Structured proteins and proteins with intrinsic disorder

Until recently, the point of view that the unique tertiary structure is necessary for protein function has prevailed. However, recent data have demonstrated that many cell proteins do not possess such structure in isolation, although displaying a distinct function under physiological conditions. These proteins were named the naturally, or intrinsically, disordered proteins. The fraction of intrinsically disordered regions in such proteins may vary from several amino acid residues to a completely unordered sequence of several tens or even several hundreds of residues. The main distinction of these proteins from structured (globular) proteins is that they have no unique tertiary structure in isolation and acquire it only upon interaction with their partners. The conformation of these proteins in a complex is determined not only by their own amino acid sequence (as is typical of structured, or globular, proteins) but also by the interacting partner. This review discusses the structure-function relationships in structured and intrinsically disordered proteins. The intricateness of this problem and the possible ways to solve it are illustrated by the example of the EF1A elongation factor family.     

Electric charge balance mechanism of extended soluble proteins

Extended proteins such as calmodulin and troponin C have two globular terminal domains linked by a central region that is exposed to water and often acts as a function-regulating element. The mechanisms that stabilize the tertiary structure of extended proteins appear to differ greatly from those of globular proteins. Identifying such differences in physical properties of amino acid sequences between extended proteins and globular proteins can provide clues useful for identification of extended proteins from complete genomes including orphan sequences. In the present study, we examined the structure and amino acid sequence of extended proteins. We found that extended proteins have a large net electric charge, high charge density, and an even balance of charge between the terminal domains, indicating that electrostatic interaction is a dominant factor in stabilization of extended proteins. Additionally, the central domain exposed to water contained many amphiphilic residues. Extended proteins can be identified from these physical properties of the tertiary structure, which can be deduced from the amino acid sequence. Analysis of physical properties of amino acid sequences can provide clues to the mechanism of protein folding. Also, structural changes in extended proteins may be caused by formation of molecular complexes. Long-range effects of electrostatic interactions also appear to play important roles in structural changes of extended proteins.     

Sequence patterns associated with disordered regions in proteins

The relationship between amino acid sequence and intrinsic disorder in proteins is investigated. Two databases, one of disordered proteins and the other of globular proteins, are analyzed and compared in order to extract simple sequence patterns of a few amino acids or amino acid properties that characterize disordered segments. It is found that a number of reliable, nonrandom associations exists. In particular, two types of patterns appear to be recurrent: a proline-rich pattern and a (positively or negatively) charged pattern. These results indicate that local sequence information can determine disordered regions in proteins. The derived patterns provide some insights into the physical reasons for disordered structures. They should also be helpful in improving currently available prediction methods.     

A comparative study of the relationship between protein structure and beta-aggregation in globular and intrinsically disordered proteins

A growing number of proteins are being identified that are biologically active though intrinsically disordered, in sharp contrast with the classic notion that proteins require a well-defined globular structure in order to be functional. At the same time recent work showed that aggregation and amyloidosis are initiated in amino acid sequences that have specific physico-chemical properties in terms of secondary structure propensities, hydrophobicity and charge. In intrinsically disordered proteins (IDPs) such sequences would be almost exclusively solvent-exposed and therefore cause serious solubility problems. Further, some IDPs such as the human prion protein, synuclein and Tau protein are related to major protein conformational diseases. However, this scenario contrasts with the large number of unstructured proteins identified, especially in higher eukaryotes, and the fact that the solubility of these proteins is often particularly good. We have used the algorithm TANGO to compare the beta aggregation tendency of a set of globular proteins derived from SCOP and a set of 296 experimentally verified, non-redundant IDPs but also with a set of IDPs predicted by the algorithms DisEMBL and GlobPlot. Our analysis shows that the beta-aggregation propensity of all-alpha, all-beta and mixed alpha/beta globular proteins as well as membrane-associated proteins is fairly similar. This illustrates firstly that globular structures possess an appreciable amount of structural frustration and secondly that beta-aggregation is not determined by hydrophobicity and beta-sheet propensity alone. We also show that globular proteins contain almost three times as much aggregation nucleating regions as IDPs and that the formation of highly structured globular proteins comes at the cost of a higher beta-aggregation propensity because both structure and aggregation obey very similar physico-chemical constraints. Finally, we discuss the fact that although IDPs have a much lower aggregation propensity than globular proteins, this does not necessarily mean that they have a lower potential for amyloidosis.     

