{beta}-sheet folding of fragment (16-36) of bovine pancreatic trypsin inhibitor as predicted by Monte Carlo simulated annealing

A tertiary structure prediction is described using Monte Carlosimulated annealing for the peptide fragment corresponding toresidues 16–36 of bovine pancreatic trypsin inhibitor(BPTI). The simulation starts with randomly chosen initial conformationsand is performed without imposing experimental constraints usingenergy functions given for generic interatomic interactions.Out of 20 simulation trials, seven conformations show a sheet-likestructure—two strands connected by a turn—althoughthis sheet-like structure is not as rigid as that observed innative BPTI. It is also shown that these conformations are mostlylooped and exhibit a native- like right-handed twist. Unlikethe case with the C-peptide of RNase A, no conspicuous -helicalstructure is found in any of the final conformations obtainedin the simulation. However, the lowest-energy conformation doesnot resemble exactly the native structure. This indicates thatthe rigid ß-sheet conformation of native BPTI merelycorresponds to a local minimum of the energy function if thefragment with residues 16–36 is isolated from the nativeprotein. A statistical analysis of all 20 final conformationssuggests that the tendency for the peptide segments to formextended ß-strands is strong for those with residues18–24, and moderate for those with residues 30–35.The segment of residues 25–29 does not tend to form anydefinite structure. In native BPTI, the former segments areinvolved in the ß-sheet and the latter in the turn.A folding scenario is also speculated from this analysis.     

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.     

Finding the global minimum: a fuzzy end elimination implementation

The ‘fuzzy end elimination theorem’ (FEE) is a mathematicallyproven theorem that identifies rotameric states in proteinswhich are incompatible with the global minimum energy conformation.While implementing the FEE we noticed two different aspectsthat directly affected the final results at convergence. First,the identification of a single dead-ending rotameric state cantrigger a ‘domino effect’ that initiates the identificationof additional rotameric states which become dead-ending. A recursivecheck for deadending rotameric states is therefore necessaryevery time a dead-ending rotameric state is identified. It isshown that, if the recursive check is omitted, it is possibleto miss the identification of some dead-ending rotameric statescausing a premature termination of the elimination process.Second, we examined the effects of removing dead-ending rotamericstates from further considerations at different moments of time.Two different methods of rotameric state removal were examinedfor an order dependence. In one case, each rotamer found tobe incompatible with the global minimum energy conformationwas removed immediately following its identification. In theother, dead-ending rotamers were marked for deletion but retainedduring the search, so that they influenced the evaluation ofother rotameric states. When the search was completed, all markedrotamers were removed simultaneously. In addition, to expandfurther the usefulness of the FEE, a novel method is presentedthat allows for further reduction in the remaining set of conformationsat the FEE convergence. In this method, called a tree-basedsearch, each dead-ending pair of rotamers which does not leadto the direct removal of either rotameric state is used to reducesignificantly the number of remaining conformations. In thefuture this method can also be expanded to triplet and quadrupletsets of rotameric states. We tested our implementation of theFEE by exhaustively searching ten protein segments and foundthat the FEE identified the global minimum every time. For eachsegment, the global minimum was exhaustively searched in twodifferent environments: (i) the segments were extracted fromthe protein and exhaustively searched in the absence of thesurrounding residues; (ii) the segments were exhaustively searchedin the presence of the remaining residues fixed at crystal structureconformations. We also evaluated the performance of the methodfor accurately predicting side chain conformations. We examinedthe influence of factors such as type and accuracy of backbonetemplate used, and the restrictions imposed by the choice ofpotential function, parameterization and rotamer database. Conclusionsare drawn on these results and future prospects are given     

Solution conformations of human growth hormone releasing factor: comparison of the restrained molecular dynamics and distance geometry methods for a system without long-range distance data

