Unstructural biology coming of age

Unravelling the involvement of protein disorder in cyanobacterial stress responses

This study has explored the involvement of Intrinsically Disordered Proteins (IDPs) in cyanobacterial stress response. IDPs possess distinct physicochemical properties, which allow them to execute diverse functions. Anabaena PCC 7120, the model photosynthetic, nitrogen-fixing cyanobacterium encodes 688 proteins (11 % of the total proteome) with at least one intrinsically disordered region (IDR). Of these, 130 proteins that showed >30 % overall disorder were designated as IDPs. Physico-chemical analysis, showed these IDPs to adopt shapes ranging from 'globular' to 'tadpole-like'. Upon exposure to NaCl, 41 IDP-encoding genes were found to be differentially expressed. Surprisingly, most of these were induced, indicating the importance of IDP-accumulation in overcoming salt stress. Subsequently, six IDPs were identified to be induced by multiple stresses (salt, ammonium and selenite). Interestingly, the presence of these 6-multiple stress-induced IDPs was conserved in filamentous cyanobacteria. Utilizing the experimental proteomic data of Anabaena, these 6 IDPs were found to interact with many proteins involved in diverse pathways, underscoring their physiological importance as protein hubs. This study lays the framework for IDP-related research in Anabaena by (a) identifying, as well as physiochemically characterizing, all the disordered proteins and (b) uncovering a subset of IDPs that are likely to be critical in adaptation to environmental stresses.

PDFll: Predictors of Disorder and Function of Proteins from the Language of Life

The identification of intrinsically disordered proteins and their functional roles is largely dependent on the performance of computational predictors, necessitating a high standard of accuracy in these tools. In this context, we introduce a novel series of computational predictors, termed PDFll (Predictors of Disorder and Function of proteins from the Language of Life), which are designed to offer precise predictions of protein disorder and associated functional roles based on protein sequences. PDFll is developed through a two-step process. Initially, it leverages large-scale protein language models (pLMs), trained on an extensive dataset comprising billions of protein sequences. Subsequently, the embeddings derived from pLMs are integrated into streamlined, yet sophisticated, deep-learning models to generate predictions. These predictions notably surpass the performance of existing state-of-the-art predictors, particularly those that forecast disorder and function without utilizing evolutionary information.

The Proteomic Analysis of Cancer-Related Alterations in the Human Unfoldome

Many proteins lack stable 3D structures. These intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains with intrinsically disordered protein regions (IDPRs) often carry out regulatory functions related to molecular recognition and signal transduction. IDPs/IDPRs constitute a substantial portion of the human proteome and are termed "the unfoldome". Herein, we probe the human breast cancer unfoldome and investigate relations between IDPs and key disease genes and pathways. We utilized bottom-up proteomics, MudPIT (Multidimensional Protein Identification Technology), to profile differentially expressed IDPs in human normal (MCF-10A) and breast cancer (BT-549) cell lines. Overall, we identified 2271 protein groups in the unfoldome of normal and cancer proteomes, with 148 IDPs found to be significantly differentially expressed in cancer cells. Further analysis produced annotations of 140 IDPs, which were then classified to GO (Gene Ontology) categories and pathways. In total, 65% (91 of 140) IDPs were related to various diseases, and 20% (28 of 140) mapped to cancer terms. A substantial portion of the differentially expressed IDPs contained disordered regions, confirmed by in silico characterization. Overall, our analyses suggest high levels of interactivity in the human cancer unfoldome and a prevalence of moderately and highly disordered proteins in the network.

Uncovering the structural stability of Magnaporthe oryzae effectors: a secretome-wide in silico analysis

Rice blast, caused by the ascomycete fungus Magnaporthe oryzae, is a deadly disease and a major threat to global food security. The pathogen secretes small proteinaceous effectors, virulence factors, inside the host to manipulate and perturb the host immune system, allowing the pathogen to colonize and establish a successful infection. While the molecular functions of several effectors are characterized, very little is known about the structural stability of these effectors. We analyzed a total of 554 small secretory proteins (SSPs) from the M. oryzae secretome to decipher key features of intrinsic disorder (ID) and the structural dynamics of the selected putative effectors through thorough and systematic in silico studies. Our results suggest that out of the total SSPs, 66% were predicted as effector proteins, released either into the apoplast or cytoplasm of the host cell. Of these, 68% were found to be intrinsically disordered effector proteins (IDEPs). Among the six distinct classes of disordered effectors, we observed peculiar relationships between the localization of several effectors in the apoplast or cytoplasm and the degree of disorder. We determined the degree of structural disorder and its impact on protein foldability across all the putative small secretory effector proteins from the blast pathogen, further validated by molecular dynamics simulation studies. This study provides definite clues toward unraveling the mystery behind the importance of structural distortions in effectors and their impact on plant-pathogen interactions. The study of these dynamical segments may help identify new effectors as well.Communicated by Ramaswamy H. Sarma.

Short Linear Motifs in Colorectal Cancer Interactome and Tumorigenesis

Colorectal tumorigenesis is driven by alterations in genes and proteins responsible for cancer initiation, progression, and invasion. This multistage process is based on a dense network of protein-protein interactions (PPIs) that become dysregulated as a result of changes in various cell signaling effectors. PPIs in signaling and regulatory networks are known to be mediated by short linear motifs (SLiMs), which are conserved contiguous regions of 3-10 amino acids within interacting protein domains. SLiMs are the minimum sequences required for modulating cellular PPI networks. Thus, several in silico approaches have been developed to predict and analyze SLiM-mediated PPIs. In this review, we focus on emerging evidence supporting a crucial role for SLiMs in driver pathways that are disrupted in colorectal cancer (CRC) tumorigenesis and related PPI network alterations. As a result, SLiMs, along with short peptides, are attracting the interest of researchers to devise small molecules amenable to be used as novel anti-CRC targeted therapies. Overall, the characterization of SLiMs mediating crucial PPIs in CRC may foster the development of more specific combined pharmacological approaches.

Intrinsic protein disorder uncouples affinity from binding specificity

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins often function by molecular recognition, in which they undergo induced folding. Based on prior generalizations, the idea prevails in the IDP field that due to the entropic penalty of induced folding, the major functional advantage associated with this binding mode is "uncoupling" specificity from binding strength. Nevertheless, both weaker binding and high specificity of IDPs/IDRs rest on limited experimental observations, making these assumptions more speculations than evidence-supported facts. The issue is also complicated by the rather vague concept of specificity that lacks an exact measure, such as the Kd for binding strength. We addressed these issues by creating and analyzing a comprehensive dataset of well-characterized ID/globular protein complexes, for which both the atomic structure of the complex and free energy (ΔG, Kd ) of interaction is known. Through this analysis, we provide evidence that the affinity distributions of IDP/globular and globular/globular complexes show different trends, whereas specificity does not connote to weaker binding strength of IDPs/IDRs. Furthermore, protein disorder extends the spectrum in the direction of very weak interactions, which may have important regulatory consequences and suggest that, in a biological sense, strict correlation of specificity and binding strength are uncoupled by structural disorder.

Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including 15N spin relaxation, without the need for reweighting. Further inspection revealed that 10-20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function.

Enhancing and inhibitory motifs regulate CD4 activity

CD4+ T cells use T cell receptor (TCR)-CD3 complexes, and CD4, to respond to peptide antigens within MHCII molecules (pMHCII). We report here that, through ~435 million years of evolution in jawed vertebrates, purifying selection has shaped motifs in the extracellular, transmembrane, and intracellular domains of eutherian CD4 that enhance pMHCII responses, and covary with residues in an intracellular motif that inhibits responses. Importantly, while CD4 interactions with the Src kinase, Lck, are viewed as key to pMHCII responses, our data indicate that CD4-Lck interactions derive their importance from the counterbalancing activity of the inhibitory motif, as well as motifs that direct CD4-Lck pairs to specific membrane compartments. These results have implications for the evolution and function of complex transmembrane receptors and for biomimetic engineering.

Non-Equilibrium Protein Folding and Activation by ATP-Driven Chaperones

Recent experimental studies suggest that ATP-driven molecular chaperones can stabilize protein substrates in their native structures out of thermal equilibrium. The mechanism of such non-equilibrium protein folding is an open question. Based on available structural and biochemical evidence, I propose here a unifying principle that underlies the conversion of chemical energy from ATP hydrolysis to the conformational free energy associated with protein folding and activation. I demonstrate that non-equilibrium folding requires the chaperones to break at least one of four symmetry conditions. The Hsp70 and Hsp90 chaperones each break a different subset of these symmetries and thus they use different mechanisms for non-equilibrium protein folding. I derive an upper bound on the non-equilibrium elevation of the native concentration, which implies that non-equilibrium folding only occurs in slow-folding proteins that adopt an unstable intermediate conformation in binding to ATP-driven chaperones. Contrary to the long-held view of Anfinsen's hypothesis that proteins fold to their conformational free energy minima, my results predict that some proteins may fold into thermodynamically unstable native structures with the assistance of ATP-driven chaperones, and that the native structures of some chaperone-dependent proteins may be shaped by their chaperone-mediated folding pathways.

Impact of protein conformational diversity on AlphaFold predictions

MOTIVATION

After the outstanding breakthrough of AlphaFold in predicting protein 3D models, new questions appeared and remain unanswered. The ensemble nature of proteins, for example, challenges the structural prediction methods because the models should represent a set of conformers instead of single structures. The evolutionary and structural features captured by effective deep learning techniques may unveil the information to generate several diverse conformations from a single sequence. Here, we address the performance of AlphaFold2 predictions obtained through ColabFold under this ensemble paradigm.

RESULTS

Using a curated collection of apo-holo pairs of conformers, we found that AlphaFold2 predicts the holo form of a protein in ∼70% of the cases, being unable to reproduce the observed conformational diversity with the same error for both conformers. More importantly, we found that AlphaFold2's performance worsens with the increasing conformational diversity of the studied protein. This impairment is related to the heterogeneity in the degree of conformational diversity found between different members of the homologous family of the protein under study. Finally, we found that main-chain flexibility associated with apo-holo pairs of conformers negatively correlates with the predicted local model quality score plDDT, indicating that plDDT values in a single 3D model could be used to infer local conformational changes linked to ligand binding transitions.

AVAILABILITY AND IMPLEMENTATION

Data and code used in this manuscript are publicly available at https://gitlab.com/sbgunq/publications/af2confdiv-oct2021.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Functional inhibition of c-Myc using novel inhibitors identified through “hot spot” targeting

Protein–protein interactions drive various biological processes in healthy as well as disease states. The transcription factor c-Myc plays a crucial role in maintaining cellular homeostasis, and its deregulated expression is linked to various human cancers; therefore, it can be considered a viable target for cancer therapeutics. However, the structural heterogeneity of c-Myc due to its disordered nature poses a major challenge to drug discovery. In the present study, we used an in silico alanine scanning mutagenesis approach to identify “hot spot” residues within the c-Myc/Myc-associated factor X interface, which is highly disordered and has not yet been systematically analyzed for potential small molecule binding sites. We then used the information gained from this analysis to screen potential inhibitors using a conformation ensemble approach. The fluorescence-based biophysical experiments showed that the identified hit molecules displayed noncovalent interactions with these hot spot residues, and further cell-based experiments showed substantial in vitro potency against diverse c-Myc-expressing cancer/stem cells by deregulating c-Myc activity. These biophysical and computational studies demonstrated stable binding of the hit compounds with the disordered c-Myc protein. Collectively, our data indicated effective drug targeting of the disordered c-Myc protein via the determination of hot spot residues in the c-Myc/Myc-associated factor X heterodimer.

NMR of intrinsically disordered proteins: A note on the application of 15N-13Cα het-TOCSY mixing for 13Cα magnetisation transfers

Intrinsically disordered proteins (IDPs) or protein regions represent functionally important biomolecules without unique structure. Their inherent flexibility prevents high-resolution structure determination by X-ray or cryo-EM methods. In contrast, NMR spectroscopy provides an extensive and still growing set of experimental approaches to obtain detailed information on structure and dynamics of IDPs. Here, it is experimentally demonstrated that ¹⁵N-¹³C^α band-selective heteronuclear cross-polarisation that has been successfully employed recently to achieve the efficient transfer of ¹⁵N_x magnetisation from amino acid residue 'i' to 'i + 1' and 'i - 1' residues in uniformly (¹⁵N,¹³C)-labelled intrinsically disordered proteins can also be applied to transfer, without significant relaxation losses, ¹³C^α_x magnetisation from an amino acid residue to its neighbouring residues. The possibility to obtain in one-shot correlation spectra arising from the simultaneous transfer of ¹⁵N_x and ¹³C^α_x magnetisations from an amino acid residue to neighbouring residues is also demonstrated.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

The importance of the compact disordered state in the fuzzy interactions between intrinsically disordered proteins

The intrinsically disordered C-terminal domain (CTD) of protein 4.1G is able to specifically bind a 26-residue intrinsically disordered region of NuMA, forming a dynamic fuzzy complex. As one of a few cases of extremely fuzzy interactions between two intrinsically disordered proteins/regions (IDPs/IDRs) without induced folding, the principle of the binding is unknown. Here, we combined experimental and computational methods to explore the detailed mechanism of the interaction between 4.1G-CTD and NuMA. MD simulations suggest that the kinetic hub states in the structure ensemble of 4.1G-CTD are favorable in the fuzzy complex. The feature of these hub states is that the binding 'hot spot' motifs βA and βB exhibit β strand propensities and are well packed to each other. The binding between 4.1G-CTD and NuMA is disrupted at low pH, which changes the intramolecular packing of 4.1G-CTD and weakens the packing between βA and βB motifs. Low pH conditions also lead to increased hydrodynamic radius and acceleration of backbone dynamics of 4.1G-CTD. All these results underscore the importance of tertiary structural arrangements and overall compactness of 4.1G-CTD in its binding to NuMA, i.e. the compact disordered state of 4.1G-CTD is crucial for binding. Different from the short linear motifs (SLiMs) that are often found to mediate IDP interactions, 4.1G-CTD functions as an intrinsically disordered domain (IDD), which is a functional and structural unit similar to conventional protein domains. This work sheds light on the molecular recognition mechanism of IDPs/IDRs and expands the conventional structure-function paradigm in protein biochemistry.

Global diversity and balancing selection of 23 leading Plasmodium falciparum candidate vaccine antigens

Investigation of the diversity of malaria parasite antigens can help prioritize and validate them as vaccine candidates and identify the most common variants for inclusion in vaccine formulations. Studies of vaccine candidates of the most virulent human malaria parasite, Plasmodium falciparum, have focused on a handful of well-known antigens, while several others have never been studied. Here we examine the global diversity and population structure of leading vaccine candidate antigens of P. falciparum using the MalariaGEN Pf3K (version 5.1) resource, comprising more than 2600 genomes from 15 malaria endemic countries. A stringent variant calling pipeline was used to extract high quality antigen gene 'haplotypes' from the global dataset and a new R-package named VaxPack was used to streamline population genetic analyses. In addition, a newly developed algorithm that enables spatial averaging of selection pressure on 3D protein structures was applied to the dataset. We analysed the genes encoding 23 leading and novel candidate malaria vaccine antigens including csp, trap, eba175, ama1, rh5, and CelTOS. Our analysis shows that current malaria vaccine formulations are based on rare haplotypes and thus may have limited efficacy against natural parasite populations. High levels of diversity with evidence of balancing selection was detected for most of the erythrocytic and pre-erythrocytic antigens. Measures of natural selection were then mapped to 3D protein structures to predict targets of functional antibodies. For some antigens, geographical variation in the intensity and distribution of these signals on the 3D structure suggests adaptation to different human host or mosquito vector populations. This study provides an essential framework for the diversity of P. falciparum antigens to be considered in the design of the next generation of malaria vaccines.

On the Effects of Disordered Tails, Supertertiary Structure and Quinary Interactions on the Folding and Function of Protein Domains

The vast majority of our current knowledge about the biochemical and biophysical properties of proteins derives from in vitro studies conducted on isolated globular domains. However, a very large fraction of the proteins expressed in the eukaryotic cell are structurally more complex. In particular, the discovery that up to 40% of the eukaryotic proteins are intrinsically disordered, or possess intrinsically disordered regions, and are highly dynamic entities lacking a well-defined three-dimensional structure, revolutionized the structure–function paradigm and our understanding of proteins. Moreover, proteins are mostly characterized by the presence of multiple domains, influencing each other by intramolecular interactions. Furthermore, proteins exert their function in a crowded intracellular milieu, transiently interacting with a myriad of other macromolecules. In this review we summarize the literature tackling these themes from both the theoretical and experimental perspectives, highlighting the effects on protein folding and function that are played by (i) flanking disordered tails; (ii) contiguous protein domains; (iii) interactions with the cellular environment, defined as quinary structures. We show that, in many cases, both the folding and function of protein domains is remarkably perturbed by the presence of these interactions, pinpointing the importance to increase the level of complexity of the experimental work and to extend the efforts to characterize protein domains in more complex contexts.

The protein disorder cycle

This mini-review represents a brief, disorder-centric consideration of the interplay between order and disorder in proteins. The goal here is to show that inside the cell, folding, non-folding, and misfolding of proteins are interlinked on multiple levels. This is evidenced by the highly heterogeneous spatio-temporal structural organization of a protein molecule, where one can find differently (dis)ordered components that can undergo local or global order-to-disorder and disorder-to-order transitions needed for functionality. This is further illustrated by the fact that at particular moments of their life, most notably during their synthesis and degradation, all proteins are at least partially disordered. In addition to these intrinsic forms of disorder, proteins are constantly facing extrinsic disorder, which is intrinsic disorder in their functional partners. All this comprises the multileveled protein disorder cycle.

Protein conformational dynamics and phenotypic switching

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure but exist as conformational ensembles. Because of their structural plasticity, they can interact with multiple partners. The protein interactions between IDPs and their partners form scale-free protein interaction networks (PINs) that facilitate information flow in the cell. Because of their plasticity, IDPs typically occupy hub positions in cellular PINs. Furthermore, their conformational dynamics and propensity for post-translational modifications contribute to "conformational" noise which is distinct from the well-recognized transcriptional noise. Therefore, upregulation of IDPs in response to a specific input, such as stress, contributes to increased noise and, hence, an increase in stochastic, "promiscuous" interactions. These interactions lead to activation of latent pathways or can induce "rewiring" of the PIN to yield an optimal output underscoring the critical role of IDPs in regulating information flow. We have used PAGE4, a highly intrinsically disordered stress-response protein as a paradigm. Employing a variety of experimental and computational techniques, we have elucidated the role of PAGE4 in phenotypic switching of prostate cancer cells at a systems level. These cumulative studies over the past decade provide a conceptual framework to better understand how IDP conformational dynamics and conformational noise might facilitate cellular decision-making.

When Order Meets Disorder: Modeling and Function of the Protein Interface in Fuzzy Complexes

The degree of proteins structural organization ranges from highly structured, compact folding to intrinsic disorder, where each degree of self-organization corresponds to specific functions: well-organized structural motifs in enzymes offer a proper environment for precisely positioned functional groups to participate in catalytic reactions; at the other end of the self-organization spectrum, intrinsically disordered proteins act as binding hubs via the formation of multiple, transient and often non-specific interactions. This review focusses on cases where structurally organized proteins or domains associate with highly disordered protein chains, leading to the formation of interfaces with varying degrees of fuzziness. We present a review of the computational methods developed to provide us with information on such fuzzy interfaces, and how they integrate experimental information. The discussion focusses on two specific cases, microtubules and homologous recombination nucleoprotein filaments, where a network of intrinsically disordered tails exerts regulatory function in recruiting partner macromolecules, proteins or DNA and tuning the atomic level association. Notably, we show how computational approaches such as molecular dynamics simulations can bring new knowledge to help bridging the gap between experimental analysis, that mostly concerns ensemble properties, and the behavior of individual disordered protein chains that contribute to regulation functions.

Intrinsically disordered proteins: modes of binding with emphasis on disordered domains

Our notions of protein function have long been determined by the protein structure-function paradigm. However, the idea that protein function is dictated by a prerequisite complementarity of shapes at the binding interface is becoming increasingly challenged. Interactions involving intrinsically disordered proteins (IDPs) have indicated a significant degree of disorder present in the bound state, ranging from static disorder to complete disorder, termed 'random fuzziness'. This review assesses the anatomy of an IDP and relates how its intrinsic properties permit promiscuity and allow for the various modes of interaction. Furthermore, a mechanistic overview of the types of disordered domains is detailed, while also relating to a recent example and the kinetic and thermodynamic principles governing its formation.

Enthalpy-Entropy Compensation in the Promiscuous Interaction of an Intrinsically Disordered Protein with Homologous Protein Partners

Intrinsically disordered proteins (IDPs) can engage in promiscuous interactions with their protein targets; however, it is not clear how this feature is encoded in the primary sequence of the IDPs and to what extent the surface properties and the shape of the binding cavity dictate the binding mode and the final bound conformation. Here we show, using a combination of nuclear magnetic resonance (NMR) spectroscopy and isothermal titration calorimetry (ITC), that the promiscuous interaction of the intrinsically disordered regulatory domain of the mitogen-activated protein kinase kinase MKK4 with p38α and JNK1 is facilitated by folding-upon-binding into two different conformations, despite the high sequence conservation and structural homology between p38α and JNK1. Our results support a model whereby the specific surface properties of JNK1 and p38α dictate the bound conformation of MKK4 and that enthalpy–entropy compensation plays a major role in maintaining comparable binding affinities for MKK4 towards the two kinases.

Exploring Curated Conformational Ensembles of Intrinsically Disordered Proteins in the Protein Ensemble Database

The Protein Ensemble Database (PED; https://proteinensemble.org/) is the major repository of conformational ensembles of intrinsically disordered proteins (IDPs). Conformational ensembles of IDPs are primarily provided by their authors or occasionally collected from literature, and are subsequently deposited in PED along with the corresponding structured, manually curated metadata. The modeling of conformational ensembles usually relies on experimental data from small-angle X-ray scattering (SAXS), fluorescence resonance energy transfer (FRET), NMR spectroscopy, and molecular dynamics (MD) simulations, or a combination of these techniques. The growing number of scientific studies based on these data, along with the astounding and swift progress in the field of protein intrinsic disorder, has required a significant update and upgrade of PED, first published in 2014. To this end, the database was entirely renewed in 2020 and now has a dedicated team of biocurators providing manually curated descriptions of the methods and conditions applied to generate the conformational ensembles and for checking consistency of the data. Here, we present a detailed description on how to explore PED with its protein pages and experimental pages, and how to interpret entries of conformational ensembles. We describe how to efficiently search conformational ensembles deposited in PED by means of its web interface and API. We demonstrate how to make sense of the PED protein page and its associated experimental entry pages with reference to the yeast Sic1 use case. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Performing a search in PED Support Protocol 1: Programmatic access with the PED API Basic Protocol 2: Interpreting the protein page and the experimental entry page-the Sic1 use case Support Protocol 2: Downloading options Support Protocol 3: Understanding the validation report-the Sic1 use case Basic Protocol 3: Submitting new conformational ensembles to PED Basic Protocol 4: Providing feedback in PED.

Exploring Energy Landscapes of Intrinsically Disordered Proteins: Insights into Functional Mechanisms

Intrinsically disordered proteins (IDPs) lack a rigid three-dimensional structure and populate a polymorphic ensemble of conformations. Because of the lack of a reference conformation, their energy landscape representation in terms of reaction coordinates presents a daunting challenge. Here, our newly developed energy landscape visualization method (ELViM), a reaction coordinate-free approach, shows its prime application to explore frustrated energy landscapes of an intrinsically disordered protein, prostate-associated gene 4 (PAGE4). PAGE4 is a transcriptional coactivator that potentiates the oncogene c-Jun. Two kinases, namely, HIPK1 and CLK2, phosphorylate PAGE4, generating variants phosphorylated at different serine/threonine residues (HIPK1-PAGE4 and CLK2-PAGE4, respectively) with opposing functions. While HIPK1-PAGE4 predominantly phosphorylates Thr51 and potentiates c-Jun, CLK2-PAGE4 hyperphosphorylates PAGE4 and attenuates transactivation. To understand the underlying mechanisms of conformational diversity among different phosphoforms, we have analyzed their atomistic trajectories simulated using AWSEM forcefield, and the energy landscapes were elucidated using ELViM. This method allows us to identify and compare the population distributions of different conformational ensembles of PAGE4 phosphoforms using the same effective phase space. The results reveal a predominant conformational ensemble with an extended C-terminal segment of WT PAGE4, which exposes a functional residue Thr51, implying its potential of undertaking a fly-casting mechanism while binding to its cognate partner. In contrast, for HIPK1-PAGE4, a compact conformational ensemble enhances its population sequestering phosphorylated-Thr51. This clearly explains the experimentally observed weaker affinity of HIPK1-PAGE4 for c-Jun. ELViM appears as a powerful tool, especially to analyze the highly frustrated energy landscape representation of IDPs where appropriate reaction coordinates are hard to apprehend.

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

Recent advances in atomic molecular dynamics simulation of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) play important roles in cellular functions. The inherent structural heterogeneity of IDPs makes the high-resolution experimental characterization of IDPs extremely difficult. Molecular dynamics (MD) simulation could provide the atomic-level description of the structural and dynamic properties of IDPs. This perspective reviews the recent progress in atomic MD simulation studies of IDPs, including the development of force fields and sampling methods, as well as applications in IDP-involved protein-protein interactions. The employment of large-scale simulations and advanced sampling techniques allows more accurate estimation of the thermodynamics and kinetics of IDP-mediated protein interactions, and the holistic landscape of the binding process of IDPs is emerging.

Structure-based peptide design targeting intrinsically disordered proteins: Novel histone H4 and H2A peptidic inhibitors

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Intrinsically disordered proteins/protein regions (IDPs/IDPRs) are emerging drug targets.

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Lack of fast methods hinders the discovery of inhibitors for IDPs/ IDPRs.

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Fast and inexpensive structure-based approaches have been developed.

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The developed methods were applied to succesfully design inhibitors targeting the disordered tail of histone H4 and H2A.

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The presented methods can be widely used to identify inhibitors for other IDPs/IDPRs.

A growing body of research has demonstrated that targeting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) is feasible and represents a new trending strategy in drug discovery. However, the number of inhibitors targeting IDPs/IDPRs is increasing slowly due to limitations of the methods that can be used to accelerate the discovery process. We have applied structure-based methods to successfully develop the first peptidic inhibitor (HIPe - Histone Inhibitory Peptide) that targets histone H4 that are released from NETs (Neutrophil Extracellular Traps). HIPe binds stably to the disordered N-terminal tail of histone H4, thereby preventing histone H4-induced cell death. Recently, by utilisation of the same state-of-the-art approaches, we have developed a novel peptidic inhibitor (CHIP - Cyclical Histone H2A Interference Peptide) that binds to NET-resident histone H2A, which results in a blockade of monocyte adhesion and consequently reduction in atheroprogression. Here, we present comprehensive details on the computational methods utilised to design and develop HIPe and CHIP. We have exploited protein–protein complexes as starting structures for rational peptide design and then applied binding free energy methods to predict and prioritise binding strength of the designed peptides with histone H4 and H2A. By doing this way, we have modelled only around 20 peptides and from these were able to select 4–5 peptides, from a total of more than a trillion candidate peptides, for functional characterisation in different experiments. The developed computational protocols are generic and can be widely used to design and develop novel inhibitors for other disordered proteins.

Functional characterization of an unknown soybean intrinsically disordered protein in vitro and in Escherichia coli

Intrinsically disordered proteins (IDPs) possess a wide range of biological function in all organisms, however the specific functions of most IDPs are still unknown. Soybean LOC protein, LOC for short, is a heat-stable protein, which is more abundant in the stress-resistant radicles. Sequence alignment and phylogenetic analysis showed that LOC is a functionally unknown protein and conserved in Fabaceae. LOC, being enriched in most disorder-promoting residues and depleted in most order-promoting residues, was predicted to contain high levels of intrinsic disorder by several commonly used computational tools. However, it was also predicted to contain two disorder-based protein-protein binding sites and two short α-helical segments. The circular dichroism spectroscopic analysis showed that this protein is mostly disordered in water, but can form more α-helical structure in the presence of SDS and TFE. Functional in vitro studies showed that the LOC protein is able to prevent lactate dehydrogenase inactivation by freeze-thaw at a molar ratio of 10:1. Furthermore, in vivo analyses revealed the survival rate of Escherichia coli over-expressing LOC protein under the conditions of osmotic stress was noticeably increased in comparison with the control. These observations suggest that the intrinsically disordered protein LOC might serve as a chaperone and/or cell protector.

Critical assessment of protein intrinsic disorder prediction

Intrinsically disordered proteins, defying the traditional protein structure-function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F_max = 0.483 on the full dataset and F_max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F_max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.

The complexity of protein interactions unravelled from structural disorder

The importance of unstructured biology has quickly grown during the last decades accompanying the explosion of the number of experimentally resolved protein structures. The idea that structural disorder might be a novel mechanism of protein interaction is widespread in the literature, although the number of statistically significant structural studies supporting this idea is surprisingly low. At variance with previous works, our conclusions rely exclusively on a large-scale analysis of all the 134337 X-ray crystallographic structures of the Protein Data Bank averaged over clusters of almost identical protein sequences. In this work, we explore the complexity of the organisation of all the interaction interfaces observed when a protein lies in alternative complexes, showing that interfaces progressively add up in a hierarchical way, which is reflected in a logarithmic law for the size of the union of the interface regions on the number of distinct interfaces. We further investigate the connection of this complexity with different measures of structural disorder: the standard missing residues and a new definition, called "soft disorder", that covers all the flexible and structurally amorphous residues of a protein. We show evidences that both the interaction interfaces and the soft disordered regions tend to involve roughly the same amino-acids of the protein, and preliminary results suggesting that soft disorder spots those surface regions where new interfaces are progressively accommodated by complex formation. In fact, our results suggest that structurally disordered regions not only carry crucial information about the location of alternative interfaces within complexes, but also about the order of the assembly. We verify these hypotheses in several examples, such as the DNA binding domains of P53 and P73, the C3 exoenzyme, and two known biological orders of assembly. We finally compare our measures of structural disorder with several disorder bioinformatics predictors, showing that these latter are optimised to predict the residues that are missing in all the alternative structures of a protein and they are not able to catch the progressive evolution of the disordered regions upon complex formation. Yet, the predicted residues, when not missing, tend to be characterised as soft disordered regions.

A code within the genetic code: codon usage regulates co-translational protein folding

The genetic code is degenerate, and most amino acids are encoded by two to six synonymous codons. Codon usage bias, the preference for certain synonymous codons, is a universal feature of all genomes examined. Synonymous codon mutations were previously thought to be silent; however, a growing body evidence now shows that codon usage regulates protein structure and gene expression through effects on co-translational protein folding, translation efficiency and accuracy, mRNA stability, and transcription. Codon usage regulates the speed of translation elongation, resulting in non-uniform ribosome decoding rates on mRNAs during translation that is adapted to co-translational protein folding process. Biochemical and genetic evidence demonstrate that codon usage plays an important role in regulating protein folding and function in both prokaryotic and eukaryotic organisms. Certain protein structural types are more sensitive than others to the effects of codon usage on protein folding, and predicted intrinsically disordered domains are more prone to misfolding caused by codon usage changes than other domain types. Bioinformatic analyses revealed that gene codon usage correlates with different protein structures in diverse organisms, indicating the existence of a codon usage code for co-translational protein folding. This review focuses on recent literature on the role and mechanism of codon usage in regulating translation kinetics and co-translational protein folding.

Molecular Motors: Kif14's Disordered Dongle

Modern life is replete with function-expanding dongles, and life at the molecular scale is, it turns out, no exception. Hanging out of the back of the Kif14 molecular motor is an intrinsically disordered domain that gives it superpowers.

Interplay of Structural Disorder and Short Binding Elements in the Cellular Chaperone Function of Plant Dehydrin ERD14

Details of the functional mechanisms of intrinsically disordered proteins (IDPs) in living cells is an area not frequently investigated. Here, we dissect the molecular mechanism of action of an IDP in cells by detailed structural analyses based on an in-cell nuclear magnetic resonance experiment. We show that the ID stress protein (IDSP) A. thaliana Early Response to Dehydration (ERD14) is capable of protecting E. coli cells under heat stress. The overexpression of ERD14 increases the viability of E. coli cells from 38.9% to 73.9% following heat stress (50 °C × 15 min). We also provide evidence that the protection is mainly achieved by protecting the proteome of the cells. In-cell NMR experiments performed in E. coli cells show that the protective activity is associated with a largely disordered structural state with conserved, short sequence motifs (K- and H-segments), which transiently sample helical conformations in vitro and engage in partner binding in vivo. Other regions of the protein, such as its S segment and its regions linking and flanking the binding motifs, remain unbound and disordered in the cell. Our data suggest that the cellular function of ERD14 is compatible with its residual structural disorder in vivo.

Evolution of novel genes in three-spined stickleback populations

Eukaryotic genomes frequently acquire new protein-coding genes which may significantly impact an organism’s fitness. Novel genes can be created, for example, by duplication of large genomic regions or de novo, from previously non-coding DNA. Either way, creation of a novel transcript is an essential early step during novel gene emergence. Most studies on the gain-and-loss dynamics of novel genes so far have compared genomes between species, constraining analyses to genes that have remained fixed over long time scales. However, the importance of novel genes for rapid adaptation among populations has recently been shown. Therefore, since little is known about the evolutionary dynamics of transcripts across natural populations, we here study transcriptomes from several tissues and nine geographically distinct populations of an ecological model species, the three-spined stickleback. Our findings suggest that novel genes typically start out as transcripts with low expression and high tissue specificity. Early expression regulation appears to be mediated by gene-body methylation. Although most new and narrowly expressed genes are rapidly lost, those that survive and subsequently spread through populations tend to gain broader and higher expression levels. The properties of the encoded proteins, such as disorder and aggregation propensity, hardly change. Correspondingly, young novel genes are not preferentially under positive selection but older novel genes more often overlap with F_ST outlier regions. Taken together, expression of the surviving novel genes is rapidly regulated, probably via epigenetic mechanisms, while structural properties of encoded proteins are non-debilitating and might only change much later.

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.

Understanding the Binding Induced Folding of Intrinsically Disordered Proteins by Protein Engineering: Caveats and Pitfalls

Many proteins lack a well-defined three-dimensional structure in isolation. These proteins, typically denoted as intrinsically disordered proteins (IDPs), may display a characteristic disorder-to-order transition when binding their physiological partner(s). From an experimental perspective, it is of great importance to establish the general grounds to understand how such folding processes may be explored. Here we discuss the caveats and the pitfalls arising when applying to IDPs one of the key techniques to characterize the folding of globular proteins, the Φ value analysis. This method is based on measurements of the free energy changes of transition and native states upon conservative, non-disrupting, mutations. On the basis of available data, we reinforce the validity of Φ value analysis in the study of IDPs and suggest future experiments to further validate this powerful experimental method.

Targeting intrinsically disordered proteins involved in cancer

Intrinsically disordered proteins (IDPs) do not have a well-defined structure under physiological conditions, but they have key roles in cell signaling and regulation, and they are frequently related to the development of diseases, such as cancer and other malignancies. This has converted IDPs in attractive therapeutic targets; however, targeting IDPs is challenging because of their dynamic nature. In the last years, different experimental and computational approaches, as well as the combination of both, have been explored to identify molecules to target either the hot-spots or the allosteric sites of IDPs. In this review, we summarize recent developments in successful targeting of IDPs, all of which are involved in different cancer types. The strategies used to develop and design (or in one particular example, to repurpose) small molecules targeting IDPs are, in a global sense, similar to those used in well-folded proteins: (1) screening of chemically diverse or target-oriented compound libraries; or (2) study of the interfaces involved in recognition of their natural partners, and design of molecular candidates capable of binding to such binding interface. We describe the outcomes of using these approaches in targeting IDPs involved in cancer, in the view to providing insight, to target IDPs in general. In a broad sense, the designed small molecules seem to target the most hydrophobic regions of the IDPs, hampering macromolecule (DNA or protein)-IDP interactions; furthermore, in most of the molecule-IDP complexes described so far, the protein remains disordered.

Templated folding of intrinsically disordered proteins

Much of our current knowledge of biological chemistry is founded in the structure-function relationship, whereby sequence determines structure that determines function. Thus, the discovery that a large fraction of the proteome is intrinsically disordered, while being functional, has revolutionized our understanding of proteins and raised new and interesting questions. Many intrinsically disordered proteins (IDPs) have been determined to undergo a disorder-to-order transition when recognizing their physiological partners, suggesting that their mechanisms of folding are intrinsically different from those observed in globular proteins. However, IDPs also follow some of the classic paradigms established for globular proteins, pointing to important similarities in their behavior. In this review, we compare and contrast the folding mechanisms of globular proteins with the emerging features of binding-induced folding of intrinsically disordered proteins. Specifically, whereas disorder-to-order transitions of intrinsically disordered proteins appear to follow rules of globular protein folding, such as the cooperative nature of the reaction, their folding pathways are remarkably more malleable, due to the heterogeneous nature of their folding nuclei, as probed by analysis of linear free-energy relationship plots. These insights have led to a new model for the disorder-to-order transition in IDPs termed "templated folding," whereby the binding partner dictates distinct structural transitions en route to product, while ensuring a cooperative folding.

Choice of Force Field for Proteins Containing Structured and Intrinsically Disordered Regions

Biomolecular force fields optimized for globular proteins fail to properly reproduce properties of intrinsically disordered proteins. In particular, parameters of the water model need to be modified to improve applicability of the force fields to both ordered and disordered proteins. Here, we compared performance of force fields recommended for intrinsically disordered proteins in molecular dynamics simulations of three proteins differing in the content of ordered and disordered regions (two proteins consisting of a well-structured domain and of a disordered region with and without a transient helical motif and one disordered protein containing a region of increased helical propensity). The obtained molecular dynamics trajectories were used to predict measurable parameters, including radii of gyration of the proteins and chemical shifts, residual dipolar couplings, paramagnetic relaxation enhancement, and NMR relaxation data of their individual residues. The predicted quantities were compared with experimental data obtained within this study or published previously. The results showed that the NMR relaxation parameters, rarely used for benchmarking, are particularly sensitive to the choice of force-field parameters, especially those defining the water model. Interestingly, the TIP3P water model, leading to an artificial structural collapse, also resulted in unrealistic relaxation properties. The TIP4P-D water model, combined with three biomolecular force-field parameters for the protein part, significantly improved reliability of the simulations. Additional analysis revealed only one particular force field capable of retaining the transient helical motif observed in NMR experiments. The benchmarking protocol used in our study, being more sensitive to imperfections than the commonly used tests, is well suited to evaluate the performance of newly developed force fields.

Proteome-wide analysis of protein disorder in Triticum aestivum and Hordeum vulgare

There has been an increasing interest in Intrinsically Disordered Proteins (IDPs) ever since it was proven that they are ubiquitous and involved in key cellular functions. Interestingly, they have shown a large abundance in complete proteomes. In the current study, we have investigated the first large-scale study of the repertoire of IDPs in Triticum aestivum and Hordeum vulgare proteomes, in order to get insight into the biological roles of IDPs in both species. Results show that proteins in T. aestivum are significantly more disordered than those of H. vulgare. Moreover, the data revealed that DNA/RNA binding domains, co-factors, heme, metal ions binding domains, ATP/GTP binding proteins, ligands, linker domains and repeats, other domains typical to transcription factors such as zinc finger, F-box domain, homeodomain-like, l-domain like and chaperones, are predominantly present and co-occur in disordered proteins in T.aestivum and H.vulgare. The Gene Ontology analysis revealed that IDPs in T. aestivum and H. vulgare are mainly involved in regulation of cellular and biological processes up on response to stress. In future, this study may provide valuable information while considering IDPs in understanding the organism complexity and environmental adaptation.

NMR experiments on the transient interaction of the intrinsically disordered N-terminal peptide of cystathionine-β-synthase with heme

The N-terminal segment of human cystathionine-β-synthase (CBS(1-40)) constitutes an intrinsically disordered protein stretch that transiently interacts with heme. We illustrate that the HCBCACON experimental protocol provides an efficient alternative approach for probing transient interactions of intrinsically disordered proteins with heme in situations where the applicability of the conventional [¹H, ¹⁵N]-HSQC experiment may be limited. This experiment starting with the excitation of protein side chain protons delivers information about the proline residues and thereby makes it possible to use these residues in interaction mapping experiments. Employing this approach in conjunction with site-specific mutation we show that transient heme binding is mediated by the Cys¹⁵-Pro¹⁶ motif of CBS(1-40).

An intrinsically disordered proteins community for ELIXIR

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled “An intrinsically disordered protein user community proposal for ELIXIR” held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.

An arsenal of methods for the experimental characterization of intrinsically disordered proteins - How to choose and combine them?

In this review, we detail the most common experimental approaches to assess and characterize protein intrinsic structural disorder, with the notable exception of NMR and EPR spectroscopy, two ideally suited approaches that will be described in depth in two other reviews within this special issue. We discuss the advantages, the limitations, as well as the caveats of the various methods. We also describe less common and more demanding approaches that enable achieving further insights into the conformational properties of IDPs. Finally, we present recent developments that have enabled assessment of structural disorder in living cells, and discuss the currently available methods to model IDPs as conformational ensembles.

Binding induced folding: Lessons from the kinetics of interaction between NTAIL and XD

Intrinsically Disordered Proteins (IDPs) are a class of protein that exert their function despite lacking a well-defined three-dimensional structure, which is sometimes achieved only upon binding to their natural ligands. This feature implies the folding of IDPs to be generally coupled with a binding event, representing an interesting challenge for kinetic studies. In this review, we recapitulate some of the most important findings of IDPs binding-induced folding mechanisms obtained by analyzing their binding kinetics. Furthermore, by focusing on the interaction between the Measles virus N_TAIL protein, a prototypical IDP, and its physiological partner, the X domain, we recapitulate the major theoretical and experimental approaches that were used to describe binding induced folding.

OPAL: prediction of MoRF regions in intrinsically disordered protein sequences

Motivation

Intrinsically disordered proteins lack stable 3-dimensional structure and play a crucial role in performing various biological functions. Key to their biological function are the molecular recognition features (MoRFs) located within long disordered regions. Computationally identifying these MoRFs from disordered protein sequences is a challenging task. In this study, we present a new MoRF predictor, OPAL, to identify MoRFs in disordered protein sequences. OPAL utilizes two independent sources of information computed using different component predictors. The scores are processed and combined using common averaging method. The first score is computed using a component MoRF predictor which utilizes composition and sequence similarity of MoRF and non-MoRF regions to detect MoRFs. The second score is calculated using half-sphere exposure (HSE), solvent accessible surface area (ASA) and backbone angle information of the disordered protein sequence, using information from the amino acid properties of flanks surrounding the MoRFs to distinguish MoRF and non-MoRF residues.

Results

OPAL is evaluated using test sets that were previously used to evaluate MoRF predictors, MoRFpred, MoRFchibi and MoRFchibi-web. The results demonstrate that OPAL outperforms all the available MoRF predictors and is the most accurate predictor available for MoRF prediction. It is available at http://www.alok-ai-lab.com/tools/opal/.

Contact

ashwini@hgc.jp or alok.sharma@griffith.edu.au.

Supplementary information

Supplementary data are available at Bioinformatics online.

Functions of intrinsic disorder in proteins involved in DNA demethylation during pre-implantation embryonic development

DNA demethylation is involved in many biological processes during pre-implantation embryonic development in mammals. To date, the complicated mechanism of DNA demethylation is still not fully understood. Ten-eleven translocation family (TET3, TET1 and TET2), thymine DNA glycosylase (TDG) and DNA methyltransferase 1 (DNMT1) are considered the major protein enzymes of DNA demethylation in pre-implantation embryos. TET3, TET1, TET2, TDG, and DNMT1 contain abundant levels of intrinsically disordered protein regions (IDPRs), which contribute to increasing the functional diversity of proteins. Thus we tried to explore the complicated DNA demethylation in pre-implantation embryos from the intrinsic disorder perspective. These five biological macromolecules all have DNA demethylation-related functional domains. They can work together to fulfill DNA demethylation in pre-implantation embryos through complex protein-protein interaction networks. Intrinsic disorder analysis results showed these proteins were partial intrinsically disordered proteins. Many identifiable disorder-based DNA-binding sites, protein-binding sites and post-translational modification sites located in the intrinsically disordered regions, and DNA demethylation deficiency point mutations in the IDPRs could significantly change the local disorder propensity of these proteins. To the best of our knowledge, this work provides a new viewpoint for studying the mechanism of DNA methylation reprogramming during mammalian pre-implantation embryonic development.

How Robust Is the Mechanism of Folding-Upon-Binding for an Intrinsically Disordered Protein?

The mechanism of interaction of an intrinsically disordered protein (IDP) with its physiological partner is characterized by a disorder-to-order transition in which a recognition and a binding step take place. Even if the mechanism is quite complex, IDPs tend to bind their partner in a cooperative manner such that it is generally possible to detect experimentally only the disordered unbound state and the structured complex. The interaction between the disordered C-terminal domain of the measles virus nucleoprotein (N_TAIL) and the X domain (XD) of the viral phosphoprotein allows us to detect and quantify the two distinct steps of the overall reaction. Here, we analyze the robustness of the folding of N_TAIL upon binding to XD by measuring the effect on both the folding and binding steps of N_TAIL when the structure of XD is modified. Because it has been shown that wild-type XD is structurally heterogeneous, populating an on-pathway intermediate under native conditions, we investigated the binding to 11 different site-directed variants of N_TAIL of one particular variant of XD (I504A XD) that populates only the native state. Data reveal that the recognition and the folding steps are both affected by the structure of XD, indicating a highly malleable pathway. The experimental results are briefly discussed in the light of previous experiments on other IDPs.