Contributions of residue pairing to beta-sheet formation: conservation and covariation of amino acid residue pairs on antiparallel beta-strands

Computational Identification and Design of Complementary β-Strand Sequences

The ß-sheet is a regular secondary structure element which consists of linear segments called ß-strands. They are involved in many important biological processes, and some are known to be related to serious diseases such as neurologic disorders and amyloidosis. The self-assembly of ß-sheet peptides also has practical applications in material sciences since they can be building blocks of repeated nanostructures. Therefore, computational algorithms for identification of ß-sheet formation can offer useful insight into the mechanism of disease-prone protein segments and the construction of biocompatible nanomaterials. Despite the recent advances in structure-based methods for the assessment of atomic interactions, identifying amyloidogenic peptides has proven to be extremely difficult since they are structurally very flexible. Thus, an alternative strategy is required to describe ß-sheet formation. It has been hypothesized and observed that there are certain amino acid propensities between ß-strand pairs. Based on this hypothesis, a database search algorithm, B-SIDER, is developed for the identification and design of ß-sheet forming sequences. Given a target sequence, the algorithm identifies exact or partial matches from the structure database and constructs a position-specific score matrix. The score matrix can be utilized to design novel sequences that can form a ß-sheet specifically with the target.

B-SIDER: Computational Algorithm for the Design of Complementary β-Sheet Sequences

The β-sheet is an element of protein secondary structure, and intra-/intermolecular β-sheet interactions play pivotal roles in biological regulatory processes including scaffolding, transporting, and oligomerization. In nature, a β-sheet formation is tightly regulated because dysregulated β-stacking often leads to severe diseases such as Alzheimer's, Parkinson's, systemic amyloidosis, or diabetes. Thus, the identification of intrinsic β-sheet-forming propensities can provide valuable insight into protein designs for the development of novel therapeutics. However, structure-based design methods may not be generally applicable to such amyloidogenic peptides mainly owing to high structural plasticity and complexity. Therefore, an alternative design strategy based on complementary sequence information is of significant importance. Herein, we developed a database search method called β-Stacking Interaction DEsign for Reciprocity (B-SIDER) for the design of complementary β-strands. This method makes use of the structural database information and generates target-specific score matrices. The discriminatory power of the B-SIDER score function was tested on representative amyloidogenic peptide substructures against a sequence-based score matrix (PASTA 2.0) and two popular ab initio protein design score functions (Rosetta and FoldX). B-SIDER is able to distinguish wild-type amyloidogenic β-strands as favored interactions in a more consistent manner than other methods. B-SIDER was prospectively applied to the design of complementary β-strands for a splitGFP scaffold. Three variants were identified to have stronger interactions than the original sequence selected through a directed evolution, emitting higher fluorescence intensities. Our results indicate that B-SIDER can be applicable to the design of other β-strands, assisting in the development of therapeutics against disease-related amyloidogenic peptides.

Cross-strand disulfides in the hydrogen bonding site of antiparallel β-sheet (aCSDhs): Forbidden disulfides that are highly strained, easily broken

Some disulfide bonds perform important structural roles in proteins, but another group has functional roles via redox reactions. Forbidden disulfides are stressed disulfides found in recognizable protein contexts, which currently constitute more than 10% of all disulfides in the PDB. They likely have functional redox roles and constitute a major subset of all redox-active disulfides. The torsional strain of forbidden disulfides is typically higher than for structural disulfides, but not so high as to render them immediately susceptible to reduction under physionormal conditions. Previously we characterized the most abundant forbidden disulfide in the Protein Data Bank, the aCSDn: a canonical motif in which disulfide-bonded cysteine residues are positioned directly opposite each other on adjacent anti-parallel β-strands such that the backbone hydrogen-bonded moieties are directed away from each other. Here we perform a similar analysis for the aCSDh, a less common motif in which the opposed cysteine residues are backbone hydrogen bonded. Oxidation of two Cys in this context places significant strain on the protein system, with the β-chains tilting toward each other to allow disulfide formation. Only left-handed aCSDh conformations are compatible with the inherent right-handed twist of β-sheets. aCSDhs tend to be more highly strained than aCSDns, particularly when both hydrogen bonds are formed. We discuss characterized roles of aCSDh motifs in proteins of the dataset, which include catalytic disulfides in ribonucleotide reductase and ahpC peroxidase as well as a redox-active disulfide in P1 lysozyme, involved in a major conformation change. The dataset also includes many binding proteins.

Conserved Binding Regions Provide the Clue for Peptide-Based Vaccine Development: A Chemical Perspective

Synthetic peptides have become invaluable biomedical research and medicinal chemistry tools for studying functional roles, i.e., binding or proteolytic activity, naturally-occurring regions’ immunogenicity in proteins and developing therapeutic agents and vaccines. Synthetic peptides can mimic protein sites; their structure and function can be easily modulated by specific amino acid replacement. They have major advantages, i.e., they are cheap, easily-produced and chemically stable, lack infectious and secondary adverse reactions and can induce immune responses via T- and B-cell epitopes. Our group has previously shown that using synthetic peptides and adopting a functional approach has led to identifying Plasmodium falciparumconserved regions binding to host cells. Conserved high activity binding peptides’ (cHABPs) physicochemical, structural and immunological characteristics have been taken into account for properly modifying and converting them into highly immunogenic, protection-inducing peptides (mHABPs) in the experimental Aotus monkey model. This article describes stereo–electron and topochemical characteristics regarding major histocompatibility complex (MHC)-mHABP-T-cell receptor (TCR) complex formation. Some mHABPs in this complex inducing long-lasting, protective immunity have been named immune protection-inducing protein structures (IMPIPS), forming the subunit components in chemically synthesized vaccines. This manuscript summarizes this particular field and adds our recent findings concerning intramolecular interactions (H-bonds or π-interactions) enabling proper IMPIPS structure as well as the peripheral flanking residues (PFR) to stabilize the MHCII-IMPIPS-TCR interaction, aimed at inducing long-lasting, protective immunological memory.