Serine/arginine-rich splicing factors belong to a class of intrinsically disordered proteins

Serine/arginine-rich (SR) splicing factors play an important role in constitutive and alternative splicing as well as during several steps of RNA metabolism. Despite the wealth of functional information about SR proteins accumulated to-date, structural knowledge about the members of this family is very limited. To gain a better insight into structure-function relationships of SR proteins, we performed extensive sequence analysis of SR protein family members and combined it with ordered/disordered structure predictions. We found that SR proteins have properties characteristic of intrinsically disordered (ID) proteins. The amino acid composition and sequence complexity of SR proteins were very similar to those of the disordered protein regions. More detailed analysis showed that the SR proteins, and their RS domains in particular, are enriched in the disorder-promoting residues and are depleted in the order-promoting residues as compared to the entire human proteome. Moreover, disorder predictions indicated that RS domains of SR proteins were completely unstructured. Two different classification methods, the charge-hydropathy measure and the cumulative distribution function (CDF) of the disorder scores, were in agreement with each other, and they both strongly predicted members of the SR protein family to be disordered. This study emphasizes the importance of the disordered structure for several functions of SR proteins, such as for spliceosome assembly and for interaction with multiple partners. In addition, it demonstrates the usefulness of order/disorder predictions for inferring protein structure from sequence.     

Sequence periodicity and secondary structure propensity in model proteins

We explore the question of whether local effects (originating from the amino acids intrinsic secondary structure propensities) or nonlocal effects (reflecting the sequence of amino acids as a whole) play a larger role in determining the fold of globular proteins. Earlier circular dichroism studies have shown that the pattern of polar, non polar amino acids (nonlocal effect) dominates over the amino acid intrinsic propensity (local effect) in determining the secondary structure of oligomeric peptides. In this article, we present a coarse grained computational model that allows us to quantitatively estimate the role of local and nonlocal factors in determining both the secondary and tertiary structure of small, globular proteins. The amino acid intrinsic secondary structure propensity is modeled by a dihedral potential term. This dihedral potential is parametrized to match with experimental measurements of secondary structure propensity. Similarly, the magnitude of the attraction between hydrophobic residues is parametrized to match the experimental transfer free energies of hydrophobic amino acids. Under these parametrization conditions, we systematically explore the degree of frustration a given polar, non polar pattern can tolerate when the secondary structure intrinsic propensities are in opposition to it. When the parameters are in the biophysically relevant range, we observe that the fold of small, globular proteins is determined by the pattern of polar, non polar amino acids regardless of their instrinsic secondary structure propensities. Our simulations shed new light on previous observations that tertiary interactions are more influential in determining protein structure than secondary structure propensity. The fact that this can be inferred using a simple polymer model that lacks most of the biochemical details points to the fundamental importance of binary patterning in governing folding.     

Markov models of amino acid substitution to study proteins with intrinsically disordered regions

Background

Intrinsically disordered proteins (IDPs) or proteins with disordered regions (IDRs) do not have a well-defined tertiary structure, but perform a multitude of functions, often relying on their native disorder to achieve the binding flexibility through changing to alternative conformations. Intrinsic disorder is frequently found in all three kingdoms of life, and may occur in short stretches or span whole proteins. To date most studies contrasting the differences between ordered and disordered proteins focused on simple summary statistics. Here, we propose an evolutionary approach to study IDPs, and contrast patterns specific to ordered protein regions and the corresponding IDRs.

Results

Two empirical Markov models of amino acid substitutions were estimated, based on a large set of multiple sequence alignments with experimentally verified annotations of disordered regions from the DisProt database of IDPs. We applied new methods to detect differences in Markovian evolution and evolutionary rates between IDRs and the corresponding ordered protein regions. Further, we investigated the distribution of IDPs among functional categories, biochemical pathways and their preponderance to contain tandem repeats.

