Advantages of proteins being disordered

The past decade has witnessed great advances in our understanding of protein structure‐function relationships in terms of the ubiquitous existence of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs). The structural disorder of IDPs/IDRs enables them to play essential functions that are complementary to those of ordered proteins. In addition, IDPs/IDRs are persistent in evolution. Therefore, they are expected to possess some advantages over ordered proteins. In this review, we summarize and survey nine possible advantages of IDPs/IDRs: economizing genome/protein resources, overcoming steric restrictions in binding, achieving high specificity with low affinity, increasing binding rate, facilitating posttranslational modifications, enabling flexible linkers, preventing aggregation, providing resistance to non‐native conditions, and allowing compatibility with more available sequences. Some potential advantages of IDPs/IDRs are not well understood and require both experimental and theoretical approaches to decipher. The connection with protein design is also briefly discussed.     

Targeting intrinsically disordered proteins in neurodegenerative and protein dysfunction diseases: another illustration of the D2 concept

Many biologically active proteins, which are usually called intrinsically disordered or natively unfolded proteins, lack stable tertiary and/or secondary structure under physiological conditions in vitro. Their functions complement the functional repertoire of ordered proteins, with intrinsically disordered proteins (IDPs) often being involved in regulation, signaling and control. Their amino acid sequences and compositions are very different from those of ordered proteins, making reliable identification of IDPs possible at the proteome level. IDPs are highly abundant in various human diseases, including neurodegeneration and other protein dysfunction maladies and, therefore, represent attractive novel drug targets. Some of the aspects of IDPs, as well as their roles in neurodegeneration and protein dysfunction diseases, are discussed in this article, together with the peculiarities of IDPs as potential drug targets.     

On the nature of cavities on protein surfaces: application to the identification of drug-binding sites

In this article we introduce a new method for the identification and the accurate characterization of protein surface cavities. The method is encoded in the program SCREEN (Surface Cavity REcognition and EvaluatioN). As a first test of the utility of our approach we used SCREEN to locate and analyze the surface cavities of a nonredundant set of 99 proteins cocrystallized with drugs. We find that this set of proteins has on average about 14 distinct cavities per protein. In all cases, a drug is bound at one (and sometimes more than one) of these cavities. Using cavity size alone as a criterion for predicting drug-binding sites yields a high balanced error rate of 15.7%, with only 71.7% coverage. Here we characterize each surface cavity by computing a comprehensive set of 408 physicochemical, structural, and geometric attributes. By applying modern machine learning techniques (Random Forests) we were able to develop a classifier that can identify drug-binding cavities with a balanced error rate of 7.2% and coverage of 88.9%. Only 18 of the 408 cavity attributes had a statistically significant role in the prediction. Of these 18 important attributes, almost all involved size and shape rather than physicochemical properties of the surface cavity. The implications of these results are discussed. A SCREEN Web server is available at http://interface.bioc.columbia.edu/screen.     

Features of molecular recognition of intrinsically disordered proteins via coupled folding and binding

The sequence–structure–function paradigm of proteins has been revolutionized by the discovery of intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). In contrast to traditional ordered proteins, IDPs/IDRs are unstructured under physiological conditions. The absence of well‐defined three‐dimensional structures in the free state of IDPs/IDRs is fundamental to their function. Folding upon binding is an important mode of molecular recognition for IDPs/IDRs. While great efforts have been devoted to investigating the complex structures and binding kinetics and affinities, our knowledge on the binding mechanisms of IDPs/IDRs remains very limited. Here, we review recent advances on the binding mechanisms of IDPs/IDRs. The structures and kinetic parameters of IDPs/IDRs can vary greatly, and the binding mechanisms can be highly dependent on the structural properties of IDPs/IDRs. IDPs/IDRs can employ various combinations of conformational selection and induced fit in a binding process, which can be templated by the target and/or encoded by the IDP/IDR. Further studies should provide deeper insights into the molecular recognition of IDPs/IDRs and enable the rational design of IDP/IDR binding mechanisms in the future.     