Protein β-sheet prediction using an efficient dynamic programming algorithm

Predicting the β-sheet structure of a protein is one of the most important intermediate steps towards the identification of its tertiary structure. However, it is regarded as the primary bottleneck due to the presence of non-local interactions between several discontinuous regions in β-sheets. To achieve reliable long-range interactions, a promising approach is to enumerate and rank all β-sheet conformations for a given protein and find the one with the highest score. The problem with this solution is that the search space of the problem grows exponentially with respect to the number of β-strands. Additionally, brute-force calculation in this conformational space leads to dealing with a combinatorial explosion problem with intractable computational complexity. The main contribution of this paper is to generate and search the space of the problem efficiently to reduce the time complexity of the problem. To achieve this, two tree structures, called sheet-tree and grouping-tree, are proposed. They model the search space by breaking it into sub-problems. Then, an advanced dynamic programming is proposed that stores the intermediate results, avoids repetitive calculation by repeatedly uses them efficiently in successive steps and reduces the space of the problem by removing those intermediate results that will no longer be required in later steps. As a consequence, the following contributions have been made. Firstly, more accurate β-sheet structures are found by searching all possible conformations, and secondly, the time complexity of the problem is reduced by searching the space of the problem efficiently which makes the proposed method applicable to predict β-sheet structures with high number of β-strands. Experimental results on the BetaSheet916 dataset showed significant improvements of the proposed method in both execution time and the prediction accuracy in comparison with the state-of-the-art β-sheet structure prediction methods Moreover, we investigate the effect of different contact map predictors on the performance of the proposed method using BetaSheet1452 dataset. The source code is available at http://www.conceptsgate.com/BetaTop.rar.

Efficient dynamic programming algorithm with prior knowledge for protein β-strand alignment

One of the main tasks towards the prediction of protein β-sheet structure is to predict the native alignment of β-strands. The alignment of two β-strands defines similar regions that may reflect functional, structural, or evolutionary relationships between them. Therefore, any improvement in β-strands alignment not only reduces the computational search space but also improves β-sheet structure prediction accuracy. To define the alignment scores, previous studies utilized predicted residue-residue contacts (contact maps). However, there are two serious problems using them. First, the precision of contact map prediction techniques, especially for long-range contacts (i.e., β-residues), is still not satisfactory. Second, the residue-residue contact predictors usually utilize general properties of amino acids and disregard the structural features of β-residues. In this paper, we consider β-structure information, which is estimated from protein β-sheet data sets, as alignment scores. However, the predicted contact maps are used as a prior knowledge about residues. They are used for strengthening or weakening the alignment scores in our algorithm. Thus, we can utilize both β-residues and β-structure information in alignment of β-strands. The structure of dynamic programming of the alignment algorithm is changed in order to work with our prior knowledge. Moreover, the Four Russians method is applied to the proposed alignment algorithm in order to reduce the time complexity of the problem. For evaluating the proposed method, we applied it to the state-of-the-art β-sheet structure prediction methods. The experimental results on the BetaSheet916 data set showed significant improvements in the execution time, the accuracy of β-strands' alignment and consequently β-sheet structure prediction accuracy. The results are available at http://conceptsgate.com/BetaSheet.

β-Bulges: extensive structural analyses of β-sheets irregularities

β-Sheets are quite frequent in protein structures and are stabilized by regular main-chain hydrogen bond patterns. Irregularities in β-sheets, named β-bulges, are distorted regions between two consecutive hydrogen bonds. They disrupt the classical alternation of side chain direction and can alter the directionality of β-strands. They are implicated in protein-protein interactions and are introduced to avoid β-strand aggregation. Five different types of β-bulges are defined. Previous studies on β-bulges were performed on a limited number of protein structures or one specific family. These studies evoked a potential conservation during evolution. In this work, we analyze the β-bulge distribution and conservation in terms of local backbone conformations and amino acid composition. Our dataset consists of 66 times more β-bulges than the last systematic study (Chan et al. Protein Science 1993, 2:1574-1590). Novel amino acid preferences are underlined and local structure conformations are highlighted by the use of a structural alphabet. We observed that β-bulges are preferably localized at the N- and C-termini of β-strands, but contrary to the earlier studies, no significant conservation of β-bulges was observed among structural homologues. Displacement of β-bulges along the sequence was also investigated by Molecular Dynamics simulations.

Statistical Analysis of Terminal Extensions of Protein β-Strand Pairs

The long-range interactions, required to the accurate predictions of tertiary structures of β-sheet-containing proteins, are still difficult to simulate. To remedy this problem and to facilitate β-sheet structure predictions, many efforts have been made by computational methods. However, known efforts on β-sheets mainly focus on interresidue contacts or amino acid partners. In this study, to go one step further, we studied β-sheets on the strand level, in which a statistical analysis was made on the terminal extensions of paired β-strands. In most cases, the two paired β-strands have different lengths, and terminal extensions exist. The terminal extensions are the extended part of the paired strands besides the common paired part. However, we found that the best pairing required a terminal alignment, and β-strands tend to pair to make bigger common parts. As a result, 96.97%  of β-strand pairs have a ratio of 25% of the paired common part to the whole length. Also 94.26% and 95.98%  of β-strand pairs have a ratio of 40% of the paired common part to the length of the two β-strands, respectively. Interstrand register predictions by searching interacting β-strands from several alternative offsets should comply with this rule to reduce the computational searching space to improve the performances of algorithms.

