Constructing ensembles for intrinsically disordered proteins

The relatively flat energy landscapes associated with intrinsically disordered proteins makes modeling these systems especially problematic. A comprehensive model for these proteins requires one to build an ensemble consisting of a finite collection of structures, and their corresponding relative stabilities, which adequately capture the range of accessible states of the protein. In this regard, methods that use computational techniques to interpret experimental data in terms of such ensembles are an essential part of the modeling process. In this review, we critically assess the advantages and limitations of current techniques and discuss new methods for the validation of these ensembles.     

Temperature effects on the hydrodynamic radius of the intrinsically disordered N‐terminal region of the p53 protein

Intrinsically disordered proteins (IDPs) are often characterized in terms of the hydrodynamic radius, R_h. The R_h of IDPs are known to depend on fractional proline content and net charge, where increased numbers of proline residues and increased net charge cause larger R_h. Though sequence and charge effects on the R_h of IDPs have been studied, the temperature sensitivity has been noted only briefly. Reported here are R_h measurements in the temperature range of 5–75°C for the intrinsically disordered N‐terminal region of the p53 protein, p53(1–93). Of note, the R_h of this protein fragment was highly sensitive to temperature, decreasing from 35 Å at 5°C to 26 Å at 75°C. Computer generated simulations of conformationally dynamic and disordered polypeptide chains were performed to provide a hypothesis for the heat‐induced compaction of p53(1–93) structure, which was opposite to the heat‐induced increase in R_h observed for a model folded protein. The simulations demonstrated that heat caused R_h to trend toward statistical coil values for both proteins, indicating that the effects of heat on p53(1–93) structure could be interpreted as thermal denaturation. The simulation data also predicted that proline content contributed minimally to the native R_h of p53(1–93), which was confirmed by measuring R_h for a substitution variant that had all 22 proline residues changed for glycine. Proteins 2014; 82:668–678. © 2013 Wiley Periodicals, Inc.     

Unusual biophysics of intrinsically disordered proteins

Research of a past decade and a half leaves no doubt that complete understanding of protein functionality requires close consideration of the fact that many functional proteins do not have well-folded structures. These intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered protein regions (IDPRs) are highly abundant in nature and play a number of crucial roles in a living cell. Their functions, which are typically associated with a wide range of intermolecular interactions where IDPs possess remarkable binding promiscuity, complement functional repertoire of ordered proteins. All this requires a close attention to the peculiarities of biophysics of these proteins. In this review, some key biophysical features of IDPs are covered. In addition to the peculiar sequence characteristics of IDPs these biophysical features include sequential, structural, and spatiotemporal heterogeneity of IDPs; their rough and relatively flat energy landscapes; their ability to undergo both induced folding and induced unfolding; the ability to interact specifically with structurally unrelated partners; the ability to gain different structures at binding to different partners; and the ability to keep essential amount of disorder even in the bound form. IDPs are also characterized by the “turned-out” response to the changes in their environment, where they gain some structure under conditions resulting in denaturation or even unfolding of ordered proteins. It is proposed that the heterogeneous spatiotemporal structure of IDPs/IDPRs can be described as a set of foldons, inducible foldons, semi-foldons, non-foldons, and unfoldons. They may lose their function when folded, and activation of some IDPs is associated with the awaking of the dormant disorder. It is possible that IDPs represent the “edge of chaos” systems which operate in a region between order and complete randomness or chaos, where the complexity is maximal. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.     

Length-dependent compaction of intrinsically disordered proteins

This work investigates the effect of chain length on the degree of compaction of intrinsically disordered proteins (IDPs). The three main IDP types, native coil (NC), pre-molten globule (PMG) and molten globule (MG), are compared by means of a compaction index (CI) normalized for chain length. The results point out a strong variability of compactness as a function of chain length within each group, with larger proteins populating more compact states. While qualitative sequence features are responsible for the main differences among groups, chain length seems to have an unspecific effect modulating the extent of compaction within each group. The results are consistent with a cooperative character of the weak interactions responsible for chain collapse.     