Protein folding and the order/disorder paradox

Most proteins encoded by the nuclear genome are synthesized in the cytoplasm and fold into precise 3D structures. During synthesis, the nascent polypeptide begins to fold as it traverses the large subunit of the ribosome and is assisted by molecular chaperones in attaining its precise folded/highly ordered state efficiently and in a biologically relevant timescale. Proteins that are misfolded are culled, re-routed, and marked by mechanisms such as ubiquitinylation for degradation ensuring strict quality control (QC). In addition to the highly ordered "globular" proteins, emerging evidence indicates that a large fraction of the proteome also comprises the so-called "Intrinsically Disordered Proteins" (IDPs). IDPs are proteins that lack rigid 3D structures and instead, exist as dynamic ensembles. The dynamic structures in the IDPs have many similarities with "normal" globular proteins such as the native (ordered), and non-native (molten globule, pre-molten globule, and coil-like) states seen during folding of "normal" globular proteins. However, unlike the case of the nascent globular proteins, IDPs evade being detected as "misfolded" and degraded by the cell's QC system. We refer to this paradox as the order/disorder paradox and postulate that the IDPs capitalize on their intrinsic promiscuity and ability to undergo disorder-to-order transitions upon binding to biological targets (coupled folding and binding) to escape the cell's surveillance machinery. Understanding the mechanism by which the IDPs evade the quality check has wide implications from protein folding to disease biology since the aggregation of misfolded proteins underlies several debilitating illnesses such as many neurodegenerative diseases and cancer.     

Mapping of ligand‐binding cavities in proteins

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand‐binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between‐species differences and flexibility upon ligand‐binding. The presented results show that information on ligand‐binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand‐binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of “orphan structures”, selection of protein structures for docking studies in structure‐based design, and identification of proteins for selectivity screens in drug design programs. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Intrinsically Disordered Proteins and Their Environment: Effects of Strong Denaturants, Temperature, pH, Counter Ions, Membranes, Binding Partners, Osmolytes, and Macromolecular Crowding

Intrinsically disordered proteins (IDPs) differ from “normal” ordered proteins at several levels, structural, functional and conformational. Amino acid biases characteristic for IDPs determine their structural variability and lack of rigid well-folded structure. This structural plasticity is necessary for the unique functional repertoire of IDPs, which is complementary to the catalytic activities of ordered proteins. Amino acid biases also drive atypical responses of IDPs to changes in their environment. The conformational behavior of IDPs is characterized by the low cooperativity (or the complete lack thereof) of the denaturant-induced unfolding, lack of the measurable excess heat absorption peak(s) characteristic for the melting of ordered proteins, “turned out” response to heat and changes in pH, the ability to gain structure in the presence of various counter ions, osmolytes, membranes and binding partners, and by the unique response to macromolecular crowding. This review describes some of the most characteristic features of the IDP conformational behavior and the unique response of IDPs to changes in their environment.     

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.     

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.     

Analysis of protein features and machine learning algorithms for prediction of druggable proteins

Background: Computational tools have been widely used in drug discovery process since they reduce the time and cost. Prediction of whether a protein is druggable is fundamental and crucial for drug research pipeline. Sequence based protein function prediction plays vital roles in many research areas. Training data, protein features selection and machine learning algorithms are three indispensable elements that drive the successfulness of the models. Methods: In this study, we tested the performance of different combinations of protein features and machine learning algorithms, based on FDA-approved small molecules’ targets, in druggable proteins prediction. We also enlarged the dataset to include the targets of small molecules that were in experiment or clinical investigation. Results: We found that although the 146-d vector used by Li et al. with neuron network achieved the best training accuracy of 91.10%, overlapped 3-gram word2vec with logistic regression achieved best prediction accuracy on independent test set (89.55%) and on newly approved-targets. Enlarged dataset with targets of small molecules in experiment and clinical investigation were trained. Unfortunately, the best training accuracy was only 75.48%. In addition, we applied our models to predict potential targets for references in future study. Conclusions: Our study indicates the potential ability of word2vec in the prediction of druggable protein. And the training dataset of druggable protein should not be extended to targets that are lack of verification. The target prediction package could be found on https://github.com/pkumdl/target_prediction.     

Ligand Clouds around Protein Clouds: A Scenario of Ligand Binding with Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) were found to be widely associated with human diseases and may serve as potential drug design targets. However, drug design targeting IDPs is still in the very early stages. Progress in drug design is usually achieved using experimental screening; however, the structural disorder of IDPs makes it difficult to characterize their interaction with ligands using experiments alone. To better understand the structure of IDPs and their interactions with small molecule ligands, we performed extensive simulations on the c-Myc_370–409 peptide and its binding to a reported small molecule inhibitor, ligand 10074-A4. We found that the conformational space of the apo c-Myc_370–409 peptide was rather dispersed and that the conformations of the peptide were stabilized mainly by charge interactions and hydrogen bonds. Under the binding of the ligand, c-Myc_370–409 remained disordered. The ligand was found to bind to c-Myc_370–409 at different sites along the chain and behaved like a ‘ligand cloud’. In contrast to ligand binding to more rigid target proteins that usually results in a dominant bound structure, ligand binding to IDPs may better be described as ligand clouds around protein clouds. Nevertheless, the binding of the ligand and a non-ligand to the c-Myc_370–409 target could be clearly distinguished. The present study provides insights that will help improve rational drug design that targets IDPs.     