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure

MOTIVATION

The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in β-sheets. The strong constraints and prior knowledge associated with β-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM.

RESULTS

Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for β-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input.

AVAILABILITY

http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/

A hierarchical order within protein structures underlies large separations between strands in β-sheets

Protein β-sheets often involve nonlocal interactions between parts of the polypeptide chain that are separated by hundreds of residues, raising the question of how these nonlocal contacts form. A recent study of the smallest β-sheets found that their formation was not driven by signals hidden in the primary sequence. Instead, the strands in these sheets were either local in sequence, or, when separated by large sequential distances, the intervening residues were found to fold into compact modules that anchored distant parts of the chain in close spatial proximity. Here, we examine larger β-sheets to investigate the extensibility of this principle. From an analysis of the β-sheets in a nonredundant protein dataset, we find that a highly ordered hierarchical relationship exists in the intervening structure between nonlocal β-strands. This observation is almost universal: virtually all β-sheets, no matter their complexity, appear to adopt an antiparallel model to manage the nonlocal aspects of their assembly, one where the chain, having left the vicinity of an unfinished β-sheet, retraces its steps via the same route to complete the initial sheet. Exceptions typically involve unstructured regions at chain termini. Moreover, an analysis of the residues involved in nonlocal crossstrand interactions did not produce any evidence of a signal hidden in the sequence that might direct long-range interactions. These results build on those reported for the smallest sheets, suggesting that sheet formation is either local in sequence or local in space following prior folding events that anchor disparate parts of the chain in close proximity.

COVARIATION ANALYSIS OF LOCAL AMINO ACID SEQUENCES IN RECURRENT PROTEIN LOCAL STRUCTURES

Local structural information is supposed to be frequently encoded in local amino acid sequences. Previous research only indicated that some local structure positions have specific residue preferences in some particular local structures. However, correlated pairwise replacements for interacting residues in recurrent local structural motifs from unrelated proteins have not been studied systematically. We introduced a new method fusing statistical covariation analysis and local structure-based alignment. Systematic analysis of structure-based multiple alignments of recurrent local structures from unrelated proteins in representative subset of Protein Databank indicates that covarying residue pairs with statistical significance exist in local structural motifs, in particular β-turns and helix caps. These residue pairs are mostly linked through polar functional groups with direct or indirect hydrogen bonding. Hydrophobic interaction is also a major factor in constraining pairwise amino acid residue replacement in recurrent local structures. We also found correlated residue pairs that are not clearly linked with through-space interactions. The physical constrains underlying these covariations are less clear. Overall, covarying residue pairs with statistical significance exist in local structures from unrelated proteins. The existence of sequence covariations in local structural motifs from unrelated proteins indicates that many relics of local relations are still retained in the tertiary structures after protein folding. It supports the notion that some local structural information is encoded in local sequences and the local structural codes could play important roles in determining native state protein folding topology.

Studies on the rules of β-strand alignment in a protein β-sheet structure

To further disclose the underlying mechanisms of protein β-sheet formation, studies were made on the rules of β-strands alignment forming β-sheet structure using statistical and machine learning approaches. Firstly, statistical analysis was performed on the sum of β-strands between each β-strand pairs in protein sequences. The results showed a propensity of near-neighbor pairing (or called "first come first pair") in the β-strand pairs. Secondly, based on the same dataset, the pairwise cross-combinations of real β-strand pairs and four pseudo-β-strand contained pairs were classified by support vector machine (SVM). A novel feature extracting approach was designed for classification using the average amino acid pairing encoding matrix (APEM). Analytical results of the classification indicated that a segment of β-strand had the ability to distinguish β-strands from segments of α-helix and coil. However, the result also showed that a β-strand was not strongly conserved to choose its real partner from all the alternative β-strand partners, which was corresponding with the ordination results of the statistical analysis each other. Thus, the rules of "first come first pair" propensity and the non-conservative ability to choose real partner, were possible important factors affecting the β-strands alignment forming β-sheet structures.

Improved sequence-based prediction of strand residues

Accurate identification of strand residues aids prediction and analysis of numerous structural and functional aspects of proteins. We propose a sequence-based predictor, BETArPRED, which improves prediction of strand residues and β-strand segments. BETArPRED uses a novel design that accepts strand residues predicted by SSpro and predicts the remaining positions utilizing a logistic regression classifier with nine custom-designed features. These are derived from the primary sequence, the secondary structure (SS) predicted by SSpro, PSIPRED and SPINE, and residue depth as predicted by RDpred. Our features utilize certain local (window-based) patterns in the predicted SS and combine information about the predicted SS and residue depth. BETArPRED is evaluated on 432 sequences that share low identity with the training chains, and on the CASP8 dataset. We compare BETArPRED with seven modern SS predictors, and the top-performing automated structure predictor in CASP8, the ZHANG-server. BETArPRED provides statistically significant improvements over each of the SS predictors; it improves prediction of strand residues and β-strands, and it finds β-strands that were missed by the other methods. When compared with the ZHANG-server, we improve predictions of strand segments and predict more actual strand residues, while the other predictor achieves higher rate of correct strand residue predictions when under-predicting them.