A series of three-dimensional structures of the 1–29 fragmentof human growth hormone releasing factor in trifluoroethanolhave been determined by molecular dynamics and distance geometrymethods. The resulting structures satisfy information from nuclearOverhauser effect (NOE) distance data and an empirical potentialenergy function. Although the polypeptide was found to havean ordered structure in all simulations, the NOE data were notsufficient for global convergence to a unique three-dimensionalgeometry. Several satisfactory structures have been determined,all of which are extended conformations consisting of a shortß-strand and two -helices (residues 6–13 andresidues 16–29) connected by short segments of less welldefined secondary structure. Because of the lack of NOE dataconnecting the helix segments, their relative orientation isnot uniquely determined.     

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.     

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.     

Similarity graphing and enzyme-reaction database: methods to detect sequence regions of importance for recognition of chemical structures

We developed a new method which searches sequence segments responsiblefor the recognition of a given chemical structure. These segmentsare detected as those locally conserved among a sequence tobe analyzed (target sequence) and a set of sequences (referencesequences). Reference sequences are the sequences of functionallyrelated proteins, ligands of which contain a common chemicalsubstructure in their molecular structures. ‘Similaritygraphing’ cuts target sequences into segments, alignsthem with reference sequence pairwise, calculates the degreeof similarity for each alignment, and shows graphically cumulativesimilarity values on target sequence. Any locally conservedregions, short or long in length and weak or strong in similarity,are detected at their optimal conditions by adjusting threeparameters. The ‘enzyme-reaction database’ containschemical structures and their related enzymes. When a chemicalsubstructure is input into the database, sequences of the enzymesrelated to the input substructure are systematically searchedfrom the NBRF sequence database and output as reference sequences.Examples of analysis using similarity graphing in combinationwith the enzyme-reaction database showed a great potentialityin the systematic analysis of the relationships between sequencesand molecular recognitions for protein engineering.     

A novel search method for protein sequence-structure relations using property profiles

In protein engineering and design it is very important thatresidues can be inspected in their specific environment. A standardrelational database system cannot serve this purpose adequatelybecause it cannot handle relations between individual residues.With SCAN3D we introduce a new database system for integratedsequence and structure analysis of proteins. It uses the relationalparadigm wherever possible. Its main power, however, stems fromthe ability to retrieve stretches of consecutive residues withcertain properties by comparing a property profile with allstretches of residues in the database, exploiting the orderedcharacter of proteins. In doing so, it bypasses the large numberof join operations that would be required by relational databasesystems. An additional advantage of using property profile matchingis that searches can be carried out allowing a pre-set numberof mismatches. Also, as the database is read-only, SCAN3D doesnot need interactive data update mechanisms. Queries typicalof a molecular engineering environment are demonstrated withspecific examples: analysis of peptides that induce local structure,analysis of site-dependent rotamers and residue-residue contactanalysis     

A relational database of protein structures designed for flexible enquiries about conformation

A relational database of protein structure has been developedto enable rapid and flexible enquiries about the occurrenceof many aspects of protein architecture. The coordinates of294 proteins from the Brookhaven Data Bank have been processedby standard computer programs to generate many additional termsthat quantify aspects of protein structure. These terms includesolvent accessibility, main-chain and side-chain dihedral angles,and secondary structure. In a relational database, the informationis stored in tables with columns holding the different termsand rows holding the different entries for the terms. The differentrelational base tables store the information about the proteincoordinate set, the different chains in the protein, the aminoacid residues and ligands, the atomic coordinates, the saltbridges, the hydrogen bonds, the disulphide bridges and theclose tertiary contacts. The database was established underORACLE management system. Enquiries are constructed in ORACLEusing SQL (structured query language) which is simple to useand alleviates the need for extensive computer programs. A singletable can be searched for entries that meet various criteria,e.g. all protein solved to better than a given resolution. Thepower of the database occurs when several tables, or the entriesin a single table, are cross-correlated. For example the dihedralangles of proline in the fourth position in an -helix in highresolution structures can be rapidly obtained. The structuraldatabase provides a powerful tool to obtain empirical rulesabout protein conformation. This database of protein structuresis part of a joint project between Birkbeck College and LeedsUniversity to establish an integrated data resource of proteinsequences and structures (ISIS) that encodes the complex patternsof residues and coordinates that define protein conformation.The entire data resource (ISIS) will provide a system to guideall areas of protein modelling including structure prediction,site-directed mutagenesis and de novo protein design. The availabilityof ISIS is described in the paper.     