Conclusions

We find significant differences in the evolution between ordered and disordered regions of proteins. Most importantly we find that disorder promoting amino acids are more conserved in IDRs, indicating that in some cases not only amino acid composition but the specific sequence is important for function. This conjecture is also reinforced by the observation that for of our data set IDRs evolve more slowly than the ordered parts of the proteins, while we still support the common view that IDRs in general evolve more quickly. The improvement in model fit indicates a possible improvement for various types of analyses e.g. de novo disorder prediction using a phylogenetic Hidden Markov Model based on our matrices showed a performance similar to other disorder predictors.     

Disorder predictors also predict backbone dynamics for a family of disordered proteins

Several algorithms have been developed that use amino acid sequences to predict whether or not a protein or a region of a protein is disordered. These algorithms make accurate predictions for disordered regions that are 30 amino acids or longer, but it is unclear whether the predictions can be directly related to the backbone dynamics of individual amino acid residues. The nuclear Overhauser effect between the amide nitrogen and hydrogen (NHNOE) provides an unambiguous measure of backbone dynamics at single residue resolution and is an excellent tool for characterizing the dynamic behavior of disordered proteins. In this report, we show that the NHNOE values for several members of a family of disordered proteins are highly correlated with the output from three popular algorithms used to predict disordered regions from amino acid sequence. This is the first test between an experimental measure of residue specific backbone dynamics and disorder predictions. The results suggest that some disorder predictors can accurately estimate the backbone dynamics of individual amino acids in a long disordered region.     

Prediction of Protein Binding Regions in Disordered Proteins

Many disordered proteins function via binding to a structured partner and undergo a disorder-to-order transition. The coupled folding and binding can confer several functional advantages such as the precise control of binding specificity without increased affinity. Additionally, the inherent flexibility allows the binding site to adopt various conformations and to bind to multiple partners. These features explain the prevalence of such binding elements in signaling and regulatory processes. In this work, we report ANCHOR, a method for the prediction of disordered binding regions. ANCHOR relies on the pairwise energy estimation approach that is the basis of IUPred, a previous general disorder prediction method. In order to predict disordered binding regions, we seek to identify segments that are in disordered regions, cannot form enough favorable intrachain interactions to fold on their own, and are likely to gain stabilizing energy by interacting with a globular protein partner. The performance of ANCHOR was found to be largely independent from the amino acid composition and adopted secondary structure. Longer binding sites generally were predicted to be segmented, in agreement with available experimentally characterized examples. Scanning several hundred proteomes showed that the occurrence of disordered binding sites increased with the complexity of the organisms even compared to disordered regions in general. Furthermore, the length distribution of binding sites was different from disordered protein regions in general and was dominated by shorter segments. These results underline the importance of disordered proteins and protein segments in establishing new binding regions. Due to their specific biophysical properties, disordered binding sites generally carry a robust sequence signal, and this signal is efficiently captured by our method. Through its generality, ANCHOR opens new ways to study the essential functional sites of disordered proteins.     

The unfoldomics decade: an update on intrinsically disordered proteins

Background

Our first predictor of protein disorder was published just over a decade ago in the Proceedings of the IEEE International Conference on Neural Networks (Romero P, Obradovic Z, Kissinger C, Villafranca JE, Dunker AK (1997) Identifying disordered regions in proteins from amino acid sequence. Proceedings of the IEEE International Conference on Neural Networks, 1: 90–95). By now more than twenty other laboratory groups have joined the efforts to improve the prediction of protein disorder. While the various prediction methodologies used for protein intrinsic disorder resemble those methodologies used for secondary structure prediction, the two types of structures are entirely different. For example, the two structural classes have very different dynamic properties, with the irregular secondary structure class being much less mobile than the disorder class. The prediction of secondary structure has been useful. On the other hand, the prediction of intrinsic disorder has been revolutionary, leading to major modifications of the more than 100 year-old views relating protein structure and function. Experimentalists have been providing evidence over many decades that some proteins lack fixed structure or are disordered (or unfolded) under physiological conditions. In addition, experimentalists are also showing that, for many proteins, their functions depend on the unstructured rather than structured state; such results are in marked contrast to the greater than hundred year old views such as the lock and key hypothesis. Despite extensive data on many important examples, including disease-associated proteins, the importance of disorder for protein function has been largely ignored. Indeed, to our knowledge, current biochemistry books don't present even one acknowledged example of a disorder-dependent function, even though some reports of disorder-dependent functions are more than 50 years old. The results from genome-wide predictions of intrinsic disorder and the results from other bioinformatics studies of intrinsic disorder are demanding attention for these proteins.