Tryptophan residues: scarce in proteins but strong stabilizers of β-hairpin peptides

Tryptophan plays important roles in protein stability and recognition despite its scarcity in proteins. Except as fluorescent groups, they have been used rarely in peptide design. Nevertheless, Trp residues were crucial for the stability of some designed minimal proteins. In 2000, Trp-Trp pairs were shown to contribute more than any other hydrophobic interaction to the stability of β-hairpin peptides. Since then, Trp-Trp pairs have emerged as a paradigm for the design of stable β-hairpins, such as the Trpzip peptides. Here, we analyze the nature of the stabilizing capacity of Trp-Trp pairs by reviewing the β-hairpin peptides containing Trp-Trp pairs described up to now, the spectroscopic features and geometry of the Trp-Trp pairs, and their use as binding sites in β-hairpin peptides. To complete the overview, we briefly go through the other relevant β-hairpin stabilizing Trp-non-Trp interactions and illustrate the use of Trp in the design of short peptides adopting α-helical and mixed α/β motifs. This review is of interest in the field of rational design of proteins, peptides, peptidomimetics, and biomaterials.

Bayesian models and algorithms for protein β-sheet prediction

Prediction of the 3D structure greatly benefits from the information related to secondary structure, solvent accessibility, and nonlocal contacts that stabilize a protein's structure. We address the problem of \beta-sheet prediction defined as the prediction of \beta--strand pairings, interaction types (parallel or antiparallel), and \beta-residue interactions (or contact maps). We introduce a Bayesian approach for proteins with six or less \beta-strands in which we model the conformational features in a probabilistic framework by combining the amino acid pairing potentials with a priori knowledge of \beta-strand organizations. To select the optimum \beta-sheet architecture, we significantly reduce the search space by heuristics that enforce the amino acid pairs with strong interaction potentials. In addition, we find the optimum pairwise alignment between \beta-strands using dynamic programming in which we allow any number of gaps in an alignment to model \beta-bulges more effectively. For proteins with more than six \beta-strands, we first compute \beta-strand pairings using the BetaPro method. Then, we compute gapped alignments of the paired \beta-strands and choose the interaction types and \beta--residue pairings with maximum alignment scores. We performed a 10-fold cross-validation experiment on the BetaSheet916 set and obtained significant improvements in the prediction accuracy.

Protein beta-sheet nucleation is driven by local modular formation

Despite its central role in the protein folding process, the specific mechanism(s) behind beta-sheet formation has yet to be determined. For example, whether the nucleation of beta-sheets, often containing strands separated in sequence by many residues, is local or not remains hotly debated. Here, we investigate the initial nucleation step of beta-sheet formation by performing an analysis of the smallest beta-sheets in a non-redundant dataset on the grounds that the smallest sheets, having undergone little growth after nucleation, will be enriched for nucleating characteristics. We find that the residue propensities are similar for small and large beta-sheets as are their interstrand pairing preferences, suggesting that nucleation is not primarily driven by specific residues or interacting pairs. Instead, an examination of the structural environments of the two-stranded sheets shows that virtually all of them are contained in single, compact structural modules, or when multiple modules are present, one or both of the chain termini are involved. We, therefore, find that beta-nucleation is a local phenomenon resulting either from sequential or topological proximity. We propose that beta-nucleation is a result of two opposite factors; that is, the relative rigidity of an associated folding module that holds two stretches of coil close together in topology coupled with sufficient chain flexibility that enables the stretches of coil to bring their backbones in close proximity. Our findings lend support to the hydrophobic zipper model of protein folding (Dill, K. A., Fiebig, K. M., and Chan, H. S. (1993) Proc. Natl. Acad. Sci. U.S.A. 90, 1942-1946). Implications for protein folding are discussed.

Analysis of loop boundaries using different local structure assignment methods

Loops connect regular secondary structures. In many instances, they are known to play important biological roles. Analysis and prediction of loop conformations depend directly on the definition of repetitive structures. Nonetheless, the secondary structure assignment methods (SSAMs) often lead to divergent assignments. In this study, we analyzed, both structure and sequence point of views, how the divergence between different SSAMs affect boundary definitions of loops connecting regular secondary structures. The analysis of SSAMs underlines that no clear consensus between the different SSAMs can be easily found. Because these latter greatly influence the loop boundary definitions, important variations are indeed observed, that is, capping positions are shifted between different SSAMs. On the other hand, our results show that the sequence information in these capping regions are more stable than expected, and, classical and equivalent sequence patterns were found for most of the SSAMs. This is, to our knowledge, the most exhaustive survey in this field as (i) various databank have been used leading to similar results without implication of protein redundancy and (ii) the first time various SSAMs have been used. This work hence gives new insights into the difficult question of assignment of repetitive structures and addresses the issue of loop boundaries definition. Although SSAMs give very different local structure assignments capping sequence patterns remain efficiently stable.

The interstrand amino acid pairs play a significant role in determining the parallel or antiparallel orientation of beta-strands

It is widely considered that it is not appropriate to treat beta-pairs in isolation, since other secondary structural models (such as helices, coils), protein topology and protein tertiary structures would limit beta-strand pairing. However, to understand the underlying mechanisms of beta-sheet formation, studies ought to be performed separately on more concrete aspects. In this study, we focus on the parallel or antiparallel orientation of beta-strands. First, statistical analysis was performed on the relative frequencies of the interstrand amino acid pairs within parallel and antiparallel beta-strands. Consequently, features were extracted by singular value decomposition from the statistical results. By using the support vector machine to distinguish the features extracted from the two types of beta-strands, high accuracy was achieved (up to 99.4%). This suggests that the interstrand amino acid pairs play a significant role in determining the parallel or antiparallel orientation of beta-strands. These results may provide useful information for developing other useful algorithms to examine to the beta-strand folding pathways, and could eventually lead to protein structure predictions.