Utilization of protein intrinsic disorder knowledge in structural proteomics

Intrinsically disordered proteins (IDPs) and proteins with long disordered regions are highly abundant in various proteomes. Despite their lack of well-defined ordered structure, these proteins and regions are frequently involved in crucial biological processes. Although in recent years these proteins have attracted the attention of many researchers, IDPs represent a significant challenge for structural characterization since these proteins can impact many of the processes in the structure determination pipeline. Here we investigate the effects of IDPs on the structure determination process and the utility of disorder prediction in selecting and improving proteins for structural characterization. Examination of the extent of intrinsic disorder in existing crystal structures found that relatively few protein crystal structures contain extensive regions of intrinsic disorder. Although intrinsic disorder is not the only cause of crystallization failures and many structured proteins cannot be crystallized, filtering out highly disordered proteins from structure-determination target lists is still likely to be cost effective. Therefore it is desirable to avoid highly disordered proteins from structure-determination target lists and we show that disorder prediction can be applied effectively to enrich structure determination pipelines with proteins more likely to yield crystal structures. For structural investigation of specific proteins, disorder prediction can be used to improve targets for structure determination. Finally, a framework for considering intrinsic disorder in the structure determination pipeline is proposed.     

A decade and a half of protein intrinsic disorder: Biology still waits for physics

The abundant existence of proteins and regions that possess specific functions without being uniquely folded into unique 3D structures has become accepted by a significant number of protein scientists. Sequences of these intrinsically disordered proteins (IDPs) and IDP regions (IDPRs) are characterized by a number of specific features, such as low overall hydrophobicity and high net charge which makes these proteins predictable. IDPs/IDPRs possess large hydrodynamic volumes, low contents of ordered secondary structure, and are characterized by high structural heterogeneity. They are very flexible, but some may undergo disorder to order transitions in the presence of natural ligands. The degree of these structural rearrangements varies over a very wide range. IDPs/IDPRs are tightly controlled under the normal conditions and have numerous specific functions that complement functions of ordered proteins and domains. When lacking proper control, they have multiple roles in pathogenesis of various human diseases. Gaining structural and functional information about these proteins is a challenge, since they do not typically “freeze” while their “pictures are taken.” However, despite or perhaps because of the experimental challenges, these fuzzy objects with fuzzy structures and fuzzy functions are among the most interesting targets for modern protein research. This review briefly summarizes some of the recent advances in this exciting field and considers some of the basic lessons learned from the analysis of physics, chemistry, and biology of IDPs.     

Small Molecule Sequestration of the Intrinsically Disordered Protein,p27Kip1, Within Soluble Oligomers

Proteins that exhibit intrinsically disordered regions (IDRs) are prevalent in the human proteome and perform diverse biological functions, including signaling and regulation. Due to these important roles, misregulation of intrinsically disordered proteins (IDPs) is associated with myriad human diseases, including neurodegeneration and cancer. The inherent flexibility of IDPs limits the applicability of the traditional structure-based drug design paradigm; therefore, IDPs have long been considered “undruggable”. Using NMR spectroscopy and other methods, we previously discovered small, drug-like molecules that bind specifically, albeit weakly, to dynamic clusters of aromatic residues within p27^Kip1 (p27), an archetypal disordered protein involved in cell cycle regulation. Here, using synthetic chemistry, NMR spectroscopy and other biophysical methods, we discovered elaborated analogs of our previously reported molecules with 30-fold increased affinity for p27 (apparent K_d = 57 ± 19 μM). Strikingly, using analytical ultracentrifugation methods, we showed that the highest affinity compounds caused p27 to form soluble, disordered oligomers. Based on these observations, we propose that sequestration within soluble oligomers may represent a general strategy for therapeutically targeting disease-associated IDPs in the future.     

Do sequence neighbours of intrinsically disordered regions promote structural flexibility in intrinsically disordered proteins?