Results

Disorder prediction has been important for showing that the relatively few experimentally characterized examples are members of a very large collection of related disordered proteins that are wide-spread over all three domains of life. Many significant biological functions are now known to depend directly on, or are importantly associated with, the unfolded or partially folded state. Here our goal is to review the key discoveries and to weave these discoveries together to support novel approaches for understanding sequence-function relationships.

Conclusion

Intrinsically disordered protein is common across the three domains of life, but especially common among the eukaryotic proteomes. Signaling sequences and sites of posttranslational modifications are frequently, or very likely most often, located within regions of intrinsic disorder. Disorder-to-order transitions are coupled with the adoption of different structures with different partners. Also, the flexibility of intrinsic disorder helps different disordered regions to bind to a common binding site on a common partner. Such capacity for binding diversity plays important roles in both protein-protein interaction networks and likely also in gene regulation networks. Such disorder-based signaling is further modulated in multicellular eukaryotes by alternative splicing, for which such splicing events map to regions of disorder much more often than to regions of structure. Associating alternative splicing with disorder rather than structure alleviates theoretical and experimentally observed problems associated with the folding of different length, isomeric amino acid sequences. The combination of disorder and alternative splicing is proposed to provide a mechanism for easily "trying out" different signaling pathways, thereby providing the mechanism for generating signaling diversity and enabling the evolution of cell differentiation and multicellularity. Finally, several recent small molecules of interest as potential drugs have been shown to act by blocking protein-protein interactions based on intrinsic disorder of one of the partners. Study of these examples has led to a new approach for drug discovery, and bioinformatics analysis of the human proteome suggests that various disease-associated proteins are very rich in such disorder-based drug discovery targets.

     

Sequence complexity of disordered protein

Intrinsic disorder refers to segments or to whole proteins that fail to self-fold into fixed 3D structure, with such disorder sometimes existing in the native state. Here we report data on the relationships among intrinsic disorder, sequence complexity as measured by Shannon's entropy, and amino acid composition. Intrinsic disorder identified in protein crystal structures, and by nuclear magnetic resonance, circular dichroism, and prediction from amino acid sequence, all exhibit similar complexity distributions that are shifted to lower values compared to, but significantly overlapping with, the distribution for ordered proteins. Compared to sequences from ordered proteins, these variously characterized intrinsically disordered segments and proteins, and also a collection of low-complexity sequences, typically have obviously higher levels of protein-specific subsets of the following amino acids: R, K, E, P, and S, and lower levels of subsets of the following: C, W, Y, I, and V. The Swiss Protein database of sequences exhibits significantly higher amounts of both low-complexity and predicted-to-be-disordered segments as compared to a non-redundant set of sequences from the Protein Data Bank, providing additional data that nature is richer in disordered and low-complexity segments compared to the commonness of these features in the set of structurally characterized proteins.     

The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins

The structural stability of a protein requires a large number of interresidue interactions. The energetic contribution of these can be approximated by low-resolution force fields extracted from known structures, based on observed amino acid pairing frequencies. The summation of such energies, however, cannot be carried out for proteins whose structure is not known or for intrinsically unstructured proteins. To overcome these limitations, we present a novel method for estimating the total pairwise interaction energy, based on a quadratic form in the amino acid composition of the protein. This approach is validated by the good correlation of the estimated and actual energies of proteins of known structure and by a clear separation of folded and disordered proteins in the energy space it defines. As the novel algorithm has not been trained on unstructured proteins, it substantiates the concept of protein disorder, i.e. that the inability to form a well-defined 3D structure is an intrinsic property of many proteins and protein domains. This property is encoded in their sequence, because their biased amino acid composition does not allow sufficient stabilizing interactions to form. By limiting the calculation to a predefined sequential neighborhood, the algorithm was turned into a position-specific scoring scheme that characterizes the tendency of a given amino acid to fall into an ordered or disordered region. This application we term IUPred and compare its performance with three generally accepted predictors, PONDR VL3H, DISOPRED2 and GlobPlot on a database of disordered proteins.     

