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.     

An assignment of intrinsically disordered regions of proteins based on NMR structures

Intrinsically disordered proteins (IDPs) do not adopt stable three-dimensional structures in physiological conditions, yet these proteins play crucial roles in biological phenomena. In most cases, intrinsic disorder manifests itself in segments or domains of an IDP, called intrinsically disordered regions (IDRs), but fully disordered IDPs also exist. Although IDRs can be detected as missing residues in protein structures determined by X-ray crystallography, no protocol has been developed to identify IDRs from structures obtained by Nuclear Magnetic Resonance (NMR). Here, we propose a computational method to assign IDRs based on NMR structures. We compared missing residues of X-ray structures with residue-wise deviations of NMR structures for identical proteins, and derived a threshold deviation that gives the best correlation of ordered and disordered regions of both structures. The obtained threshold of 3.2 Å was applied to proteins whose structures were only determined by NMR, and the resulting IDRs were analyzed and compared to those of X-ray structures with no NMR counterpart in terms of sequence length, IDR fraction, protein function, cellular location, and amino acid composition, all of which suggest distinct characteristics. The structural knowledge of IDPs is still inadequate compared with that of structured proteins. Our method can collect and utilize IDRs from structures determined by NMR, potentially enhancing the understanding of IDPs.     

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.     

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.     

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.     

固有无序蛋白质及逆境胁迫下的分子功能

固有无序蛋白质是一类在生理条件下缺乏稳定三维结构而具有正常功能,参与信号转导、转录调控、胁迫应答等多种生物学过程的蛋白质.植物中许多逆境响应蛋白是固有无序蛋白质,通过其结构无序或部分无序区域在蛋白质 蛋白质、蛋白质 膜脂、蛋白质 核酸的互作中发挥重要作用.本文主要对固有无序蛋白质的类别、氨基酸组成和结构特点以及在逆境胁迫下其稳定细胞膜、保护核酸和蛋白质、调控基因表达等分子功能进行综述,以拓展对逆境胁迫下蛋白质作用分子机制的认识.     

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.     

NMR illuminates intrinsic disorder

Nuclear magnetic resonance (NMR) has long been instrumental in the characterization of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs). This method continues to offer rich insights into the nature of IDPs in solution, especially in combination with other biophysical methods such as small-angle scattering, single-molecule fluorescence, electron paramagnetic resonance (EPR), and mass spectrometry. Substantial advances have been made in recent years in studies of proteins containing both ordered and disordered domains and in the characterization of problematic sequences containing repeated tracts of a single or a few amino acids. These sequences are relevant to disease states such as Alzheimer's, Parkinson's, and Huntington's diseases, where disordered proteins misfold into harmful amyloid. Innovative applications of NMR are providing novel insights into mechanisms of protein aggregation and the complexity of IDP interactions with their targets. As a basis for understanding the solution structural ensembles, dynamic behavior, and functional mechanisms of IDPs and IDRs, NMR continues to prove invaluable.     

On the Potential of Machine Learning to Examine the Relationship Between Sequence,Structure, Dynamics and Function of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs—and intrinsically disordered regions (IDRs) interspersed between folded domains—are generally characterized as having no persistent tertiary structure; instead they interconvert between a large number of different and often expanded structures. IDPs and IDRs are involved in an enormously wide range of biological functions and reveal novel mechanisms of interactions, and while they defy the common structure-function paradigm of folded proteins, their structural preferences and dynamics are important for their function. We here discuss open questions in the field of IDPs and IDRs, focusing on areas where machine learning and other computational methods play a role. We discuss computational methods aimed to predict transiently formed local and long-range structure, including methods for integrative structural biology. We discuss the many different ways in which IDPs and IDRs can bind to other molecules, both via short linear motifs, as well as in the formation of larger dynamic complexes such as biomolecular condensates. We discuss how experiments are providing insight into such complexes and may enable more accurate predictions. Finally, we discuss the role of IDPs in disease and how new methods are needed to interpret the mechanistic effects of genomic variants in IDPs.     

How do disordered regions achieve comparable functions to structured domains?

The traditional structure to function paradigm conceives of a protein''s function as emerging from its structure. In recent years, it has been established that unstructured, intrinsically disordered regions (IDRs) in proteins are equally crucial elements for protein function, regulation and homeostasis. In this review, we provide a brief overview of how IDRs can perform similar functions to structured proteins, focusing especially on the formation of protein complexes and assemblies and the mediation of regulated conformational changes. In addition to highlighting instances of such functional equivalence, we explain how differences in the biological and physicochemical properties of IDRs allow them to expand the functional and regulatory repertoire of proteins. We also discuss studies that provide insights into how mutations within functional regions of IDRs can lead to human diseases.     