Very short peptides with stable folds: building on the interrelationship of Trp/Trp, Trp/cation, and Trp/backbone-amide interaction geometries

By combining a favorable turn sequence with a turn flanking Trp/Trp interaction and a C-terminal H-bonding interaction between a backbone amide and an i-2 Trp ring, a particularly stable (DeltaG(U) > 7 kJ/mol) truncated hairpin, Ac-WI-(D-Pro-D-Asn)-KWTG-NH(2), results. In this construct and others with a W-(4-residue turn)-W motif in severely truncated hairpins, the C-terminal Trp is the edge residue in a well-defined face-to-edge (FtE) aryl/aryl interaction. Longer hairpins and those with six-residue turns retain the reversed "edge-to-face" (EtF) Trp/Trp geometry first observed for the trpzip peptides. Mutational studies suggest that the W-(4-residue turn)-W interaction provides at least 3 kJ/mol of stabilization in excess of that due to the greater beta-propensity of Trp. The pi-cation, and Trp/Gly-H(N) interactions have been defined. The latter can give rise to >3 ppm upfield shifts for the Gly-H(N) in -WX(n)G- units both in turns (n = 2) and at the C-termini (n = 1) of hairpins. Terminal YTG units result in somewhat smaller shifts (extrapolated to 2 ppm for 100% folding). In peptides with both the EtF and FtE W/W interaction geometries, Trp to Tyr mutations indicate that Trp is the preferred "face" residue in aryl/aryl pairings, presumably because of its greater pi basicity.

Folding by numbers: primary sequence statistics and their use in studying protein folding

The exponential growth over the past several decades in the quantity of both primary sequence data available and the number of protein structures determined has provided a wealth of information describing the relationship between protein primary sequence and tertiary structure. This growing repository of data has served as a prime source for statistical analysis, where underlying relationships between patterns of amino acids and protein structure can be uncovered. Here, we survey the main statistical approaches that have been used for identifying patterns within protein sequences, and discuss sequence pattern research as it relates to both secondary and tertiary protein structure. Limitations to statistical analyses are discussed, and a context for their role within the field of protein folding is given. We conclude by describing a novel statistical study of residue patterning in β-strands, which finds that hydrophobic (i,i+2) pairing in β-strands occurs more often than expected at locations near strand termini. Interpretations involving β-sheet nucleation and growth are discussed.

Understanding the mechanism of beta-sheet folding from a chemical and biological perspective

Perturbing the structure of the Pin1 WW domain, a 34-residue protein comprised of three beta-strands and two intervening loops has provided significant insight into the structural and energetic basis of beta-sheet folding. We will review our current perspective on how structure acquisition is influenced by the sequence, which determines local conformational propensities and mediates the hydrophobic effect, hydrogen bonding, and analogous intramolecular interactions. We have utilized both traditional site-directed mutagenesis and backbone mutagenesis approaches to alter the primary structure of this beta-sheet protein. Traditional site-directed mutagenesis experiments are excellent for altering side-chain structure, whereas amide-to-ester backbone mutagenesis experiments modify backbone-backbone hydrogen bonding capacity. The transition state structure associated with the folding of the Pin1 WW domain features a partially H-bonded, near-native reverse turn secondary structure in loop 1 that has little influence on thermodynamic stability. The thermodynamic stability of the Pin1 WW domain is largely determined by the formation of a small hydrophobic core and by the formation of desolvated backbone-backbone H-bonds enveloped by this hydrophobic core. Loop 1 engineering to the consensus five-residue beta-bulge-turn found in most WW domains or a four-residue beta-turn found in most beta-hairpins accelerates folding substantially relative to the six-residue turn found in the wild type Pin1 WW domain. Furthermore, the more efficient five- and four-residue reverse turns now contribute to the stability of the three-stranded beta-sheet. These insights have allowed the design of Pin1 WW domains that fold at rates that approach the theoretical speed limit of folding.

Exploring beta-sheet structure and interactions with chemical model systems

Beta-sheets consist of extended polypeptide strands (beta-strands) connected by a network of hydrogen bonds and occur widely in proteins. Although the importance of beta-sheets in the folded structures of proteins has long been recognized, there is a growing recognition of the importance of intermolecular interactions among beta-sheets. Intermolecular interactions between the hydrogen-bonding edges of beta-sheets constitute a fundamental form of biomolecular recognition (like DNA base pairing) and are involved protein quaternary structure, protein-protein interactions, and peptide and protein aggregation. The importance of beta-sheet interactions in biological processes makes them potential targets for intervention in diseases such as AIDS, cancer, and Alzheimer's disease. This Account describes my research group's use of chemical model systems to study the structure and interactions of beta-sheets. Chemical model systems provide an excellent vehicle with which to explore beta-sheets, because they are smaller, simpler, and easier to manipulate than proteins. Synthetic chemical models also provide the opportunity to control or modulate natural systems or to develop other useful applications and may eventually lead to new drugs with which to treat diseases. In our "artificial beta-sheets", molecular template and turn units are combined with peptides to mimic the structures of parallel and antiparallel beta-sheets. The templates and turn units form folded, hydrogen-bonded structures with the peptide groups and help prevent the formation of complex, ill-defined aggregates. Templates that duplicate the hydrogen-bonding pattern of one edge of a peptide beta-strand while blocking the other edge have proven particularly valuable in preventing aggregate formation and in promoting the formation of simple monomeric and dimeric structures. Artificial beta-sheets that present exposed hydrogen-bonding edges can form well-defined hydrogen-bonded dimers. Dimerization occurs readily in chloroform solutions but requires additional hydrophobic interactions to occur in aqueous solution. Interactions among the side chains, as well as hydrogen bonding among the main chains, are important in dimer formation. NMR studies of artificial beta-sheets have elucidated the importance of hydrogen-bonding complementarity, size complementarity, and chiral complementarity in these interactions. These pairing preferences demonstrate sequence selectivity in the molecular recognition between beta-sheets. These studies help illustrate the importance of intermolecular edge-to-edge interactions between beta-sheets in peptides and proteins. Ultimately, these model systems may lead to new ways of controlling beta-sheet interactions and treating diseases in which they are involved.

