SNPeffect 5.0: large-scale structural phenotyping of protein coding variants extracted from next-generation sequencing data using AlphaFold models.

BACKGROUND: Next-generation sequencing technologies yield large numbers of genetic alterations, of which a subset are missense variants that alter an amino acid in the protein product. These variants can have a potentially destabilizing effect leading to an increased risk of misfolding and aggregation. Multiple software tools exist to predict the effect of single-nucleotide variants on proteins, however, a pipeline integrating these tools while starting from an NGS data output list of variants is lacking. RESULTS: The previous version SNPeffect 4.0 (De Baets in Nucleic Acids Res 40(D1):D935-D939, 2011) provided an online database containing pre-calculated variant effects and low-throughput custom variant analysis. Here, we built an automated and parallelized pipeline that analyzes the impact of missense variants on the aggregation propensity and structural stability of proteins starting from the Variant Call Format as input. The pipeline incorporates the AlphaFold Protein Structure Database to achieve high coverage for structural stability analyses using the FoldX force field. The effect on aggregation-propensity is analyzed using the established predictors TANGO and WALTZ. The pipeline focuses solely on the human proteome and can be used to analyze proteome stability/damage in a given sample based on sequencing results. CONCLUSION: We provide a bioinformatics pipeline that allows structural phenotyping from sequencing data using established stability and aggregation predictors including FoldX, TANGO, and WALTZ; and structural proteome coverage provided by the AlphaFold database. The pipeline and installation guide are freely available for academic users on https://github.com/vibbits/snpeffect and requires a computer cluster.

Degron masking outlines degronons, co-degrading functional modules in the proteome.

Effective organization of proteins into functional modules (networks, pathways) requires systems-level coordination between transcription, translation and degradation. Whereas the cooperation between transcription and translation was extensively studied, the cooperative degradation regulation of protein complexes and pathways has not been systematically assessed. Here we comprehensively analyzed degron masking, a major mechanism by which cellular systems coordinate degron recognition and protein degradation. For over 200 substrates with characterized degrons (E3 ligase targeting motifs, ubiquitination sites and disordered proteasomal entry sequences), we demonstrate that degrons extensively overlap with protein-protein interaction sites. Analysis of binding site information and protein abundance comparisons show that regulatory partners effectively outcompete E3 ligases, masking degrons from the ubiquitination machinery. Protein abundance variations between normal and cancer cells highlight the dynamics of degron masking components. Finally, integrative analysis of gene co-expression, half-life correlations and functional relationships between interacting proteins point towards higher-order, co-regulated degradation modules ('degronons') in the proteome.

Distance-Based Metrics for Comparing Conformational Ensembles of Intrinsically Disordered Proteins.

Intrinsically disordered proteins are proteins whose native functional states represent ensembles of highly diverse conformations. Such ensembles are a challenge for quantitative structure comparisons because their conformational diversity precludes optimal superimposition of the atomic coordinates necessary for deriving common similarity measures such as the root mean-square deviation of these coordinates. Here, we introduce superimposition-free metrics that are based on computing matrices of the Cα-Cα distance distributions within ensembles and comparing these matrices between ensembles. Differences between two matrices yield information on the similarity between specific regions of the polypeptide, whereas the global structural similarity is captured by the root mean-square difference between the medians of the Cα-Cα distance distributions of two ensembles. Together, our metrics enable rigorous investigations of structure-function relationships in conformational ensembles of intrinsically disordered proteins derived using experimental restraints or by molecular simulations and for proteins containing both structured and disordered regions.

DisProt: intrinsic protein disorder annotation in 2020.

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome.

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.

Unique Physicochemical Patterns of Residues in Protein-Protein Interfaces.

Protein-protein interactions can be characterized by high-resolution structures of complexes, from which diverse features of the interfaces can be derived. For the majority of protein-protein interactions identified, however, there is no information on the structure of the complex or the interface involved in the interaction. Understanding what surface properties drive certain interactions is crucial in the functional evaluation of protein complexes. Here we show that the local patterning of the physicochemical properties of amino acids within surface patches is characteristic of interfaces. To describe this feature in a quantitative manner, we have defined a statistical potential, iPat, as a measure of surface patterning. iPat, which does not take evolutionary conservation or knowledge of the interaction partner into consideration, represents a function principally different from algorithms that consider intermolecular contacts. We assess its suitability for characterizing protein and peptide interfaces, and we demonstrate that iPat is uniquely descriptive for interfaces of proteins that undergo large conformational changes or that are involved in the binding of intrinsically disordered protein (IDP) partners. We suggest that as a stand-alone propensity or in combination with other features, iPat represents a new feature in analyzing the functional binding specificity of protein-protein interactions that has better predictive potential than other simple 1D features, such as hydrophobicity or stickiness.