Cold stability of intrinsically disordered proteins

Contrary to globular proteins, intrinsically disordered proteins (IDPs) lack a folded structure and they do not lose solubility at elevated temperatures. Although this should also be true at low temperatures, cold stability of IDPs has not been addressed in any scientific work so far. As direct characterization of cold-denaturation is difficult, we approached the problem through a freezing-induced loss-of-function model of globular-disordered functional protein pairs (m-calpain-calpastatin, tubulin-Map2c, Hsp90-ERD14). Our results affirm that in contrast with globular proteins IDPs are resistant to cold treatment. The theoretical and functional aspects of this observation are discussed.     

Molecular dynamics simulation of intrinsically disordered proteins

Intrinsically disordered proteins are biomolecules that do not have a definite 3D structure; therefore, their dynamical simulation cannot start from a known list of atomistic positions, such as a Protein Data Bank file. We describe a method to start a computer simulation of these proteins. The first step of the procedure is the creation of a multi-rod configuration of the molecule, derived from its primary sequence. This structure is dynamically evolved in vacuo until its gyration radius reaches the experimental average value; at this point solvent molecules, in explicit or implicit implementation, are added to the protein and a regular molecular dynamics simulation follows. We have applied this procedure to the simulation of tau, one of the largest totally disordered proteins.     

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.     

Protein kinases phosphorylate long disordered regions in intrinsically disordered proteins

Phosphorylation is a major post‐translational modification that plays a central role in signaling pathways. Protein kinases phosphorylate substrates (phosphoproteins) by adding phosphate at Ser/Thr or Tyr residues (phosphosites). A large amount of data identifying and describing phosphosites in phosphoproteins has been reported but the specificity of phosphorylation is not fully resolved. In this report, data of kinase‐substrate pairs identified by the Kinase‐Interacting Substrate Screening (KISS) method were used to analyze phosphosites in intrinsically disordered regions (IDRs) of intrinsically disordered proteins. We compared phosphorylated and nonphosphorylated IDRs and found that the phosphorylated IDRs were significantly longer than nonphosphorylated IDRs. The phosphorylated IDR is often the longest IDR (71%) in a phosphoprotein when only a single phosphosite exists in the IDR, and when the phosphoprotein has multiple phosphosites in an IDR(s), the phosphosites are primarily localized in a single IDR (78%) and this IDR is usually the longest one (81%). We constructed a stochastic model of phosphorylation to estimate the effect of IDR length. The model that accounted for IDR length produced more realistic results when compared with a model that excluded the IDR length. We propose that the IDR length is a significant determinant for locating kinase phosphorylation sites in phosphoproteins.     

HA-detected experiments for the backbone assignment of intrinsically disordered proteins

We propose a new alpha proton detection based approach for the sequential assignment of natively unfolded proteins. The proposed protocol superimposes on following features: HA-detection (1) enables assignment of natively unfolded proteins at any pH, i.e., it is not sensitive to rapid chemical exchange undergoing in natively unfolded proteins even at moderately high pH. (2) It allows straightforward assignment of proline-rich polypeptides without additional proline-customized experiments. (3) It offers more streamlined and less ambiguous assignment based on solely intraresidual ¹⁵N(i)-¹³C′(i)-H^α(i) (or ¹⁵N(i)-¹³C^α(i)-H^α(i)) and sequential ¹⁵N(i + 1)-¹³C′(i)-H^α(i) (or ¹⁵N(i + 1)-¹³C^α(i)-H^α(i)) correlation experiments together with efficient use of chemical shifts of ¹⁵N and ¹³C′ nuclei, which show smaller dependence on residue type. We have tested the proposed protocol on two proteins, small globular 56-residue GB1, and highly disordered, proline-rich 47-residue fifth repeat of EspF_U. Using the proposed approach, we were able to assign 90% of ¹H^α, ¹³C^α, ¹³C′, ¹⁵N chemical shifts in EspF_U. We reckon that the HA-detection based strategy will be very useful in the assignment of natively unfolded proline-rich proteins or polypeptide chains.     