Beta-strand flipping and slipping triggered by turn replacement reveal the opportunistic nature of beta-strand pairing

We investigated how the register between adjacent beta-strands is specified using a series of mutants of the single-layer beta-sheet (SLB) in Borrelia OspA. The single-layer architecture of this system eliminates structural restraints imposed by a hydrophobic core, enabling us to address this question. A critical turn (turn 9/10) in the SLB was replaced with a segment with an intentional structural mismatch. Its crystal structure revealed a one-residue insertion into the central beta-strand (strand 9) of the SLB. This insertion triggered a surprisingly large-scale structural rearrangement: (i) the central strand (strand 9) was shifted by one residue, causing the strand to flip with respect to the adjacent beta-strands and thus completely disrupting the native side-chain contacts; (ii) the three-residue turn located on the opposite end of the beta-strand (turn 8/9) was pushed into its preceding beta-strand (strand 8); (iii) the register between strands 8 and 9 was shifted by three residues. Replacing the original sequence for turn 8/9 with a stronger turn motif restored the original strand register but still with a flipped beta-strand 9. The stability differences of these distinct structures were surprisingly small, consistent with an energy landscape where multiple low-energy states with different beta-sheet configurations exist. The observed conformations can be rationalized in terms of maximizing the number of backbone H-bonds. These results suggest that adjacent beta-strands "stick" through the use of factors that are not highly sequence specific and that beta-strands could slide back and forth relatively easily in the absence of external elements such as turns and tertiary packing.

Ranking the factors that contribute to protein β-sheet folding

The formation of beta-sheet domains in proteins involves five energetically important factors: the formation of networks of hydrogen bonds and hydrophobic faces, and the residue propensities, or preferences, to be found at the edges of the beta-sheet, to adopt the extended conformation, and to make contact with other residues. These relative energy contributions define a potential energy function. Here, we show how optimizing this potential energy function reveals the formation of hydrophobic faces as the utmost factor. The potential energy function was optimized to minimize the Z-scores of the native topologies among the exhaustive sets of over 400 different beta-sheets. These results corroborate with experimental data that showed the environment of a protein is an important modulator of beta-sheet folding. The contact propensities were found to be the least important, which could explain the poor predictive power of beta-strand alignment methods based on pair-wise contact matrices.

Cyclic modular beta-sheets

The development of peptide beta-hairpins is problematic, because folding depends on the amino acid sequence and changes to the sequence can significantly decrease folding. Robust beta-hairpins that can tolerate such changes are attractive tools for studying interactions involving protein beta-sheets and developing inhibitors of these interactions. This paper introduces a new class of peptide models of protein beta-sheets that addresses the problem of separating folding from the sequence. These model beta-sheets are macrocyclic peptides that fold in water to present a pentapeptide beta-strand along one edge; the other edge contains the tripeptide beta-strand mimic Hao [JACS 2000, 122, 7654] and two additional amino acids. The pentapeptide and Hao-containing peptide strands are connected by two delta-linked ornithine (deltaOrn) turns [JACS 2003, 125, 876]. Each deltaOrn turn contains a free alpha-amino group that permits the linking of individual modules to form divalent beta-sheets. These "cyclic modular beta-sheets" are synthesized by standard solid-phase peptide synthesis of a linear precursor followed by solution-phase cyclization. Eight cyclic modular beta-sheets 1a-1h containing sequences based on beta-amyloid and macrophage inflammatory protein 2 were synthesized and characterized by 1H NMR. Linked cyclic modular beta-sheet 2, which contains two modules of 1b, was also synthesized and characterized. 1H NMR studies show downfield alpha-proton chemical shifts, deltaOrn delta-proton magnetic anisotropy, and NOE cross-peaks that establish all compounds but 1c and 1g to be moderately or well folded into a conformation that resembles a beta-sheet. Pulsed-field gradient NMR diffusion experiments show little or no self-association at low ( Collapse

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MESH Headings

• Amino Acid Sequence
• Amyloid beta-Peptides/chemistry
• Chemokine CXCL2
• Chromatography, High Pressure Liquid
• Hydrogen Bonding
• Magnetic Resonance Spectroscopy
• Molecular Conformation
• Molecular Sequence Data
• Monokines/chemistry
• Oligopeptides/chemical synthesis
• Ornithine/chemistry
• Peptides, Cyclic/chemistry
• Protein Folding
• Protein Structure, Secondary
• Water/chemistry

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Grants

• R01 GM049076-12 NIGMS NIH HHS
• 5T32 CA 009054 NCI NIH HHS
• R01 GM049076-13 NIGMS NIH HHS
• T32 CA009054 NCI NIH HHS
• GM 49076 NIGMS NIH HHS
• R01 GM049076 NIGMS NIH HHS
• 5T15 LM 07443 NLM NIH HHS
• R01 GM049076-11 NIGMS NIH HHS
• T15 LM007443 NLM NIH HHS