Disordered Substrates of the 20S Proteasome Link Degradation with Phase Separation.

The 20S proteasome is known to degrade intrinsically disordered proteins (IDPs) via an ubiquitin-independent, disorder-driven mechanism. Unless protected within protein complexes or macromolecular assemblies, certain IDPs can undergo degradation mediated directly by the 20S core particle. In this issue of Proteomics, Myers et al. utilize a proteomics approach to identify ∼500 IDP substrates of the 20S proteasome. Bioinformatics analyses of these substrates demonstrate a large fraction of highly disordered RNA-binding proteins, enriched in low-complexity, prion-like domains. A number of these proteins are also known to form phase-separated membraneless organelles in amyotrophic lateral sclerosis (ALS) and other protein neuropathies. The Myers et al. study highlights potentially interesting connections between IDP degradation and the regulatory dynamics of phase-separated intracellular assemblies. Their work should stimulate further research into the mechanistic details of how the 20S proteasome controls cellular abundances of RNA-binding proteins and thereby regulates RNA-related biological functions within both physiological and pathological phase-separated assemblies.

Phase Separation of C9orf72 Dipeptide Repeats Perturbs Stress Granule Dynamics.

Liquid-liquid phase separation (LLPS) of RNA-binding proteins plays an important role in the formation of multiple membrane-less organelles involved in RNA metabolism, including stress granules. Defects in stress granule homeostasis constitute a cornerstone of ALS/FTLD pathogenesis. Polar residues (tyrosine and glutamine) have been previously demonstrated to be critical for phase separation of ALS-linked stress granule proteins. We now identify an active role for arginine-rich domains in these phase separations. Moreover, arginine-rich dipeptide repeats (DPRs) derived from C9orf72 hexanucleotide repeat expansions similarly undergo LLPS and induce phase separation of a large set of proteins involved in RNA and stress granule metabolism. Expression of arginine-rich DPRs in cells induced spontaneous stress granule assembly that required both eIF2α phosphorylation and G3BP. Together with recent reports showing that DPRs affect nucleocytoplasmic transport, our results point to an important role for arginine-rich DPRs in the pathogenesis of C9orf72 ALS/FTLD.

Numerous proteins with unique characteristics are degraded by the 26S proteasome following monoubiquitination.

The "canonical" proteasomal degradation signal is a substrate-anchored polyubiquitin chain. However, a handful of proteins were shown to be targeted following monoubiquitination. In this study, we established-in both human and yeast cells-a systematic approach for the identification of monoubiquitination-dependent proteasomal substrates. The cellular wild-type polymerizable ubiquitin was replaced with ubiquitin that cannot form chains. Using proteomic analysis, we screened for substrates that are nevertheless degraded under these conditions compared with those that are stabilized, and therefore require polyubiquitination for their degradation. For randomly sampled representative substrates, we confirmed that their cellular stability is in agreement with our screening prediction. Importantly, the two groups display unique features: monoubiquitinated substrates are smaller than the polyubiquitinated ones, are enriched in specific pathways, and, in humans, are structurally less disordered. We suggest that monoubiquitination-dependent degradation is more widespread than assumed previously, and plays key roles in various cellular processes.

Design Principles Involving Protein Disorder Facilitate Specific Substrate Selection and Degradation by the Ubiquitin-Proteasome System.

The ubiquitin-proteasome system (UPS) regulates diverse cellular pathways by the timely removal (or processing) of proteins. Here we review the role of structural disorder and conformational flexibility in the different aspects of degradation. First, we discuss post-translational modifications within disordered regions that regulate E3 ligase localization, conformation, and enzymatic activity, and also the role of flexible linkers in mediating ubiquitin transfer and reaction processivity. Next we review well studied substrates and discuss that substrate elements (degrons) recognized by E3 ligases are highly disordered: short linear motifs recognized by many E3s constitute an important class of degrons, and these are almost always present in disordered regions. Substrate lysines targeted for ubiquitination are also often located in neighboring regions of the E3 docking motifs and are therefore part of the disordered segment. Finally, biochemical experiments and predictions show that initiation of degradation at the 26S proteasome requires a partially unfolded region to facilitate substrate entry into the proteasomal core.

