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.     

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.     

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.     

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.     

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.     

ncIDP-assign: a SPARKY extension for the effective NMR assignment of intrinsically disordered proteins

We describe here the ncIDP-assign extension for the popular NMR assignment program SPARKY, which aids in the sequence-specific resonance assignment of intrinsically disordered proteins (IDPs). The assignment plugin greatly facilitates the effective matching of a set of connected resonances to the correct position in the sequence by making use of IDP random coil chemical shifts. AVAILABILITY: The ncIDP-assign extension is available at http://www.protein-nmr.org/.     

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.     

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.     

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.

     

Analytical methods for structural ensembles and dynamics of intrinsically disordered proteins

Intrinsically disordered proteins, proteins that do not have a well-defined three-dimensional structure, make up a significant proportion of our proteome and are particularly prevalent in signaling and regulation. Although their importance has been realized for two decades, there is a lack of high-resolution experimental data. Molecular dynamics simulations have been crucial in reaching our current understanding of the dynamical structural ensemble sampled by intrinsically disordered proteins. In this review, we discuss enhanced sampling simulation methods that are particularly suitable to characterize the structural ensemble, along with examples of applications and limitations. The dynamics within the ensemble can be rigorously analyzed using Markov state models. We discuss recent developments that make Markov state modeling a viable approach for studying intrinsically disordered proteins. Finally, we briefly discuss challenges and future directions when applying molecular dynamics simulations to study intrinsically disordered proteins.     

New 13C-detected experiments for the assignment of intrinsically disordered proteins

NMR assignment of intrinsically disordered proteins (IDPs) by conventional HN-detected methods is hampered by the small dispersion of the amide protons chemical shifts and exchange broadening of amide proton signals. Therefore several alternative assignment strategies have been proposed in the last years. Attempting to seize that dispersion of ¹³C′ and ¹⁵N chemical shifts holds even in IDPs, we recently proposed two ¹³C-detected experiments to directly correlate the chemical shifts of two consecutive ¹³C′–¹⁵N groups in proteins, i.e. without mediation of other nuclei. Main drawback of these experiments is the interruption of the connection at prolines. Here we present new ¹³C-detected experiments to correlate consecutive ¹³C′–¹⁵N groups in IDPs, hacacoNcaNCO and hacaCOncaNCO, that overcome this limitation. Moreover, the experiments provide recognition of glycine residues, thereby facilitating the assignment process.     

Random coil chemical shift for intrinsically disordered proteins: effects of temperature and pH

Secondary chemical shift analysis is the main NMR method for detection of transiently formed secondary structure in intrinsically disordered proteins. The quality of the secondary chemical shifts is dependent on an appropriate choice of random coil chemical shifts. We report random coil chemical shifts and sequence correction factors determined for a GGXGG peptide series following the approach of Schwarzinger et al. (J Am Chem Soc 123(13):2970–2978, 2001). The chemical shifts are determined at neutral pH in order to match the conditions of most studies of intrinsically disordered proteins. Temperature has a non-negligible effect on the ¹³C random coil chemical shifts, so temperature coefficients are reported for the random coil chemical shifts to allow extrapolation to other temperatures. The pH dependence of the histidine random coil chemical shifts is investigated in a titration series, which allows the accurate random coil chemical shifts to be obtained at any pH. By correcting the random coil chemical shifts for the effects of temperature and pH, systematic biases of the secondary chemical shifts are minimized, which will improve the reliability of detection of transient secondary structure in disordered proteins.     

Small-angle scattering studies of intrinsically disordered proteins and their complexes

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