dimensional structure. With furtherimprovements, methods of this type may be useful for the predictionof residue-residue contacts and subsequent prediction of proteinstructure using distance geometry algorithms. In conclusion,we suggest a new experimental approach to protein structuredetermination in which selection of functional mutants afterrandom mutagenesis and analysis of correlated mutations providesufficient proximity constraints for calculation of the proteinfold     

Modeling membrane proteins based on low-resolution electron microscopy maps: a template for the TM domains of the oxalate transporter OxlT

The availability of both EM and high-resolution crystallographic data for several membrane proteins (MPs) permits a detailed evaluation of the ability of molecular modeling techniques to complement EM data in the development of models of MPs. A protocol for this purpose is presented, consisting of (1) identifying transmembrane (TM) domains from sequence; (2) assigning buried and lipid-exposed faces of the TM domains; and (3) assembling the TM domains into a bundle, based on geometric restraints obtained from the EM data. The protocol is validated by predicting the structures of several 7- and 12-TM MPs to within 3-5 A r.m.s.d. from their crystal structures. The protocol is applied to generate a model of the oxalate transporter OxlT, for which a high-resolution structure is not yet available.     

Determination of the structure of symmetric coiled-coil proteins from NMR data: application of the leucine zipper proteins Jun and GCN4

Previous attempts to determine the solution structures of homodimeric'leucine zippers' using nuclear magnetic resonance (NMR) spectroscopyhave been impeded by the complete symmetry of these coiled-coilmolecules, which makes it impossible a priori to distinguishbetween intra- and intermonomer dipolar connectivities. Consequently,a number of ad hoc approaches have been used in an attempt toderive tertiary solution structures of these molecules fromthe NMR data. In this paper we present a more rigorous approachfor analysing the NMR spectra of symmetric coiled-coil proteins.This analysis is based on calculations of intra- and intermonomerinterproton distances in the recently determined crystal structureof the GCN4 leucine zipper [O'Shea.E.K., KlemmJ.D., Kim.P.S.and Alber.T. (1991) Science, ISA, 539–543] and in symmetriccoiled-coil models of the leucine zippers of GCN4 and the humanoncoprotein Jun which we constructed using a dynamic simulatedannealing approach. This analysis has enabled the formulationof a set of rules for interpreting the NMR spectra of symmetriccoiled-coil proteins and has also led to the prediction of noveldipolar connectivities which we demonstrate in a 2-D NMR spectrumof the homodimeric Jun leucine zipper     

Structure prediction of subtilisin BPN' mutants using molecular dynamics methods

In this paper we describe the achievements and pitfalls encounteredin doing structure predictions of protein mutants using moleculardynamics simulation techniques in which properties of atomsare slowly changed as a function of time. Basically the methodconsists of a thermodynamic integration (slow growth) calculationused for free energy determination, but aimed at structure prediction;this allows for a fast determination of the mutant structure.We compared the calculated structure of the mutants Met222Ala,Met222Phe and Met222Gln of subtilisin BPN' with the respectiveX-ray structures and found good agreement between predictedand X-ray structure. The conformation of the residue subjectto the mutation is relatively easy to predict and is mainlydetermined by packing criteria. When the side chain has polargroups its exact orientation may pose problems; long-range Coulombinteractions may generate a polarization feedback involvingsystem relaxation times beyond the simulation time. Changesinduced in the environment are harder to predict using thismethod. In particular, rearrangement of the hydration structurewas difficult to predict correctly, probably because of thelong relaxation times. In all conversions made the changes observedin the environment were found to be history-dependent and inparticular the hydrogen bonding patterns provided evidence formetastable substates. In all cases the structure predicted wascompared with available kinetic data and the reduced activitycould be explained in terms of changes in the configurationof the active site.     

Enhanced Inter-helical Residue Contact Prediction in Transmembrane Proteins

In this paper, based on a recent work by McAllister and Floudas who developed a mathematical optimization model to predict the contacts in transmembrane alpha-helical proteins from a limited protein data set (McAllister and Floudas, 2008), we have enhanced this method by (1) building a more comprehensive data set for transmembrane alpha-helical proteins and this enhanced data set is then used to construct the probability sets, MIN-1N and MIN-2N, for residue contact prediction, (2) enhancing the mathematical model via modifications of several important physical constraints and (3) applying a new blind contact prediction scheme on different protein sets proposed from analyzing the contact prediction on 65 proteins from Fuchs et al. (2009). The blind contact prediction scheme has been tested on two different membrane protein sets. First, it is applied to five carefully selected proteins from the training set. The contact prediction of these five proteins uses probability sets built by excluding the target protein from the training set, and an average accuracy of 56% was obtained. Second, it is applied to six independent membrane proteins with complicated topologies, and the prediction accuracies are 73% for 2ZY9A, 21% for 3KCUA, 46% for 2W1PA, 64% for 3CN5A, 77% for 3IXZA and 83% for 3K3FA. The average prediction accuracy for the six proteins is 60.7%. The proposed approach is also compared with a support vector machine method (TMhit Lo et al., 2009) and it is shown that it exhibits better prediction accuracy.     