The application of hydrogen bonding analysis in X-ray crystallography to help orientate asparagine, glutamine and histidine side chains

Protein X-ray crystallography produces an electron density mapthat rarely detects individual hydrogen atoms or distinguishesbetween carbon, nitrogen and oxygen atoms in the electron density.This makes it difficult to orientate the side chains of Asn,Gln and His, which appear symmetrical in the electron density;their orientation is usually judged on the basis of hydrogenbonding. Based on the observation that almost all buried donorsand acceptors are satisfied, we have developed a simple algorithmto compare the alternative conformations of these residues and,where possible, identify the most favourable. In a cross-sectionof protein structures we found a few side chains (15.0% of Asnand Gln and 9.9% of His) which would be more favourable in thealternative orientation. We have also found that this proportionrises slightly with worsening resolution.     

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.     

Stereochemistry of the N-glycosylation sites in glycoproteins

The stereochemical features displayed by the N-glycosidic linkagein crystalline N-linked glycoproteins are analyzed. From thestatistical analysis of 44 different glycosylation sites belongingto 26 glycoproteins of the Brookhaven Protein Data Bank, a meanstandard geometry for the GlcNAc moiety, along with a rationalizationof its confornia-tional behavior, can be proposed. As for theglycopeptide linkage, the distribution of observed conformationshas been analyzed on the basis of molecular mechanics calculations.The rotamer distribution of the Asn side chains conforms tothat observed on non-glycosylated structures, and it agreeswith the pattern of flexible conformations gathered from NMRmeasurements. In characterizing the protein-glycan interactions,some hydrogen bonds occur. Stacking between the amphiphilicmoiety of the glycan and some surrounding aromatic, or at leasthydrophobic, amino acid residues is also found. When lookingat the secondary structure of the glycosylated peptide, only25% of the glycosylation sites correspond to situations whereAsn is located at the top of a ß-turn. Other typesof secondary structure exist which fulfil the spatial requirementof having the glycan exposed at the surface of the protein.These data can be compared with the most recent studies on thepeptide conformation which would be required for glycosylation.     

Alignment of protein sequences using secondary structure: a modified dynamic programming method

A method for comparison of protein sequences based on theirprimary and secondary structure is described. Protein sequencesare annotated with predicted secondary structures (using a modifiedChou and Fasman method). Two lettered code sequences are generated(Xx, where X is the amino acid and x is its annotated secondarystructure). Sequences are compared with a dynamic programmingmethod (STRALIGN) that includes a similarity matrix for boththe amino acids and secondary structures. The similarity valuefor each paired two-lettered code is a linear combination ofsimilarity values for the paired amino acids and their annotatedsecondary structures. The method has been applied to eight globinproteins (28 pairs) for which the X-ray structure is known.For protein pairs with high primary sequence similarity (>45%),STRALIGN alignment is identical to that obtained by a dynamicprogramming method using only primary sequence information.However, alignment of protein pairs with lower primary sequencesimilarity improves significantly with the addition of secondarystructure annotation. Alignment of the pair with the least primarysequence similarity of 16% was improved from 0 to 37% ‘correct’alignment using this method. In addition, STRALIGN was successfullyapplied to seven pairs of distantly related cytochrome c proteins,and three pairs of distantly related picornavirus proteins.     