Tripartite degrons confer diversity and specificity on regulated protein degradation in the ubiquitin-proteasome system.

Specific signals (degrons) regulate protein turnover mediated by the ubiquitin-proteasome system. Here we systematically analyse known degrons and propose a tripartite model comprising the following: (1) a primary degron (peptide motif) that specifies substrate recognition by cognate E3 ubiquitin ligases, (2) secondary site(s) comprising a single or multiple neighbouring ubiquitinated lysine(s) and (3) a structurally disordered segment that initiates substrate unfolding at the 26S proteasome. Primary degron sequences are conserved among orthologues and occur in structurally disordered regions that undergo E3-induced folding-on-binding. Posttranslational modifications can switch primary degrons into E3-binding-competent states, thereby integrating degradation with signalling pathways. Degradation-linked lysines tend to be located within disordered segments that also initiate substrate degradation by effective proteasomal engagement. Many characterized mutations and alternative isoforms with abrogated degron components are implicated in disease. These effects result from increased protein stability and interactome rewiring. The distributed nature of degrons ensures regulation, specificity and combinatorial control of degradation.

Ensemble Methods Enable a New Definition for the Solution to Gas-Phase Transfer of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) are important for health and disease, yet their lack of net structure precludes an understanding of their function using classical methods. Gas-phase techniques provide a promising alternative to access information on the structure and dynamics of IDPs, but the fidelity to which these methods reflect the solution conformations of these proteins has been difficult to ascertain. Here we use state of the art ensemble techniques to investigate the solution to gas-phase transfer of a range of different IDPs. We show that IDPs undergo a vast conformational space expansion in the absence of solvent to sample a conformational space 3-5 fold broader than in solution. Moreover, we show that this process is coupled to the electrospray ionization process, which brings about the generation of additional subpopulations for these proteins not observed in solution due to competing effects on protein charge and shape. Ensemble methods have permitted a new definition of the solution to gas-phase transfer of IDPs and provide a roadmap for future investigations into flexible systems by mass spectrometry.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins.

Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their functionality through a quantitative description of the evolutionary conservation of disordered segments involved in binding, and investigated the structural implications of flexibility in terms of conformational stability and interface formation. We conclude that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit. Second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. These findings emphasize the functional importance of intrinsically disordered regions in RNA-binding proteins.

Bioinformatics Approaches for Predicting Disordered Protein Motifs.

Short, linear motifs (SLiMs) in proteins are functional microdomains consisting of contiguous residue segments along the protein sequence, typically not more than 10 consecutive amino acids in length with less than 5 defined positions. Many positions are 'degenerate' thus offering flexibility in terms of the amino acid types allowed at those positions. Their short length and degenerate nature confers evolutionary plasticity meaning that SLiMs often evolve convergently. Further, SLiMs have a propensity to occur within intrinsically unstructured protein segments and this confers versatile functionality to unstructured regions of the proteome. SLiMs mediate multiple types of protein interactions based on domain-peptide recognition and guide functions including posttranslational modifications, subcellular localization of proteins, and ligand binding. SLiMs thus behave as modular interaction units that confer versatility to protein function and SLiM-mediated interactions are increasingly being recognized as therapeutic targets. In this chapter we start with a brief description about the properties of SLiMs and their interactions and then move on to discuss algorithms and tools including several web-based methods that enable the discovery of novel SLiMs (de novo motif discovery) as well as the prediction of novel occurrences of known SLiMs. Both individual amino acid sequences as well as sets of protein sequences can be scanned using these methods to obtain statistically overrepresented sequence patterns. Lists of putatively functional SLiMs are then assembled based on parameters such as evolutionary sequence conservation, disorder scores, structural data, gene ontology terms and other contextual information that helps to assess the functional credibility or significance of these motifs. These bioinformatics methods should certainly guide experiments aimed at motif discovery.