Intrinsically disordered proteins (IDPs) are crucial players in various cellular activities. Several experimental and computational analyses have been conducted to study structural pliability and functional potential of IDPs. In spite of active research in past few decades, what induces structural disorder in IDPs and how is still elusive. Many studies testify that sequential and spatial neighbours often play important roles in determining structural and functional behaviour of proteins. Considering this fact, we assessed sequence neighbours of intrinsically disordered regions (IDRs) to understand if they have any role to play in inducing structural flexibility in IDPs. Our analysis includes 97% eukaryotic IDPs and 3% from bacteria and viruses. Physicochemical and structural parameters including amino acid propensity, hydrophobicity, secondary structure propensity, relative solvent accessibility, B-factor and atomic packing density are used to characterise the neighbouring residues of IDRs (NRIs). We show that NRIs exhibit a unique nature, which makes them stand out from both ordered and disordered residues. They show correlative occurrences of residue pairs like Ser-Thr and Gln-Asn, indicating their tendency to avoid strong biases of order or disorder promoting amino acids. We also find differential preferences of amino acids between N- and C-terminal neighbours, which might indicate a plausible directional effect on the dynamics of adjacent IDRs. We designed an efficient prediction tool using Random Forest to distinguish the NRIs from the ordered residues. Our findings will contribute to understand the behaviour of IDPs, and may provide potential lead in deciphering the role of IDRs in protein folding and assembly.     

Internal cavities and buried waters in globular proteins

A fast algorithm that detects internal cavities in proteins and predicts the positions of buried water molecules is described. The cavities are characterized in terms of volume, surface area, polarity, and the presence of bound waters. The algorithm is applied to 12 proteins whose structures are known to high resolution and successfully predicts the locations of over 80% of internal water molecules. Most proteins are found to have a number of internal cavities ranging in volume from 10 to 180 A3. Some of these cavities contain water and some do not, with the probability of containing a buried water increasing with cavity size. However, many large cavities are found to be empty (i.e., they do not contain a crystallographically determined water). For multidomain proteins over half of the total cavity volume is at the interdomain interface. Possible implications for the energetics of cavity formation and for the functional role of internal cavities are discussed.     

Disease mutations in disordered regions--exception to the rule?

Intrinsically disordered proteins (IDPs) have been implicated in a number of human diseases, including cancer, diabetes, neurodegenerative and cardiovascular disorders. Although for some of these conditions molecular mechanisms are now better understood, the big picture connecting distinct structural properties and functional repertoire of IDPs to pathogenesis and disease progression is still incomplete. Recent studies suggest that signaling and regulatory roles carried out by IDPs require them to be tightly regulated, and that altered IDP abundance may lead to disease. Here, we propose another link between IDPs and disease that takes into account disease-associated missense mutations located in the intrinsically disordered regions. We argue that such mutations are more prevalent and have larger functional impact than previously thought. In addition, we demonstrate that deleterious amino acid substitutions that cause disorder-to-order transitions are particularly enriched among disease mutations compared to neutral polymorphisms. Finally, we discuss potential differences in functional outcomes between disease mutations in ordered and disordered regions, and challenge the conventional structure-centric view of missense mutations.     

Does Intrinsic Disorder in Proteins Favor Their Interaction with Lipids?

Intrinsically disordered proteins (IDPs) are implicated in a range of human diseases, some of which are associated with the ability to bind to lipids. Although the presence of solvent‐exposed hydrophobic regions in IDPs should favor their interactions with low‐molecular‐weight hydrophobic/amphiphilic compounds, this hypothesis has not been systematically explored as of yet. In this study, the analysis of the DisProt database with regard to the presence of lipid‐binding IDPs (LBIDPs) reveals that they comprise, at least, 15% of DisProt entries. LBIDPs are classified into four groups by ligand type, functional categories, domain structure, and conformational state. 57% of LBIDPs are classified as ordered according to the CH‐CDF analysis, and 70% of LBIDPs possess lengths of disordered regions below 50%. To investigate the lipid‐binding properties of IDPs for which lipid binding is not reported, three proteins from different conformational groups are rationally selected. They all are shown to bind linoleic (LA) and oleic (OA) acids with capacities ranging from 9 to 34 LA/OA molecules per protein molecule. The association with LA/OA causes the formation of high‐molecular‐weight lipid–protein complexes. These findings suggest that lipid binding is common among IDPs, which can favor their involvement in lipid metabolism.