Increasing thermal stability of subtilisin from mutations suggested by strongly interacting side-chain clusters

In this paper we present for seven subtilisin structures a systematiccomparison of densely packed side-group clusters (defined asan ensemble of side chains with extensive internal atomic contactsas compared with those made with the surrounding protein environmentand measured relative to the maximum possible for each residuetype). Spatially consistent clusters are observed at structurallyequivalent positions in the proteins, as revealed by carefulmultiple superpositioning of the respective backbone atoms.The clusters are positioned at strategic loop-connecting sitesnear the protein surfaces. The residues within consistent clustersdisplaying extensive association show varying conservation atstructurally equivalent alignment sites. Suggestions for residuesubstitutions, as observed over the seven tertiary structures,were taken from the cluster positions and were shown to be consistentwith a number of point mutations in one of the seven structures(savinase) that result in increased thermal stability.     

Understanding the relationship between the primary structure of proteins and their amyloidogenic propensity: clues from inclusion body formation

Amyloid formation is dependent to a considerable extent on the amino acid sequence of the protein. The present study delineates certain sequence-dependent features that are correlated with amyloidogenic propensity. The analyses indicate that amyloid formation is favored by lower thermostability and increased half-life of the protein. There seems to be a certain degree of bias in the composition of order-promoting amino acids in the case of amyloidogenic proteins. Based on these parameters, a prediction function for the amyloidogenic propensity of proteins has been created. The prediction function has been found to rationalize the reported effect of certain mutations on amyloid formation. It seems that a higher sheet propensity of residues that constitute the first seven residues of a helical structure in a protein might increase the propensity for a helix to sheet transition in that region under denaturing conditions.     

Amino acid sequence templates derived from recurrent turn motifs in proteins: critical evaluation of their predictive power

Amino acid sequence patterns suggested to characterize specificrecurrent turn conformations in proteins are tested as to theirpredictive power in a database containing 75 proteins of knownstructure. Many of these patterns are found to be associatedwith local structures that differ from the motifs originallyused to derive them. It is therefore concluded that, while theycould be useful for improving predictions made by other methods,their stand-alone predictive power is poor. The issue of derivingand validating consensus sequence patterns for use in proteinstructure prediction is raised.     

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.     

The effect of experimental resolution on the performance of knowledge-based discriminatory functions for protein structure selection

The key to an accurate method of protein structure prediction is the development of an effective discriminatory function. Knowledge-based discriminatory functions extract parameters from statistical analysis of experimentally determined protein structures. We assess how the quality of the protein structures used for compiling statistics affects the performance of a residue-specific all-atom probability discriminatory function (RAPDF). We find that the discriminatory power correlates with the quality of the structural dataset on which the RAPDF is parameterized in a statistically significant manner. The overrepresentation of unfavorable contacts in the low-resolution and NMR structures contributes to the major errors in the compilation of the conditional probabilities. Such errors weaken the discriminatory power of the function, especially when decoy conformations also contain considerable numbers of unfavorable contacts. This indicates that using high-resolution structural datasets after filtering out unfavorable contacts can improve the performance of knowledge-based discriminatory functions.     

An analysis of structural instances of low complexity sequence segments

Amino acid sequence databases contain many low complexity, compositionallybiased sequence segments. However, only a limited number ofrelatively short instances of these segments occur in proteinsof known structure. An analysis is presented of structural instancesof these low complexity sequence segments in the BrookhavenProtein Data Bank with regard to preferences for sequence composition,secondary structural conformation and the local atomic environment.The complexity varies almost linearly with segment length, reflectingthe absence of very long, low complexity segments in the structuraldatabase. The low complexity segments identified are not disorderedand have temperature factors which are generally the same asthe rest of the protein. It is observed that these segmentsare predominantly exposed and either helical or coiled, in excessof what would be expected by chance. Secondary structure predictionmethods perform well in correctly predicting those low complexitysegments which are helical but poorly in correctly predictingsegments that are strands.