Local sequence patterns of hydrophobicity and solvent accessibility in soluble globular proteins

We examined the variation in the solvent accessibility and hydrophobicity of the amino acids along the sequences of 58 soluble globular proteins with known tertiary structure. We found that there is a significant tendency for the accessibilities to run in clusters along the sequence but that the hydrophobicities are distributed without such nonrandom clusters. Theseresults suggest severe limitations on the power of sequence analysis tools that use average hydrophobicity scores of overlapping subsequences to predict accessibility.     

Prediction of unfolded segments in a protein sequence based on amino acid composition

MOTIVATION: Partially and wholly unstructured proteins have now been identified in all kingdoms of life--more commonly in eukaryotic organisms. This intrinsic disorder is related to certain critical functions. Apart from their fundamental interest, unstructured regions in proteins may prevent crystallization. Therefore, the prediction of disordered regions is an important aspect for the understanding of protein function, but may also help to devise genetic constructs. RESULTS: In this paper we present a computational tool for the detection of unstructured regions in proteins based on two properties of unfolded fragments: (1) disordered regions have a biased composition and (2) they usually contain either small or no hydrophobic clusters. In order to quantify these two facts we first calculate the amino acid distributions in structured and unstructured regions. Using this distribution, we calculate for a given sequence fragment the probability to be part of either a structured or an unstructured region. For each amino acid, the distance to the nearest hydrophobic cluster is also computed. Using these three values along a protein sequence allows us to predict unstructured regions, with very simple rules. This method requires only the primary sequence, and no multiple alignment, which makes it an adequate method for orphan proteins. AVAILABILITY: http://genomics.eu.org/     

Solution structure of native proteins with irregular folds from Raman optical activity

Raman optical activity (ROA) spectra have been measured for the proteins hen phosvitin, yeast invertase, bovine alpha-casein, soybean Bowman-Birk protease inhibitor, and rabbit Cd(7)-metallothionein, all of which have irregular folds in the native state. The results show that ROA is able to distinguish between two types of disorder. Specifically, invertase, alpha-casein, the Bowman-Birk inhibitor, and metallothionein appear to possess a "static" type of disorder similar to that in disordered states of poly(L-lysine) and poly(L-glutamic acid); whereas phosvitin appears to possess a more "dynamic" type of disorder similar to that in reduced (unfolded) lysozyme and ribonuclease A and also in molten globule protein states. In the delimiting cases, static disorder corresponds to that found in loops and turns within native proteins with well-defined tertiary folds that contain sequences of residues with fixed but nonrepetitive phi,psi angles; and dynamic disorder corresponds to that envisaged for the model random coil in which there is a distribution of Ramachandran phi,psi angles for each amino acid residue, giving rise to an ensemble of interconverting conformers. In both cases there is a propensity for the phi,psi angles to correspond to the alpha, beta and poly(L-proline) II (PPII) regions of the Ramachandran surface, as in native proteins with well-defined tertiary folds. Our results suggest that, with the exception of invertase and metallothionein, an important conformational element present in the polypeptide and protein states supporting the static type of disorder is that of the PPII helix. Long sequences of relatively unconstrained PPII helix, as in alpha-casein, may impart a plastic (rheomorphic) character to the structure.     