Binding cavities and druggability of intrinsically disordered proteins

To assess the potential of intrinsically disordered proteins (IDPs) as drug design targets, we have analyzed the ligand-binding cavities of two datasets of IDPs (containing 37 and 16 entries, respectively) and compared their properties with those of conventional ordered (folded) proteins. IDPs were predicted to possess more binding cavity than ordered proteins at similar length, supporting the proposed advantage of IDPs economizing genome and protein resources. The cavity number has a wide distribution within each conformation ensemble for IDPs. The geometries of the cavities of IDPs differ from the cavities of ordered proteins, for example, the cavities of IDPs have larger surface areas and volumes, and are more likely to be composed of a single segment. The druggability of the cavities was examined, and the average druggable probability is estimated to be 9% for IDPs, which is almost twice that for ordered proteins (5%). Some IDPs with druggable cavities that are associated with diseases are listed. The optimism versus obstacles for drug design for IDPs is also briefly discussed.     

Context-dependent resistance to proteolysis of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs), also known as intrinsically unstructured proteins (IUPs), lack a well-defined 3D structure in vitro and, in some cases, also in vivo. Here, we discuss the question of proteolytic sensitivity of IDPs, with a view to better explaining their in vivo characteristics. After an initial assessment of the status of IDPs in vivo, we briefly survey the intracellular proteolytic systems. Subsequently, we discuss the evidence for IDPs being inherently sensitive to proteolysis. Such sensitivity would not, however, result in enhanced degradation if the protease-sensitive sites were sequestered. Accordingly, IDP access to and degradation by the proteasome, the major proteolytic complex within eukaryotic cells, are discussed in detail. The emerging picture appears to be that IDPs are inherently sensitive to proteasomal degradation along the lines of the "degradation by default" model. However, available data sets of intracellular protein half-lives suggest that intrinsic disorder does not imply a significantly shorter half-life. We assess the power of available systemic half-life measurements, but also discuss possible mechanisms that could protect IDPs from intracellular degradation. Finally, we discuss the relevance of the proteolytic sensitivity of IDPs to their function and evolution.     

Prediction of short loops in intrinsically disordered proteins

A new possibility of predicting short disordered regions (loops) at a small window size (three amino acid residues) by the FoldUnfold program is described. As demonstrated with the example of three G proteins, FoldUnfold predicted almost all existing loops at the positions fitting well the X-ray structural data. The loops predicted in the Ras p21 structure were classified into two types. The loops of the first type display high Debye-Waller factor values, characteristic of the so-called functional loops (flexible loops). The second-type loops had lower Debye-Waller factor values and, consequently, were regarded as the loops connecting secondary structure elements (rigid loops). Comparison of the results predicted by FoldUnfold with the predictions of other programs (PONDR, RONN, DisEMBL, PreLINK, IUPred, GlobPlot 2, and FoldIndex) demonstrated that the first program was much better in predicting the positions of short loops. FoldUnfold made it possible to solve the problem difficult for the other programs, that is, to determine the boundary between the ordered and disordered regions in proteins with a large fraction of disordered regions, exemplified by the ubiquitin-like domain. In particular, FoldUnfold predicted a boundary between the ordered and disordered regions at residues 30 and 31, whereas the other programs predicted the boundary in the range of 28–70 amino acid residues.     

Genome‐scale prediction of proteins with long intrinsically disordered regions

Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super‐fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time‐efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first‐of‐its‐kind large‐scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/ .Proteins 2014; 82:145–158. © 2013 Wiley Periodicals, Inc.     

Residue packing in globular and intrinsically disordered proteins

Intrinsically disordered proteins (IDPs)/regions do not have well‐defined secondary and tertiary structures, however, they are functional and it is critical to gain a deep understanding of their residue packing. The shape distributions methodology, which is usually utilized in pattern recognition, clustering, and classification studies in computer science, may be adopted to study the residue packing of the proteins. In this study, shape distributions of the globular proteins and IDPs were obtained to shed light on the residue packing of their structures. The shape feature that was used is the sphericity of tetrahedra obtained by Delaunay Tessellation of points of Cα coordinates. Then the sphericity probability distributions were compared by using Principal Component Analysis. This computational structural study shows that the set of IDPs constitute a more diverse set than the set of globular proteins in terms of the geometrical properties of their network structures.