Sequence-to-Conformation Relationships of Disordered Regions Tethered to Folded Domains of Proteins

Intrinsically disordered proteins and regions (IDPs/IDRs) are characterized by well-defined sequence-to-conformation relationships (SCRs). These relationships refer to the sequence-specific preferences for average sizes, shapes, residue-specific secondary structure propensities, and amplitudes of multiscale conformational fluctuations. SCRs are discerned from the sequence-specific conformational ensembles of IDPs. A vast majority of IDPs are actually tethered to folded domains (FDs). This raises the question of whether or not SCRs inferred for IDPs are applicable to IDRs tethered to FDs. Here, we use atomistic simulations based on a well-established forcefield paradigm and an enhanced sampling method to obtain comparative assessments of SCRs for 13 archetypal IDRs modeled as autonomous units, as C-terminal tails connected to FDs, and as linkers between pairs of FDs. Our studies uncover a set of general observations regarding context-independent versus context-dependent SCRs of IDRs. SCRs are minimally perturbed upon tethering to FDs if the IDRs are deficient in charged residues and for polyampholytic IDRs where the oppositely charged residues within the sequence of the IDR are separated into distinct blocks. In contrast, the interplay between IDRs and tethered FDs has a significant modulatory effect on SCRs if the IDRs have intermediate fractions of charged residues or if they have sequence-intrinsic conformational preferences for canonical random coils. Our findings suggest that IDRs with context-independent SCRs might be independent evolutionary modules, whereas IDRs with context-dependent SCRs might co-evolve with the FDs to which they are tethered.     

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

A major challenge to the characterization of intrinsically disordered regions (IDRs), which are widespread in the proteome, but relatively poorly understood, is the identification of molecular features that mediate functions of these regions, such as short motifs, amino acid repeats and physicochemical properties. Here, we introduce a proteome-scale feature discovery approach for IDRs. Our approach, which we call “reverse homology”, exploits the principle that important functional features are conserved over evolution. We use this as a contrastive learning signal for deep learning: given a set of homologous IDRs, the neural network has to correctly choose a held-out homolog from another set of IDRs sampled randomly from the proteome. We pair reverse homology with a simple architecture and standard interpretation techniques, and show that the network learns conserved features of IDRs that can be interpreted as motifs, repeats, or bulk features like charge or amino acid propensities. We also show that our model can be used to produce visualizations of what residues and regions are most important to IDR function, generating hypotheses for uncharacterized IDRs. Our results suggest that feature discovery using unsupervised neural networks is a promising avenue to gain systematic insight into poorly understood protein sequences.     

High-throughput prediction of RNA,DNA and protein binding regions mediated by intrinsic disorder

Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro, are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein–protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/     

Exploring disorder in the human charged biased proteins

A considerable interest has been put in the identification of biased regions in proteins. These regions are frequently associated with a structural role in the cell and particularly with protein disorder. Here, we have investigated the intrinsically disordered regions (IDRs) in the human charged biased proteins identified in our earlier work. We found that 65% of charged biased proteins contained significant IDRs involved particularly in DNA and RNA binding. Also, we have observed that these proteins are well conserved in metazoans and more particularly in mammalian. In addition, the IDRs are located largely in N-terminal, C-terminal sequence flanking the functional domains (FD) and slightly less in (FD) itself. Our work also supports the association between protein disorder and protein–protein/DNA interaction. An example will be described.     

The Balancing Act of Intrinsically Disordered Proteins: Enabling Functional Diversity while Minimizing Promiscuity

Intrinsically disordered proteins (IDPs) or regions (IDRs) perform diverse cellular functions, but are also prone to forming promiscuous and potentially deleterious interactions. We investigate the extent to which the properties of, and content in, IDRs have adapted to enable functional diversity while limiting interference from promiscuous interactions in the crowded cellular environment. Information on protein sequences, their predicted intrinsic disorder, and 3D structure contents is related to data on protein cellular concentrations, gene co-expression, and protein–protein interactions in the well-studied yeast Saccharomyces cerevisiae. Results reveal that both the protein IDR content and the frequency of “sticky” amino acids in IDRs (those more frequently involved in protein interfaces) decrease with increasing protein cellular concentration. This implies that the IDR content and the amino acid composition of IDRs experience negative selection as the protein concentration increases. In the S. cerevisiae protein–protein interaction network, the higher a protein's IDR content, the more frequently it interacts with IDR-containing partners, and the more functionally diverse the partners are. Employing a clustering analysis of Gene Ontology terms, we newly identify ~ 600 putative multifunctional proteins in S. cerevisiae. Strikingly, these proteins are enriched in IDRs and contribute significantly to all the observed trends. In particular, IDRs of multi-functional proteins feature more sticky amino acids than IDRs of their non-multifunctional counterparts, or the surfaces of structured yeast proteins. This property likely affords sufficient binding affinity for the functional interactions, commonly mediated by short IDR segments, thereby counterbalancing the loss in overall IDR conformational entropy upon binding.