Physicochemical factors for discriminating between soluble and membrane proteins: hydrophobicity of helical segments and protein length

The average hydrophobicity of a polypeptide segment is consideredto be the most important factor in the formation of transmembranehelices, and the partitioning of the most hydrophobic (MH) segmentinto the alternative nonpolar environment, a membrane or hydrophobiccore of a globular protein may determine the type of proteinproduced. In order to elucidate the importance of the MH segmentin determining which of the two types of protein results froma given amino acid sequence, we statistically studied the characteristicsof MH helices, longer than 19 residues in length, in 97 membraneproteins whose three-dimensional structure or topology is known,as well as 397 soluble proteins selected from the Protein DataBank. The average hydrophobicity of MH helices in membrane proteinshad a characteristic relationship with the length of the protein.All MH helices in membrane proteins that were longer than 500residues had a hydrophobicity greater than 1.75 (Kyte and Doolittlescale), while the MH helices in membrane proteins smaller than100 residues could be as hydrophilic as 0.1. The possibilityof developing a method to discriminate membrane proteins fromsoluble ones, based on the effect of size on the type of proteinproduced, is discussed.     

Position-dependent protein mutant profile based on mean force field calculation

The application of the mean force field in protein mutant stabilityprediction is explored. Based on protein main chain characteristics,including polar fraction, accessibility and dihedral angles,the mean force field was constructed to evaluate the compatibilitybetween an amino acid residue and its environment, from whicha position-dependent protein mutant profile was constructed.At each position along a protein sequence, the native residuewas replaced by the other 19 types of amino acid residues. Thematches were evaluated by energies from mean force field calculation,from which a mutant profile along the protein sequence was derived.General characteristics of such a profile were analyzed. Mutantstabilities for two sets of mutants in two proteins were foundto be reasonable compared with experimental data, which indicatesthat the present method can act as a guide in protein engineeringand as an effective scoring matrix in protein sequence–structurealignment studies.     

Local polarity analysis: a sensitive method that discriminates between native proteins and incorrectly folded models

The evaluation of calculated protein structures is an importantstep in the protein design cycle. Known criteria for this assessmentof proteins are the polar and apolar, accessible and buriedsurface area, electrostatic interactions and other interactionsbetween the protein atoms (e.g. HO, S-S),atomic packing, analysisof amino acid environment and surface charge distribution. Weshow that a powerful test of accuracy of protein structure canbe derived by analysing the water contact of atoms and additionallytaking into account their polarity. On the basis of estimatedreference values of the polar fraction of typical globular proteinswith known structure (mean, SD and distribution), the evaluationof misfolded structures can be improved significantly. The referencevalues are derived by moving windows of different length (3–99amino acid residues) over the amino acid sequence. Model proteins,which are included in the Brookhaven protein structure databank,deliberately misfolded proteins, hypothetical proteins and predictedprotein structures are diagnosed as at least partially incorrectlyfolded. The local fault, mostly observed, is that polar groupsare buried too frequently in the interior of the protein. Thedatabase-derived quantities are useful in screening the designedproteins prior to experimentation and may also be useful inthe assessment of errors in the experimentally determined proteinstructures.     

Conservation of residue interactions in a family of Ca-binding proteins

In the TNC family of Ca-binding proteins (calmodulin, parvalbumin,intestinal calcium binding protein and troponin C) {small tilde}70 well-conserved amino acid sequences and six crystal structuresare known. We find a clear correlation between residue contactsin the structures and residue conservation in the sequences:residues with strong sidechain–sidechain contacts in thethree-dimensional structure tend to be the more conserved inthe sequence. This is one way to quantify the intuitive notionof the importance of sidechain interactions for maintainingprotein three-dimensional structure in evolution and may usefullybe taken into account in planning point mutations in proteinengineering.     

Refinement of protein cores and protein-peptide interfaces using a potential scaling approach

Refinement of side chain conformations in protein model structures and at the interface of predicted protein-protein or protein-peptide complexes is an important step during protein structural modelling and docking. A common approach for side chain prediction is to assume a rigid protein main chain for both docking partners and search for an optimal set of side chain rotamers to optimize the steric fit. However, depending on the target-template similarity in the case of comparative protein modelling and on the accuracy of an initially docked complex, the main chain template structure is only an approximation of a realistic target main chain. An inaccurate rigid main chain conformation can in turn interfere with the prediction of side chain conformations. In the present study, a potential scaling approach (PS-MD) during a molecular dynamics (MD) simulation that also allows the inclusion of explicit solvent has been used to predict side chain conformations on semi-flexible protein main chains. The PS-MD method converges much faster to realistic protein-peptide interface structures or protein core structures than standard MD simulations. Depending on the accuracy of the protein main chain, it also gives significantly better results compared with the standard rotamer search method.