Computational approaches for inferring the functions of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are ubiquitously involved in cellular processes and often implicated in human pathological conditions. The critical biological roles of these proteins, despite not adopting a well-defined fold, encouraged structural biologists to revisit their views on the protein structure-function paradigm. Unfortunately, investigating the characteristics and describing the structural behavior of IDPs is far from trivial, and inferring the function(s) of a disordered protein region remains a major challenge. Computational methods have proven particularly relevant for studying IDPs: on the sequence level their dependence on distinct characteristics determined by the local amino acid context makes sequence-based prediction algorithms viable and reliable tools for large scale analyses, while on the structure level the in silico integration of fundamentally different experimental data types is essential to describe the behavior of a flexible protein chain. Here, we offer an overview of the latest developments and computational techniques that aim to uncover how protein function is connected to intrinsic disorder.

SnapShot: Intrinsic Structural Disorder.

Many proteins (intrinsically disordered proteins, IDPs) or regions of proteins (intrinsically disordered regions, IDRs) lack a well-defined 3D structure under physiological conditions. Albeit unfolded and highly dynamic, these proteins are not denatured; rather, intrinsic structural disorder is their native, functional state.

DisCons: a novel tool to quantify and classify evolutionary conservation of intrinsic protein disorder.

BACKGROUND: Analyzing the amino acid sequence of an intrinsically disordered protein (IDP) in an evolutionary context can yield novel insights on the functional role of disordered regions and sequence element(s). However, in the case of many IDPs, the lack of evolutionary conservation of the primary sequence can hamper the study of functionality, because the conservation of their disorder profile and ensuing function(s) may not appear in a traditional analysis of the evolutionary history of the protein. RESULTS: Here we present DisCons (Disorder Conservation), a novel pipelined tool that combines the quantification of sequence- and disorder conservation to classify disordered residue positions. According to this scheme, the most interesting categories (for functional purposes) are constrained disordered residues and flexible disordered residues. The former residues show conservation of both the sequence and the property of disorder and are associated mainly with specific binding functionalities (e.g., short, linear motifs, SLiMs), whereas the latter class correspond to segments where disorder as a feature is important for function as opposed to the identity of the underlying sequence (e.g., entropic chains and linkers). DisCons therefore helps with elucidating the function(s) arising from the disordered state by analyzing individual proteins as well as large-scale proteomics datasets. CONCLUSIONS: DisCons is an openly accessible sequence analysis tool that identifies and highlights structurally disordered segments of proteins where the conformational flexibility is conserved across homologs, and therefore potentially functional. The tool is freely available both as a web application and as stand-alone source code hosted at http://pedb.vib.be/discons .

Reassessing buried surface areas in protein-protein complexes.

The buried surface area (BSA), which measures the size of the interface in a protein-protein complex may differ from the accessible surface area (ASA) lost upon association (which we call DSA), if conformation changes take place. To evaluate the DSA, we measure the ASA of the interface atoms in the bound and unbound states of the components of 144 protein-protein complexes taken from the Protein-Protein Interaction Affinity Database of Kastritis et al. (2011). We observe differences exceeding 20%, and a systematic bias in the distribution. On average, the ASA calculated in the bound state of the components is 3.3% greater than in their unbound state, and the BSA, 7% greater than the DSA. The bias is observed even in complexes where the conformation changes are small. An examination of the bound and unbound structures points to a possible origin: local movements optimize contacts with the other component at the cost of internal contacts, and presumably also the binding free energy.

Intrinsic structural disorder in cytoskeletal proteins.

Cytoskeleton, the internal scaffold of the cell, displays an exceptional combination of stability and dynamics. It is composed of three major filamentous networks, microfilaments (actin filaments), intermediate filaments (neurofilaments), and microtubules. Together, they ensure the physical and structural stability of the cell, whereby also mediating its large-scale structural rearrangements, motility, stress response, division, and internal transport. All three cytoskeletal systems are built upon the same basic design: they have a central repetitive scaffold assembled from folded building elements, surrounded and regulated by accessory regions/proteins that regulate its formation and mediate its countless interactions with its environment, serving to send regulatory signals to and from the cytoskeleton. Here, we elaborate on the idea that the opposing features of stability and dynamics are also manifest in the dichotomy of the structural status of its components, the core being highly structured and the accessory proteins/regions being highly disordered, and are responsible for most of the regulatory (post-translational) input promoting adaptive responses and providing dynamics necessary for each of the cytoskeletal systems. This pattern entails special consequences, in which the manifold functional advantages of structural disorder, most pronounced in regulatory and signaling functions, are all exploited by nature.

Functional diversity and structural disorder in the human ubiquitination pathway.

The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred - E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions.