DisProt: the Database of Disordered Proteins

Opposing Intermolecular Tuning of Ca2+ Affinity for Calmodulin by Neurogranin and CaMKII Peptides

We investigated the impact of bound calmodulin (CaM)-target compound structure on the affinity of calcium (Ca²⁺) by integrating coarse-grained models and all-atomistic simulations with nonequilibrium physics. We focused on binding between CaM and two specific targets, Ca²⁺/CaM-dependent protein kinase II (CaMKII) and neurogranin (Ng), as they both regulate CaM-dependent Ca²⁺ signaling pathways in neurons. It was shown experimentally that Ca²⁺/CaM (holoCaM) binds to the CaMKII peptide with overwhelmingly higher affinity than Ca²⁺-free CaM (apoCaM); the binding of CaMKII peptide to CaM in return increases the Ca²⁺ affinity for CaM. However, this reciprocal relation was not observed in the Ng peptide (Ng_13–49), which binds to apoCaM or holoCaM with binding affinities of the same order of magnitude. Unlike the holoCaM-CaMKII peptide, whose structure can be determined by crystallography, the structural description of the apoCaM-Ng_13–49 is unknown due to low binding affinity, therefore we computationally generated an ensemble of apoCaM-Ng_13–49 structures by matching the changes in the chemical shifts of CaM upon Ng_13–49 binding from nuclear magnetic resonance experiments. Next, we computed the changes in Ca²⁺ affinity for CaM with and without binding targets in atomistic models using Jarzynski’s equality. We discovered the molecular underpinnings of lowered affinity of Ca²⁺ for CaM in the presence of Ng_13–49 by showing that the N-terminal acidic region of Ng peptide pries open the β-sheet structure between the Ca²⁺ binding loops particularly at C-domain of CaM, enabling Ca²⁺ release. In contrast, CaMKII peptide increases Ca²⁺ affinity for the C-domain of CaM by stabilizing the two Ca²⁺ binding loops. We speculate that the distinctive structural difference in the bound complexes of apoCaM-Ng_13–49 and holoCaM-CaMKII delineates the importance of CaM’s progressive mechanism of target binding on its Ca²⁺ binding affinities.

CIDER: Resources to Analyze Sequence-Ensemble Relationships of Intrinsically Disordered Proteins

Intrinsically disordered proteins and regions (IDPs) represent a large class of proteins that are defined by conformational heterogeneity and lack of persistent tertiary/secondary structure. IDPs play important roles in a range of biological functions, and their dysregulation is central to numerous diseases, including neurodegeneration and cancer. The conformational ensembles of IDPs are encoded by their amino acid sequences. Here, we present two computational tools that are designed to enable rapid and high-throughput analyses of a wide range of physicochemical properties encoded by IDP sequences. The first, CIDER, is a user-friendly webserver that enables rapid analysis of IDP sequences. The second, localCIDER, is a high-performance software package that enables a wide range of analyses relevant to IDP sequences. In addition to introducing the two packages, we demonstrate the utility of these resources using examples where sequence analysis offers biophysical insights.

Stress-Triggered Phase Separation Is an Adaptive, Evolutionarily Tuned Response

In eukaryotic cells, diverse stresses trigger coalescence of RNA-binding proteins into stress granules. In vitro, stress-granule-associated proteins can demix to form liquids, hydrogels, and other assemblies lacking fixed stoichiometry. Observing these phenomena has generally required conditions far removed from physiological stresses. We show that poly(A)-binding protein (Pab1 in yeast), a defining marker of stress granules, phase separates and forms hydrogels in vitro upon exposure to physiological stress conditions. Other RNA-binding proteins depend upon low-complexity regions (LCRs) or RNA for phase separation, whereas Pab1's LCR is not required for demixing, and RNA inhibits it. Based on unique evolutionary patterns, we create LCR mutations, which systematically tune its biophysical properties and Pab1 phase separation in vitro and in vivo. Mutations that impede phase separation reduce organism fitness during prolonged stress. Poly(A)-binding protein thus acts as a physiological stress sensor, exploiting phase separation to precisely mark stress onset, a broadly generalizable mechanism.

Dissecting physical structure of calreticulin, an intrinsically disordered Ca2+-buffering chaperone from endoplasmic reticulum

Calreticulin (CALR) is a Ca²⁺ binding multifunctional protein that mostly resides in the endoplasmic reticulum (ER) and plays a number of important roles in various physiological and pathological processes. Although the major functions ascribed to CALR are controlling the Ca²⁺ homeostasis in ER and acting as a lectin-like ER chaperon for many glycoproteins, this moonlighting protein can be found in various cellular compartments where it has many non-ER functions. To shed more light on the mechanisms underlying polyfunctionality of this moonlighting protein that can be found in different cellular compartments and that possesses a wide spectrum of unrelated biological activities, being able to interact with Ca²⁺ (and potentially other metal ions), RNA, oligosaccharides, and numerous proteins, we used a set of experimental and computational tools to evaluate the intrinsic disorder status of CALR and the role of calcium binding on structural properties and conformational stability of the full-length CALR and its isolated P- and C-domains.

Phase Separation and Single-Chain Compactness of Charged Disordered Proteins Are Strongly Correlated

Liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is a major undergirding factor in the regulated formation of membraneless organelles in the cell. The phase behavior of an IDP is sensitive to its amino acid sequence. Here we apply a recent random-phase-approximation polymer theory to investigate how the tendency for multiple chains of a protein to phase-separate, as characterized by the critical temperature T^∗_cr, is related to the protein's single-chain average radius of gyration 〈R_g〉. For a set of sequences containing different permutations of an equal number of positively and negatively charged residues, we found a striking correlation T^∗_cr ∼ 〈R_g〉^-γ with γ as large as ∼6.0, indicating that electrostatic effects have similarly significant impact on promoting single-chain conformational compactness and phase separation. Moreover, T^∗_cr ∝ -SCD, where SCD is a recently proposed "sequence charge decoration" parameter determined solely by sequence information. Ramifications of our findings for deciphering the sequence dependence of IDP phase separation are discussed.

Intrinsic disorder in proteins involved in amyotrophic lateral sclerosis

Five structurally and functionally different proteins, an enzyme superoxide dismutase 1 (SOD1), a TAR-DNA binding protein-43 (TDP-43), an RNA-binding protein FUS, a cofilin-binding protein C9orf72, and polypeptides generated as a result of its intronic hexanucleotide expansions, and to lesser degree actin-binding profilin-1 (PFN1), are considered to be the major drivers of amyotrophic lateral sclerosis. One of the features common to these proteins is the presence of significant levels of intrinsic disorder. The goal of this study is to consider these neurodegeneration-related proteins from the intrinsic disorder perspective. To this end, we employed a broad set of computational tools for intrinsic disorder analysis and conducted intensive literature search to gain information on the structural peculiarities of SOD1, TDP-43, FUS, C9orf72, and PFN1 and their intrinsic disorder predispositions, and the roles of intrinsic disorder in their normal and pathological functions.

Tubulin Binding and Polymerization Promoting Properties of Tubulin Polymerization Promoting Proteins Are Evolutionarily Conserved

Tubulin polymerization promoting proteins (TPPPs) constitute a eukaryotic protein family. There are three TPPP paralogs in the human genome, denoted as TPPP1-TPPP3. TPPP1 and TPPP3 are intrinsically unstructured proteins (IUPs) that bind and polymerize tubulin and stabilize microtubules, but TPPP2 does not. Vertebrate TPPPs originated from the ancient invertebrate TPPP by two-round whole-genome duplication; thus, whether the tubulin/microtubule binding function of TPPP1 and TPPP3 is a newly acquired property or was present in the invertebrate orthologs (generally one TPPP per species) has been an open question. To answer this question, we investigated a TPPP from a simple and early branching animal, the sponge Suberites domuncula. Bioinformatics, biochemical, immunochemical, spectroscopic, and electron microscopic data showed that the properties of the sponge protein correspond to those of TPPP1; namely, it is an IUP that strongly binds tubulin and induces its polymerization, proving that these features of animal TPPPs have been evolutionarily conserved.

Regulation of human polλ by ATM-mediated phosphorylation during non-homologous end joining

DNA double strand breaks (DSBs) trigger a variety of cellular signaling processes, collectively termed the DNA-damage response (DDR), that are primarily regulated by protein kinase ataxia-telangiectasia mutated (ATM). Among DDR activated processes, the repair of DSBs by non-homologous end joining (NHEJ) is essential. The proper coordination of NHEJ factors is mainly achieved through phosphorylation by an ATM-related kinase, the DNA-dependent protein kinase catalytic subunit (DNA-PKcs), although the molecular basis for this regulation has yet to be fully elucidated. In this study we identify the major NHEJ DNA polymerase, DNA polymerase lambda (Polλ), as a target for both ATM and DNA-PKcs in human cells. We show that Polλ is efficiently phosphorylated by DNA-PKcs in vitro and predominantly by ATM after DSB induction with ionizing radiation (IR) in vivo. We identify threonine 204 (T204) as a main target for ATM/DNA-PKcs phosphorylation on human Polλ, and establish that its phosphorylation may facilitate the repair of a subset of IR-induced DSBs and the efficient Polλ-mediated gap-filling during NHEJ. Molecular evidence suggests that Polλ phosphorylation might favor Polλ interaction with the DNA-PK complex at DSBs. Altogether, our work provides the first demonstration of how Polλ is regulated by phosphorylation to connect with the NHEJ core machinery during DSB repair in human cells.

Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind

Intrinsically disordered proteins and regions (IDPs and IDRs) are involved in a wide range of cellular functions and they often facilitate interactions with RNAs, DNAs, and proteins. Although many computational methods can predict IDPs and IDRs in protein sequences, only a few methods predict their functions and these functions primarily concern protein binding. We describe how to use the first computational method DisoRDPbind for high-throughput prediction of multiple functions of disordered regions. Our method predicts the RNA-, DNA-, and protein-binding residues located in IDRs in the input protein sequences. DisoRDPbind provides accurate predictions and is sufficiently fast to make predictions for full genomes. Our method is implemented as a user-friendly webserver that is freely available at http://biomine.ece.ualberta.ca/DisoRDPbind/ . We overview our predictor, discuss how to run the webserver, and show how to interpret the corresponding results. We also demonstrate the utility of our method based on two case studies, human BRCA1 protein that binds various proteins and DNA, and yeast 60S ribosomal protein L4 that interacts with proteins and RNA.

Thermal compaction of the intrinsically disordered protein tau: entropic, structural, and hydrophobic factors

The first quantitative assessment of the entropic, hydrophobic, and structural factors producing the thermal compaction of tau, an intrinsically disordered protein.

Intrinsic Disorder and Semi-disorder Prediction by SPINE-D

Over the past decade, it has become evident that a large proportion of proteins contain intrinsically disordered regions, which play important roles in pivotal cellular functions. Many computational tools have been developed with the aim of identifying the level and location of disorder within a protein. In this chapter, we describe a neural network based technique called SPINE-D that employs a unique three-state design and can accurately capture disordered residues in both short and long disordered regions. SPINE-D was trained on a large database of 4229 non-redundant proteins, and yielded an AUC of 0.86 on a cross-validation test and 0.89 on an independent test. SPINE-D can also detect a semi-disordered state that is associated with induced folders and aggregation-prone regions in disordered proteins and weakly stable or locally unfolded regions in structured proteins. We implement an online web service and an offline stand-alone program for SPINE-D, they are freely available at http://sparks-lab.org/SPINE-D/ . We then walk you through how to use the online and offline SPINE-D in making disorder predictions, and examine the disorder and semi-disorder prediction in a case study on the p53 protein.

Protein Bioinformatics Databases and Resources

Many publicly available data repositories and resources have been developed to support protein-related information management, data-driven hypothesis generation, and biological knowledge discovery. To help researchers quickly find the appropriate protein-related informatics resources, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases in this chapter. We also discuss the challenges and opportunities for developing next-generation protein bioinformatics databases and resources to support data integration and data analytics in the Big Data era.

How to Predict Disorder in a Protein of Interest

Currently available computational tools, which are many, provide a researcher with the multitude of options for prediction of intrinsic disorder in a protein of interest and for finding at least some of its disorder-based functions. This chapter provides a highly subjective guideline on how not to be lost in the "dark forest" of available tools for the analysis of intrinsic disorder. By no means it gives a unique pathway through this forest, but simply presents some of the tools the author uses in his everyday research.

Structured States of Disordered Proteins from Genomic Sequences

Protein flexibility ranges from simple hinge movements to functional disorder. Around half of all human proteins contain apparently disordered regions with little 3D or functional information, and many of these proteins are associated with disease. Building on the evolutionary couplings approach previously successful in predicting 3D states of ordered proteins and RNA, we developed a method to predict the potential for ordered states for all apparently disordered proteins with sufficiently rich evolutionary information. The approach is highly accurate (79%) for residue interactions as tested in more than 60 known disordered regions captured in a bound or specific condition. Assessing the potential for structure of more than 1,000 apparently disordered regions of human proteins reveals a continuum of structural order with at least 50% with clear propensity for three- or two-dimensional states. Co-evolutionary constraints reveal hitherto unseen structures of functional importance in apparently disordered proteins.

Understanding the roles of intrinsic disorder in subunits of hemoglobin and the disease process of sickle cell anemia

One of the common genetic disorders is sickle cell anemia, in which 2 recessive alleles must meet to allow for destruction and alteration in the morphology of red blood cells. This usually leads to loss of proper binding of oxygen to hemoglobin and curved, sickle-shaped erythrocytes. The mutation causing this disease occurs in the 6^th codon of the HBB gene encoding the hemoglobin subunit β (β-globin), a protein, serving as an integral part of the adult hemoglobin A (HbA), which is a heterotetramer of 2 α chains and 2 β chains that is responsible for binding to the oxygen in the blood. This mutation changes a charged glutamic acid to a hydrophobic valine residue and disrupts the tertiary structure and stability of the hemoglobin molecule. Since in the field of protein intrinsic disorder, charged and polar residues are typically considered as disorder promoting, in opposite to the order-promoting non-polar hydrophobic residues, in this study we attempted to answer a question if intrinsic disorder might have a role in the pathogenesis of sickle cell anemia. To this end, several disorder predictors were utilized to evaluate the presence of intrinsically disordered regions in all subunits of human hemoglobin: α, β, δ, ε, ζ, γ1, and γ2. Then, structural analysis was completed by using the SWISS-MODEL Repository to visualize the outputs of the disorder predictors. Finally, Uniprot STRING and D²P² were used to determine biochemical interactome and protein partners for each hemoglobin subunit along with analyzing their posttranslational modifications. All these properties were used to determine any differences between the 6 different types of subunits of hemoglobin and to correlate the mutation leading to sickle cell anemia with intrinsic disorder propensity.

How disordered is my protein and what is its disorder for? A guide through the "dark side" of the protein universe

In the last 2 decades it has become increasingly evident that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins lack a stable 3D structure, are ubiquitous and fulfill essential biological functions. Their conformational heterogeneity is encoded in their amino acid sequences, thereby allowing intrinsically disordered proteins or regions to be recognized based on properties of these sequences. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental for delineating boundaries of protein domains amenable to structural determination with X-ray crystallization. This article discusses a comprehensive selection of databases and methods currently employed to disseminate experimental and putative annotations of disorder, predict disorder and identify regions involved in induced folding. It also provides a set of detailed instructions that should be followed to perform computational analysis of disorder.

Genes encoding intrinsic disorder in Eukaryota have high GC content

We analyze a correlation between the GC content in genes of 12 eukaryotic species and the level of intrinsic disorder in their corresponding proteins. Comprehensive computational analysis has revealed that the disordered regions in eukaryotes are encoded by the GC-enriched gene regions and that this enrichment is correlated with the amount of disorder and is present across proteins and species characterized by varying amounts of disorder. The GC enrichment is a result of higher rate of amino acid coded by GC-rich codons in the disordered regions. Individual amino acids have the same GC-content profile between different species. Eukaryotic proteins with the disordered regions encoded by the GC-enriched gene segments carry out important biological functions including interactions with RNAs, DNAs, nucleotides, binding of calcium and metal ions, are involved in transcription, transport, cell division and certain signaling pathways, and are localized primarily in nucleus, cytosol and cytoplasm. We also investigate a possible relationship between GC content, intrinsic disorder and protein evolution. Analysis of a devised "age" of amino acids, their disorder-promoting capacity and the GC-enrichment of their codons suggests that the early amino acids are mostly disorder-promoting and their codons are GC-rich while most of late amino acids are mostly order-promoting.

Simulations of disordered proteins and systems with conformational heterogeneity

Intrinsically disordered proteins (IDPs) and protein regions can facilitate a wide variety of complex physiological processes such as binding, signaling, and formation of membraneless organelles. They can however also play pathological roles by aggregating into cytotoxic oligomers and fibrils. Characterizing the structure and function of disordered proteins is an onerous task, primarily because these proteins adopt transient structures, which are difficult to capture in experiments. Simulations have emerged as a powerful tool for interpreting and augmenting experimental measurements of IDPs. In this review we focus on computer simulations of disordered protein structures, functions, assemblies, and emerging questions that, taken together, give an overview of the field as it exists today.

DisProt 7.0: a major update of the database of disordered proteins

The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance (primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.

Analysis of the native conformation of the LIR/AIM motif in the Atg8/LC3/GABARAP-binding proteins

The Atg8/LC3/GABARAP family of proteins, a group that has structural homology with ubiquitin, connects with a large set of binding partners to function in macroautophagy (hereafter autophagy). This interaction occurs primarily via a conserved motif termed the LC3-interacting region (LIR), or the Atg8-interacting motif (AIM). The consensus sequence for this motif, [W/F/Y]xx[L/I/V], can be found in many proteins, but only some of them are physiological partners containing a functional LIR/AIM. Because the structure of many full-length partners has not been, or cannot be, solved, the structural context of the LIR/AIM within the native protein conformation is not obvious. Here we suggest that the functional LIR/AIM is a short linear motif (SLiM) protein-binding module, arising from an intrinsically disordered region. This finding enables the rapid elimination of some false Atg8/LC3/GABARAP-binding proteins, and connects the exponentially growing knowledge on disordered SLiMs with autophagy.

FuzDB: database of fuzzy complexes, a tool to develop stochastic structure-function relationships for protein complexes and higher-order assemblies

FuzDB (http://protdyn-database.org) compiles experimentally observed fuzzy protein complexes, where intrinsic disorder (ID) is maintained upon interacting with a partner (protein, nucleic acid or small molecule) and directly impacts biological function. Entries in the database have both (i) structural evidence demonstrating the structural multiplicity or dynamic disorder of the ID region(s) in the partner bound form of the protein and (ii) in vitro or in vivo biological evidence that indicates the significance of the fuzzy region(s) in the formation, function or regulation of the assembly. Unlike the other intrinsically disordered or unfolded protein databases, FuzDB focuses on ID regions within a biological context, including higher-order assemblies and presents a detailed analysis of the structural and functional data. FuzDB also provides interpretation of experimental results to elucidate the molecular mechanisms by which fuzzy regions-classified on the basis of topology and mechanism-interfere with the structural ensembles and activity of protein assemblies. Regulatory sites generated by alternative splicing (AS) or post-translational modifications (PTMs) are also collected. By assembling all this information, FuzDB could be utilized to develop stochastic structure-function relationships for proteins and could contribute to the emergence of a new paradigm.

Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures.

Protein intrinsic disorder within the Potyvirus genus: from proteome-wide analysis to functional annotation

Within proteins, intrinsically disordered regions (IDRs) are devoid of stable secondary and tertiary structures under physiological conditions and rather exist as dynamic ensembles of inter-converting conformers. Although ubiquitous in all domains of life, the intrinsic disorder content is highly variable in viral genomes. Over the years, functional annotations of disordered regions at the scale of the whole proteome have been conducted for several animal viruses. But to date, similar studies applied to plant viruses are still missing. Based on disorder prediction tools combined with annotation programs and evolutionary studies, we analyzed the intrinsic disorder content in Potyvirus, using a 10-species dataset representative of this genus diversity. In this paper, we revealed that: (i) the Potyvirus proteome displays high disorder content, (ii) disorder is conserved during Potyvirus evolution, suggesting a functional advantage of IDRs, (iii) IDRs evolve faster than ordered regions, and (iv) IDRs may be associated with major biological functions required for the Potyvirus cycle. Notably, the proteins P1, Coat protein (CP) and Viral genome-linked protein (VPg) display a high content of conserved disorder, enriched in specific motifs mimicking eukaryotic functional modules and suggesting strategies of host machinery hijacking. In these three proteins, IDRs are particularly conserved despite their high amino acid polymorphism, indicating a link to adaptive processes. Through this comprehensive study, we further investigate the biological relevance of intrinsic disorder in Potyvirus biology and we propose a functional annotation of potyviral proteome IDRs.

Intrinsic Disorder of the C-Terminal Domain of Drosophila Methoprene-Tolerant Protein

Methoprene tolerant protein (Met) has recently been confirmed as the long-sought juvenile hormone (JH) receptor. This protein plays a significant role in the cross-talk of the 20-hydroxyecdysone (20E) and JH signalling pathways, which are important for control of insect development and maturation. Met belongs to the basic helix-loop-helix/Per-Arnt-Sim (bHLH-PAS) family of transcription factors. In these proteins, bHLH domains are typically responsible for DNA binding and dimerization, whereas the PAS domains are crucial for the choice of dimerization partner and the specificity of target gene activation. The C-terminal region is usually responsible for the regulation of protein complex activity. The sequence of the Met C-terminal region (MetC) is not homologous to any sequence deposited in the Protein Data Bank (PDB) and has not been structurally characterized to date. In this study, we show that the MetC exhibits properties typical for an intrinsically disordered protein (IDP). The final averaged structure obtained with small angle X-ray scattering (SAXS) experiments indicates that intrinsically disordered MetC exists in an extended conformation. This extended shape and the long unfolded regions characterise proteins with high flexibility and dynamics. Therefore, we suggest that the multiplicity of conformations adopted by the disordered MetC is crucial for its activity as a biological switch modulating the cross-talk of different signalling pathways in insects.

Structural Basis for Recombinatorial Permissiveness in the Generation of Anaplasma marginale Msp2 Antigenic Variants

Sequential expression of outer membrane protein antigenic variants is an evolutionarily convergent mechanism used by bacterial pathogens to escape host immune clearance and establish persistent infection. Variants must be sufficiently structurally distinct to escape existing immune effectors yet retain the core structural elements required for localization and function within the outer membrane. We examined this balance using Anaplasma marginale, which generates antigenic variants in the outer membrane protein Msp2 using gene conversion. The overwhelming majority of Msp2 variants expressed during long-term persistent infection are mosaics, derived by recombination of oligonucleotide segments from multiple alleles to form unique hypervariable regions (HVR). As a result, the mosaics are not under long-term selective pressure to encode a functional protein; consequently, we hypothesized that the Msp2 HVR is structurally permissive for mosaic expression. Using an integrated approach of predictive modeling with determination of the native Msp2 protein structure and function, we demonstrate that structured elements, most notably, β-sheets, are significantly concentrated in the highly conserved N- and C-terminal domains. In contrast, the HVR is overwhelmingly a random coil, with the structured α-helices and β-sheets being confined to the genomically defined structural tethers that separate the antigenically variable microdomains. This structure is supported by the surface exposure of the HVR microdomains and the slow diffusion-type porin function in native Msp2. Importantly, the predominance of the random coil provides plasticity for the formation of functional HVR mosaics and realization of the full potential of segmental gene conversion to dramatically expand the variant repertoire.

Binding Mechanisms of Intrinsically Disordered Proteins: Theory, Simulation, and Experiment

In recent years, protein science has been revolutionized by the discovery of intrinsically disordered proteins (IDPs). In contrast to the classical paradigm that a given protein sequence corresponds to a defined structure and an associated function, we now know that proteins can be functional in the absence of a stable three-dimensional structure. In many cases, disordered proteins or protein regions become structured, at least locally, upon interacting with their physiological partners. Many, sometimes conflicting, hypotheses have been put forward regarding the interaction mechanisms of IDPs and the potential advantages of disorder for protein-protein interactions. Whether disorder may increase, as proposed, e.g., in the “fly-casting” hypothesis, or decrease binding rates, increase or decrease binding specificity, or what role pre-formed structure might play in interactions involving IDPs (conformational selection vs. induced fit), are subjects of intense debate. Experimentally, these questions remain difficult to address. Here, we review experimental studies of binding mechanisms of IDPs using NMR spectroscopy and transient kinetic techniques, as well as the underlying theoretical concepts and numerical methods that can be applied to describe these interactions at the atomic level. The available literature suggests that the kinetic and thermodynamic parameters characterizing interactions involving IDPs can vary widely and that there may be no single common mechanism that can explain the different binding modes observed experimentally. Rather, disordered proteins appear to make combined use of features such as pre-formed structure and flexibility, depending on the individual system and the functional context.

Estimation of Position Specific Energy as a Feature of Protein Residues from Sequence Alone for Structural Classification

A set of features computed from the primary amino acid sequence of proteins, is crucial in the process of inducing a machine learning model that is capable of accurately predicting three-dimensional protein structures. Solutions for existing protein structure prediction problems are in need of features that can capture the complexity of molecular level interactions. With a view to this, we propose a novel approach to estimate position specific estimated energy (PSEE) of a residue using contact energy and predicted relative solvent accessibility (RSA). Furthermore, we demonstrate PSEE can be reasonably estimated based on sequence information alone. PSEE is useful in identifying the structured as well as unstructured or, intrinsically disordered region of a protein by computing favorable and unfavorable energy respectively, characterized by appropriate threshold. The most intriguing finding, verified empirically, is the indication that the PSEE feature can effectively classify disorder versus ordered residues and can segregate different secondary structure type residues by computing the constituent energies. PSEE values for each amino acid strongly correlate with the hydrophobicity value of the corresponding amino acid. Further, PSEE can be used to detect the existence of critical binding regions that essentially undergo disorder-to-order transitions to perform crucial biological functions. Towards an application of disorder prediction using the PSEE feature, we have rigorously tested and found that a support vector machine model informed by a set of features including PSEE consistently outperforms a model with an identical set of features with PSEE removed. In addition, the new disorder predictor, DisPredict2, shows competitive performance in predicting protein disorder when compared with six existing disordered protein predictors.

The role of protein intrinsic disorder in major psychiatric disorders

Although new candidate genes for Autism Spectrum Disorder (ASD), Schizophrenia (SCZ), Attention-Deficit/Hyperactivity Disorder (ADHD), and Bipolar Disorder (BD) emerged from genome-wide association studies (GWAS), their underlying molecular mechanisms remain poorly understood. Evidences of the involvement of intrinsically disordered proteins in diseases have grown in the last decade. These proteins lack tridimensional structure under physiological conditions and are involved in important cellular functions such as signaling, recognition and regulation. The aim of the present study was to identify the role and abundance of intrinsically disordered proteins in a set of psychiatric diseases and to test whether diseases are different regarding protein intrinsic disorder. Our hypothesis is that differences across psychiatric illnesses phenotypes and symptoms may arise from differences in intrinsic protein disorder content and properties of each group. A bioinformatics prediction of intrinsic disorder was performed in proteins retrieved based on top findings from GWAS, Copy Number Variation and candidate gene investigations for each disease. This approach revealed that about 80% of studied proteins presented long stretches of disorder. This amount was significantly higher than that observed in general eukaryotic proteins, and those involved in cardiovascular diseases. These results suggest that proteins with intrinsic disorder are a common feature of neurodevelopment and synaptic transmission processes which are potentially involved in the etiology of psychiatric diseases. Moreover, we identified differences between ADHD and ASD when the binary prediction of structure and putative binding sites were compared. These differences may be related to variation in symptom complexity between both diseases. © 2016 Wiley Periodicals, Inc.

Resonance assignment of disordered protein with repetitive and overlapping sequence using combinatorial approach reveals initial structural propensities and local restrictions in the denatured state

NMR resonance assignment of intrinsically disordered proteins poses a challenge because of the limited dispersion of amide proton chemical shifts. This becomes even more complex with the increase in the size of the system. Residue specific selective labeling/unlabeling experiments have been used to resolve the overlap, but require multiple sample preparations. Here, we demonstrate an assignment strategy requiring only a single sample of uniformly labeled (13)C,(15)N-protein. We have used a combinatorial approach, involving 3D-HNN, CC(CO)NH and 2D-MUSIC, which allowed us to assign a denatured centromeric protein Cse4 of 229 residues. Further, we show that even the less sensitive experiments, when used in an efficient manner can lead to the complete assignment of a complex system without the use of specialized probes in a relatively short time frame. The assignment of the amino acids discloses the presence of local structural propensities even in the denatured state accompanied by restricted motion in certain regions that provides insights into the early folding events of the protein.

Putative alternative functions of human stefin B (cystatin B): binding to amyloid-beta, membranes, and copper

We describe studies performed thus far on stefin B from the family of cystatins as a model protein for folding and amyloid fibril formation studies. We also briefly mention our studies on aggregation of some of the missense EPM1 mutants of stefin B in cells, which mimic additional pathological traits (gain in toxic function) in selected patients with EPM1 disease. We collected data on the reported interactors of stefin B and discuss several hypotheses of possible cytosolic alternative functions.

G23D: Online tool for mapping and visualization of genomic variants on 3D protein structures

Background

Evaluation of the possible implications of genomic variants is an increasingly important task in the current high throughput sequencing era. Structural information however is still not routinely exploited during this evaluation process. The main reasons can be attributed to the partial structural coverage of the human proteome and the lack of tools which conveniently convert genomic positions, which are the frequent output of genomic pipelines, to proteins and structure coordinates.

Results

We present G23D, a tool for conversion of human genomic coordinates to protein coordinates and protein structures. G23D allows mapping of genomic positions/variants on evolutionary related (and not only identical) protein three dimensional (3D) structures as well as on theoretical models. By doing so it significantly extends the space of variants for which structural insight is feasible. To facilitate interpretation of the variant consequence, pathogenic variants, functional sites and polymorphism sites are displayed on protein sequence and structure diagrams alongside the input variants. G23D also provides modeling of the mutant structure, analysis of intra-protein contacts and instant access to functional predictions and predictions of thermo-stability changes. G23D is available at http://www.sheba-cancer.org.il/G23D.

Conclusions

G23D extends the fraction of variants for which structural analysis is applicable and provides better and faster accessibility for structural data to biologists and geneticists who routinely work with genomic information.

Order, Disorder, and Everything in Between

In addition to the “traditional” proteins characterized by the unique crystal-like structures needed for unique functions, it is increasingly recognized that many proteins or protein regions (collectively known as intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs)), being biologically active, do not have a specific 3D-structure in their unbound states under physiological conditions. There are also subtler categories of disorder, such as conditional (or dormant) disorder and partial disorder. Both the ability of a protein/region to fold into a well-ordered functional unit or to stay intrinsically disordered but functional are encoded in the amino acid sequence. Structurally, IDPs/IDPRs are characterized by high spatiotemporal heterogeneity and exist as dynamic structural ensembles. It is important to remember, however, that although structure and disorder are often treated as binary states, they actually sit on a structural continuum.

Phasins, Multifaceted Polyhydroxyalkanoate Granule-Associated Proteins

Phasins are the major polyhydroxyalkanoate (PHA) granule-associated proteins. They promote bacterial growth and PHA synthesis and affect the number, size, and distribution of the granules. These proteins can be classified in 4 families with distinctive characteristics. Low-resolution structural studies and in silico predictions were performed in order to elucidate the structure of different phasins. Most of these proteins share some common structural features, such as a preponderant α-helix composition, the presence of disordered regions that provide flexibility to the protein, and coiled-coil interacting regions that form oligomerization domains. Due to their amphiphilic nature, these proteins play an important structural function, forming an interphase between the hydrophobic content of PHA granules and the hydrophilic cytoplasm content. Phasins have been observed to affect both PHA accumulation and utilization. Apart from their role as granule structural proteins, phasins have a remarkable variety of additional functions. Different phasins have been determined to (i) activate PHA depolymerization, (ii) increase the expression and activity of PHA synthases, (iii) participate in PHA granule segregation, and (iv) have both in vivo and in vitro chaperone activities. These properties suggest that phasins might play an active role in PHA-related stress protection and fitness enhancement. Due to their granule binding capacity and structural flexibility, several biotechnological applications have been developed using different phasins, increasing the interest in the study of these remarkable proteins.

The gene expression profiling of hepatocellular carcinoma by a network analysis approach shows a dominance of intrinsically disordered proteins (IDPs) between hub nodes

We have analyzed the transcriptomic data from patients with hepatocellular carcinoma (HCC) after viral HCV infection at the various stages of the disease by means of a networking analysis using the publicly available E-MTAB-950 dataset. The data was compared with those obtained in our group from HepG2 cells, a cancer cell line that lacks the viral infection. By sequential pruning of data, and also taking into account the data from cells of healthy patients as blanks, we were able to obtain a distribution of hub genes for the various stages that characterize the disease and finally, we isolated a metabolic sub-net specific to HCC alone. The general picture is that the basic organization to energetically and metabolically sustain the cells in both the normal and diseased conditions is the same, but a complex cluster of sub-networks controlled by hub genes drives the HCC progression with high metabolic flexibility and plasticity. In particular, we have extracted a sub-net of genes strictly correlated to other hub genes of the network from HepG2 cells, but specific for the HCC and mainly devoted to: (i) control at chromatin levels of cell division; (ii) control of ergastoplasmatic stress through protein degradation and misfolding; (iii) control of the immune response also through an increase of mature T-cells in the thymus. This sub-net is characterized by 26 hub genes coding for intrinsically disordered proteins with a high ability to interact with numerous molecular partners. Moreover, we have also noted that periphery molecules, that is, with one or very few interactions (e.g., cytokines or post-translational enzymes), which do not have a central role in the clusters that make up the global metabolic network, essentially have roles as information transporters. The results evidence a strong presence of intrinsically disordered proteins with key roles as hubs in the sub-networks that characterize the various stages of the disease, conferring a structural plasticity to the net nodes but an inherent functional versatility to the whole metabolic net. Thus, our present article provides a novel way of targeting the intrinsic disorder in HCC networks to dampen the cancer effects and provides new insight into the potential mechanisms of HCC. Taken together, the present findings suggest novel targets to design strategies for drug design and may support a rational intervention in the pharmacotherapy of HCC and other associated diseases.

Natural protein sequences are more intrinsically disordered than random sequences

Most natural protein sequences have resulted from millions or even billions of years of evolution. How they differ from random sequences is not fully understood. Previous computational and experimental studies of random proteins generated from noncoding regions yielded inclusive results due to species-dependent codon biases and GC contents. Here, we approach this problem by investigating 10,000 sequences randomized at the amino acid level. Using well-established predictors for protein intrinsic disorder, we found that natural sequences have more long disordered regions than random sequences, even when random and natural sequences have the same overall composition of amino acid residues. We also showed that random sequences are as structured as natural sequences according to contents and length distributions of predicted secondary structure, although the structures from random sequences may be in a molten globular-like state, according to molecular dynamics simulations. The bias of natural sequences toward more intrinsic disorder suggests that natural sequences are created and evolved to avoid protein aggregation and increase functional diversity.

Decoding the Mobility and Time Scales of Protein Loops

The flexible nature of protein loops and the time scales of their dynamics are critical for many biologically important events at the molecular level, such as protein interaction and recognition processes. In order to obtain a predictive understanding of the dynamic properties of loops, 500 ns molecular dynamics (MD) computer simulations of 38 different proteins were performed and validated using NMR chemical shifts. A total of 169 loops were analyzed and classified into three types, namely fast loops with correlation times <10 ns, slow loops with correlation times between 10 and 500 ns, and loops that are static over the course of the whole trajectory. Chemical and biophysical loop descriptors, such as amino-acid sequence, average 3D structure, charge distribution, hydrophobicity, and local contacts were used to develop and parametrize the ToeLoop algorithm for the prediction of the flexibility and motional time scale of every protein loop, which is also implemented as a public Web server (http://spin.ccic.ohio-state.edu/index.php/loop). The results demonstrate that loop dynamics with their time scales can be predicted rapidly with reasonable accuracy, which will allow the screening of average protein structures to help better understand the various roles loops can play in the context of protein-protein interactions and binding.

A collection of intrinsic disorder characterizations from eukaryotic proteomes

Intrinsically disordered proteins and protein regions lack a stable three-dimensional structure under physiological conditions. Several proteomic investigations of intrinsic disorder have been performed to date and have found disorder to be prevalent in eukaryotic proteomes. Here we present descriptive statistics of intrinsic disorder features for ten model eukaryotic proteomes that have been calculated from computational disorder prediction algorithms. The data descriptor also provides consensus disorder annotations as well as additional physical parameters relevant to protein disorder, and further provides protein existence information for all proteins included in our analysis. The complete datasets can be downloaded freely, and it is envisaged that they will be updated periodically with new proteomes and protein disorder prediction algorithms. These datasets will be especially useful for assessing protein disorder, and conducting novel analyses that advance our understanding of intrinsic disorder and protein structure.

Molecular Dynamics Simulations of Intrinsically Disordered Proteins: On the Accuracy of the TIP4P-D Water Model and the Representativeness of Protein Disorder Models

Here, we first present a follow-up to a previous work by our group on the problematic of molecular dynamics simulations of intrinsically disordered proteins (IDPs) [ Henriques et al. J. Chem. Theory Comput. 2015 , 11 , 3420 - 3431 ], using the recently developed TIP4P-D water model. When used in conjunction with the standard AMBER ff99SB-ILDN force field and applied to the simulation of Histatin 5, our IDP model, we obtain results which are in excellent agreement with the best performing IDP-suitable force field from the earlier study and with experiment. We then assess the representativeness of the IDP models used in these and similar studies, finding that most are too short in comparison to the average IDP and contain a bias toward hydrophilic amino acid residues. Moreover, several key order- and disorder-promoting residues are also found to be misrepresented. It seems appropriate for future studies to address these issues.

Computational Framework for Prediction of Peptide Sequences That May Mediate Multiple Protein Interactions in Cancer-Associated Hub Proteins

A considerable proportion of protein-protein interactions (PPIs) in the cell are estimated to be mediated by very short peptide segments that approximately conform to specific sequence patterns known as linear motifs (LMs), often present in the disordered regions in the eukaryotic proteins. These peptides have been found to interact with low affinity and are able bind to multiple interactors, thus playing an important role in the PPI networks involving date hubs. In this work, PPI data and de novo motif identification based method (MEME) were used to identify such peptides in three cancer-associated hub proteins—MYC, APC and MDM2. The peptides corresponding to the significant LMs identified for each hub protein were aligned, the overlapping regions across these peptides being termed as overlapping linear peptides (OLPs). These OLPs were thus predicted to be responsible for multiple PPIs of the corresponding hub proteins and a scoring system was developed to rank them. We predicted six OLPs in MYC and five OLPs in MDM2 that scored higher than OLP predictions from randomly generated protein sets. Two OLP sequences from the C-terminal of MYC were predicted to bind with FBXW7, component of an E3 ubiquitin-protein ligase complex involved in proteasomal degradation of MYC. Similarly, we identified peptides in the C-terminal of MDM2 interacting with FKBP3, which has a specific role in auto-ubiquitinylation of MDM2. The peptide sequences predicted in MYC and MDM2 look promising for designing orthosteric inhibitors against possible disease-associated PPIs. Since these OLPs can interact with other proteins as well, these inhibitors should be specific to the targeted interactor to prevent undesired side-effects. This computational framework has been designed to predict and rank the peptide regions that may mediate multiple PPIs and can be applied to other disease-associated date hub proteins for prediction of novel therapeutic targets of small molecule PPI modulators.

Actin-Induced Structure in the Beta-Thymosin Family of Intrinsically Disordered Proteins

Thymosin β4 (Tβ4) is a 43-amino acid signature motif peptide that defines the beta-thymosin (βT) family of proteins. βTs are intrinsically unstructured in their free states and undergo disorder-to-order transitions in carrying out their biological functions. This property poses challenges in determining their 3D structures, mainly favoring structural studies on the complexes formed between βTs and their interaction partners. One of the βTs' primary binding partners is monomeric actin, a major component of the cytoskeleton in eukaryotic cells. Tβ4's role in this system is to maintain the highly concentrated pool of monomeric actin that can be accessed through profilin by actin filament nucleating machineries. Here, we give an account of the structures of βTs that have been illuminated by nuclear magnetic resonance (NMR) and X-ray crystallography. NMR has been the method of choice for probing regions that have intrinsic conformational preference within the largely disordered βTs in their native states in solution. X-ray crystallography has demonstrated at atomic detail how βTs interact with actin. Detailed analysis of these structures highlights the disorder-to-order transition of Tβ4 in binding to actin and its isoform specificity.

In silico Structural characterization of podocin and assessment of nephrotic syndrome-associated podocin mutants

Nephrotic syndrome (NS) is manifested by hyperproteinuria, hypoalbuminemia, and edema. NPHS2 that encodes podocin was found to have most mutations among the genes that are involved in the pathophysiology of NS. Podocin, an integral membrane protein belonging to stomatin family, is expressed exclusively in podocytes and is localized to slit-diaphragm (SD). Mutations in podocin are known to be associated with steroid-resistant NS and rapid progression to end-stage renal disease, thus signifying its role in maintaining SD integrity and podocyte function. The structural insights of podocin are not known, and the precise mechanism by which podocin contributes to the architecture of SD is yet to be elucidated. In this study, we deduced a model for human podocin, discussed the details of transmembrane localization and intrinsically unstructured regions, and provide an understanding of how podocin interacts with other SD components. Intraprotein interactions were assessed in wild-type podocin and in some of its mutants that are associated with idiopathic NS. Mutations in podocin alter the innate intraprotein interactions affecting the native structure of podocin and its ability to form critical complex with subpodocyte proteins. © 2016 IUBMB Life, 68(7):578-588, 2016.

Single-Molecule FRET Spectroscopy and the Polymer Physics of Unfolded and Intrinsically Disordered Proteins

The properties of unfolded proteins have long been of interest because of their importance to the protein folding process. Recently, the surprising prevalence of unstructured regions or entirely disordered proteins under physiological conditions has led to the realization that such intrinsically disordered proteins can be functional even in the absence of a folded structure. However, owing to their broad conformational distributions, many of the properties of unstructured proteins are difficult to describe with the established concepts of structural biology. We have thus seen a reemergence of polymer physics as a versatile framework for understanding their structure and dynamics. An important driving force for these developments has been single-molecule spectroscopy, as it allows structural heterogeneity, intramolecular distance distributions, and dynamics to be quantified over a wide range of timescales and solution conditions. Polymer concepts provide an important basis for relating the physical properties of unstructured proteins to folding and function.

Cryptic sequence features within the disordered protein p27Kip1 regulate cell cycle signaling

Peptide motifs embedded within intrinsically disordered regions (IDRs) of proteins are often the sites of posttranslational modifications that control cell-signaling pathways. How do IDR sequences modulate the functionalities of motifs? We answer this question using the polyampholytic C-terminal IDR of the cell cycle inhibitory protein p27(Kip1) (p27). Phosphorylation of Thr-187 (T187) within the p27 IDR controls entry into S phase of the cell division cycle. Additionally, the conformational properties of polyampholytic sequences are predicted to be influenced by the linear patterning of oppositely charged residues. Therefore, we designed sequence variants of the p27 IDR to alter charge patterning outside the primary substrate motif containing T187. Computer simulations and biophysical measurements confirm predictions regarding the impact of charge patterning on the global dimensions of IDRs. Through functional studies, we uncover cryptic sequence features within the p27 IDR that influence the efficiency of T187 phosphorylation. Specifically, we find a positive correlation between T187 phosphorylation efficiency and the weighted net charge per residue of an auxiliary motif. We also find that accumulation of positive charges within the auxiliary motif can diminish the efficiency of T187 phosphorylation because this increases the likelihood of long-range intra-IDR interactions that involve both the primary and auxiliary motifs and inhibit their contributions to function. Importantly, our findings suggest that the cryptic sequence features of the WT p27 IDR negatively regulate T187 phosphorylation signaling. Our approaches provide a generalizable strategy for uncovering the influence of sequence contexts on the functionalities of primary motifs in other IDRs.