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Affiliation(s)

R. Jeremy Woods Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920
Justin O. Brower Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920
Elena Castellanos Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920
Mehrnoosh Hashemzadeh Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920
Omid Khakshoor Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920
Wade A. Russu Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920
James S. Nowick Department of Chemistry, University of California, Irvine, Irvine, CA 92697-2025, Phone: 949-824-6091, FAX: 949-824-9920

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Hydrophobic surface burial is the major stability determinant of a flat, single-layer beta-sheet

Formation of a flat beta-sheet is a fundamental event in beta-sheet-mediated protein self-assembly. To investigate the contributions of various factors to the stability of flat beta-sheets, we performed extensive alanine-scanning mutagenesis experiments on the single-layer beta-sheet segment of Borrelia outer surface protein A (OspA). This beta-sheet segment consists of beta-strands with highly regular geometries that can serve as a building block for self-assembly. Our Ala-scanning approach is distinct from the conventional host-guest method, in that it introduces only conservative, truncation mutations that should minimize structural perturbation. Our results showed very weak correlation with experimental beta-sheet propensity scales, statistical beta-sheet propensity scales, or cross-strand pairwise correlations. In contrast, our data showed strong positive correlation with the change in buried non-polar surface area. Polar interactions including prominent Glu-Lys cross-strand pairs contribute marginally to the beta-sheet stability. These results were corroborated by results from additional non-Ala mutations. Taken together, these results demonstrate the dominant contribution of non-polar surface burial to flat beta-sheet stability even at solvent-exposed positions. The OspA single-layer beta-sheet achieves efficient hydrophobic surface burial without forming a hydrophobic core by a strategic placement of a variety of side-chains. These findings further suggest the importance of hydrophobic interactions within a beta-sheet layer in peptide self-assembly.

What I have learned by using chemical model systems to study biomolecular structure and interactions

Chemical model systems provide valuable insights into biomolecular structure and interactions by allowing researchers to simplify, isolate, and manipulate aspects of the complex molecular machinery of living systems. This perspective describes my laboratory's design, synthesis, and study of chemical model systems that fold and self-assemble like proteins and elucidates the insights that have come from studying these systems. Many of these studies have focused on protein beta-sheets, which exhibit fascinating intra- and intermolecular interactions and play important roles in protein folding, aggregation, and molecular recognition.

Sequence dependence of beta-hairpin structure: comparison of a salt bridge and an aromatic interaction

A comparison of the contributions and position dependence of cross-strand electrostatic and aromatic side-chain interactions to beta-sheet stability has been performed by using nuclear magnetic resonance in a well-folded beta-hairpin peptide of the general sequence XRTVXVdPGOXITQX. Phe-Phe and Glu-Lys pairs were varied at the internal and terminal non-hydrogen-bonded position, and the resulting stability was measured by the effects on alpha-hydrogen and aromatic hydrogen chemical shifts. It was determined that the introduction of a Phe-Phe pair resulted in a more folded peptide, regardless of position, and a more tightly folded core. Substitution of the Glu-Lys pair at the internal position results in a less folded peptide and increased fraying at the terminal residues. Upfield shifting of the aromatic hydrogens provided evidence for an edge-face aromatic interaction, regardless of position of the Phe-Phe pair. In peptides with two Phe-Phe pairs, substitution with Glu-Lys at either position resulted in a weakening of the aromatic interaction and a subsequent decrease in peptide stability. Thermal denaturation of the peptides containing Phe-Phe indicates that the aromatic interaction is enthalpically favored, whereas the folding of hairpins with cross-strand Glu-Lys pairs was less enthalpically favorable but entropically more favorable.

Sequence and structural analysis of cellular retinoic acid-binding proteins reveals a network of conserved hydrophobic interactions

Proteins in the intracellular lipid-binding protein (iLBP) family show remarkably high structural conservation despite their low-sequence identity. A multiple-sequence alignment using 52 sequences of iLBP family members revealed 15 fully conserved positions, with a disproportionately high number of these (n=7) located in the relatively small helical region. The conserved positions displayed high structural conservation based on comparisons of known iLBP crystal structures. It is striking that the beta-sheet domain had few conserved positions, despite its high structural conservation. This observation prompted us to analyze pair-wise interactions within the beta-sheet region to ask whether structural information was encoded in interacting amino acid pairs. We conducted this analysis on the iLBP family member, cellular retinoic acid-binding protein I (CRABP I), whose folding mechanism is under study in our laboratory. Indeed, an analysis based on a simple classification of hydrophobic and polar amino acids revealed a network of conserved interactions in CRABP I that cluster spatially, suggesting a possible nucleation site for folding. Significantly, a small number of residues participated in multiple conserved interactions, suggesting a key role for these sites in the structure and folding of CRABP I. The results presented here correlate well with available experimental evidence on folding of CRABPs and their family members and suggest future experiments. The analysis also shows the usefulness of considering pair-wise conservation based on a simple classification of amino acids, in analyzing sequences and structures to find common core regions among homologues.