Topology-based modeling of intrinsically disordered proteins: balancing intrinsic folding and intermolecular interactions

Coupled binding and folding is frequently involved in specific recognition of so-called intrinsically disordered proteins (IDPs), a newly recognized class of proteins that rely on a lack of stable tertiary fold for function. Here, we exploit topology-based Gō-like modeling as an effective tool for the mechanism of IDP recognition within the theoretical framework of minimally frustrated energy landscape. Importantly, substantial differences exist between IDPs and globular proteins in both amino acid sequence and binding interface characteristics. We demonstrate that established Gō-like models designed for folded proteins tend to over-estimate the level of residual structures in unbound IDPs, whereas under-estimating the strength of intermolecular interactions. Such systematic biases have important consequences in the predicted mechanism of interaction. A strategy is proposed to recalibrate topology-derived models to balance intrinsic folding propensities and intermolecular interactions, based on experimental knowledge of the overall residual structure level and binding affinity. Applied to pKID/KIX, the calibrated Gō-like model predicts a dominant multistep sequential pathway for binding-induced folding of pKID that is initiated by KIX binding via the C-terminus in disordered conformations, followed by binding and folding of the rest of C-terminal helix and finally the N-terminal helix. This novel mechanism is consistent with key observations derived from a recent NMR titration and relaxation dispersion study and provides a molecular-level interpretation of kinetic rates derived from dispersion curve analysis. These case studies provide important insight into the applicability and potential pitfalls of topology-based modeling for studying IDP folding and interaction in general.     

Effect of pH on the stability and structure of yeast hexokinase A. Acidic amino acid residues in the cleft region are critical for the opening and the closing of the structure

pH and salts have a marked effect on the stability, structure, and function of many globular proteins due to their ability to influence the electrostatic interactions. In this work, calorimetry, CD, and fluorescence studies have been carried out to understand the pH-dependent conformational changes of the two-domain protein yeast hexokinase A. In conjunction with the crystal structural data available, the present results have enabled the complete characterization and analysis of the pH-dependent conformational changes of the enzyme that have strong implications in understanding its structure-function relationship. The calorimetric profiles show a single thermal transition in the acidic pH range, whereas two independent transitions were observed in the alkaline pH range, suggesting the structural merger of the domains at the acidic pH. Comparison of the thermal transitions at pH 8.5 studied by different techniques suggests that the first transition corresponds to the smaller domain, and the second transition corresponds to the larger domain. The acid-denatured state of hexokinase A has high secondary structure content with little or no tertiary interactions and binds to the hydrophobic dye 8-anilinonaphthalene-1-sulfonic acid, suggesting that it is a molten globule-like state, whereas the alkali-denatured state is less structured than the acid-denatured state but more structured than the urea-denatured state, suggestive of a premolten globule-like state. Structural analysis using the published hexokinase B structure as well as the hexokinase A structure with the revised amino acid sequence in conjunction with the results obtained by us suggests that the ionization state of the acidic residues at the active site could regulate domain movements that are responsible for the opening and the closure of the cleft between the two domains and in turn affect the structure and function of the enzyme.     

Influence of medium- and long-range interactions in different folding types of globular proteins

Recognition of protein fold from amino acid sequence is a challenging task. The structure and stability of proteins from different fold are mainly dictated by inter-residue interactions. In our earlier work, we have successfully used the medium- and long-range contacts for predicting the protein folding rates, discriminating globular and membrane proteins and for distinguishing protein structural classes. In this work, we analyze the role of inter-residue interactions in commonly occurring folds of globular proteins in order to understand their folding mechanisms. In the medium-range contacts, the globin fold and four-helical bundle proteins have more contacts than that of DNA-RNA fold although they all belong to all-alpha class. In long-range contacts, only the ribonuclease fold prefers 4-10 range and the other folding types prefer the range 21-30 in alpha/beta class proteins. Further, the preferred residues and residue pairs influenced by these different folds are discussed. The information about the preference of medium- and long-range contacts exhibited by the 20 amino acid residues can be effectively used to predict the folding type of each protein.     

Distribution of amino acid residues in the primary protein structure

The amino acid composition and sequence in primary structure of 180 proteins have been studied. It is shown that the distribution of amino acid residues is near to a random one, i.e. it is determined by the amino acid composition. The ratio between statistical and unique character of protein primary structures has been discussed. The amino acid sequence is suggested to be unique in fibrous proteins. In contrast the amino acid sequence in globular proteins is a statistical one. The statistical character of amino acids distribution in globular proteins explains the possibility of sensible text generation under the frame shift mutations, deletions and insertions.