Conservation and amyloid formation: a study of the gelsolin-like family

The mechanism through which globular proteins transform into amyloid fibrils is still not understood. Here we analyze the structure and sequence conservation to assess the differential stability of segments from two structurally related protein families: the amyloidogenic gelsolin-like and its structurally related cofilin-like. The two families belong to the actin depolymerizing proteins, with a central beta-sheet stacked between 2 and 4 alpha-helices. Although sequentially remote, the two families share regions of high and low conservation and stability. Our results show a highly conserved hydrophobic and aromatic cluster, located at a central buried beta-hairpin. The geometry of the aromatic residues with respect to each other is strictly conserved, suggesting involvement in strand registering and beta-sheet stabilization. Consistent with experiment, we find a region of weak conservation and stability at one of the exposed beta-strands (strand B in the gelsolin-like family). This region was recently found to be affected by a point mutation-mediated destabilization of the human gelsolin domain 2, which facilitates the first proteolytic event in the formation of the amyloidogenic fragment. Thus, both experimental and computational conservation analyses suggest that this unstable region may constitute a first step in amyloid formation. Our analysis uses a recently developed multiple-structure comparison algorithm in which molecules are aligned simultaneously.

Insights into the determinants of beta-sheet stability: 1H and 13C NMR conformational investigation of three-stranded antiparallel beta-sheet-forming peptides

In a previous study we designed a 20-residue peptide able to adopt a significant population of a three-stranded antiparallel beta-sheet in aqueous solution (de Alba et al. [1999]Protein Sci.8, 854-865). In order to better understand the factors contributing to beta-sheet folding and stability we designed and prepared nine variants of the parent peptide by substituting residues at selected positions in its strands. The ability of these peptides to form the target motif was assessed on the basis of NMR parameters, in particular NOE data and 13Calpha conformational shifts. The populations of the target beta-sheet motif were lower in the variants than in the parent peptide. Comparative analysis of the conformational behavior of the peptides showed that, as expected, strand residues with low intrinsic beta-sheet propensities greatly disfavor beta-sheet folding and that, as already found in other beta-sheet models, specific cross-strand side chain-side chain interactions contribute to beta-sheet stability. More interestingly, the performed analysis indicated that the destabilization effect of the unfavorable strand residues depends on their location at inner or edge strands, being larger at the latter. Moreover, in all the cases examined, favorable cross-strand side chain-side chain interactions were not strong enough to counterbalance the disfavoring effect of a poor beta-sheet-forming residue, such as Gly.

Identification of conserved residue patterns in small beta-barrel proteins

Our abilities to predict three-dimensional conformation of a polypeptide, given its amino acid sequence, remain limited despite advances in structure analysis. Analysis of structures and sequences of protein families with similar secondary structural elements, but varying topologies, might help in addressing this problem. We have studied the small beta-barrel class of proteins characterized by four strands (n = 4) and a shear number of 8 (S = 8) to understand the principles of barrel formation. Multiple alignments of the various protein sequences were generated for the analysis. Positional entropy, as a measure of residue conservation, indicated conservation of non-polar residues at the core positions. The presence of a type II beta-turn among the various barrel proteins considered was another strikingly invariant feature. A conserved glycyl-aspartyl dipeptide at the beta-turn appeared to be important in guiding the protein sequence into the barrel fold. Molecular dynamics simulations of the type II beta-turn peptide suggested that aspartate is a key residue in the folding of the protein sequence into the barrel. Our study suggests that the conserved type II beta-turn and the non-polar residues in the barrel core are crucial for the folding of the protein's primary sequence into the beta-barrel conformation.

Quantifying beta-sheet stability by phage display

The small immunoglobulin G (IgG)-binding protein GB1 is a favored model system for the study of individual residue contributions to the stability of beta-sheets. Nevertheless, only a few of the many possible combinations of mutations have been characterized, leaving many questions unanswered. In order to allow the simultaneous evaluation of libraries of mutants, we have adapted a phage-display method, called shotgun scanning. This method combines a binding (i.e. stability) selection with high-throughput sequence analysis. Relative folding free energies determined from GB1-phage sequence data agree well with published GB1 thermal stability studies, validating the use of phage display to conduct quantitative stability studies on GB1, and further suggesting that this method is generally applicable to mutational analysis of protein stability. Examination of residue pairing in our large collection of GB1 mutants indicates that specific side-chain-side-chain interactions are much less important to beta-sheet stability than individual residue contributions. The discrepancy between this observation and published studies can be traced to anomalous stability of the alanine-substituted GB1 variants typically used as reference states in double mutant-cycle analyses. Finally, the combination of large library sizes and a quantitative stability selection should allow phage-based "computation" to be applied to protein design problems.

Prediction of strand pairing in antiparallel and parallel beta-sheets using information theory

An information theory approach was developed to predict the alignment of interacting antiparallel and parallel beta-strands. Information scores were derived for the preference of a residue on a beta-strand to be opposite a sequence of residues on an adjacent beta-strand. These scores were used to predict the interstrand register of interacting beta-strands from 10 alternative offset positions either side of the experimentally observed beta-sheet register. The amino acid sequence of an internal beta-strand can be correctly aligned with two beta-strands in a fixed position either side of the strand in 45% of antiparallel and 48% of parallel arrangements. For comparison, when another beta-strand from a nonhomologous protein substitutes the internal beta-strand, the same register is predicted for only 24 and 36% of antiparallel and parallel arrangements. As expected, alignment of a single fixed strand with just a second beta-strand sequence was more difficult, and gave a correct register in 31 and 37% of antiparallel and parallel beta-pairs, respectively. These scores are 10% higher than for two randomly selected beta-strand sequences. In general, prediction accuracy was not improved by information tables that distinguished hydrogen-bonding patterns or beta-strand order. These results will contribute to predicting the arrangement of beta-strands in beta-pleated sheets and protein topology.