Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life

Physical Chemistry of the Protein Backbone: Enabling the Mechanisms of Intrinsic Protein Disorder

Over the last two decades it has become clear that well-defined structure is not a requisite for proteins to properly function. Rather, spectra of functionally competent, structurally disordered states have been uncovered requiring canonical paradigms in molecular biology to be revisited or reimagined. It is enticing and oftentimes practical to divide the proteome into structured and unstructured, or disordered, proteins. While function, composition, and structural properties largely differ, these two classes of protein are built upon the same scaffold, namely, the protein backbone. The versatile physicochemical properties of the protein backbone must accommodate structural disorder, order, and transitions between these states. In this review, we survey these properties through the conceptual lenses of solubility and conformational populations and in the context of protein-disorder mediated phenomena (e.g., phase separation, order-disorder transitions, allostery). Particular attention is paid to the results of computational studies, which, through thermodynamic decomposition and dissection of molecular interactions, can provide valuable mechanistic insight and testable hypotheses to guide further solution experiments. Lastly, we discuss changes in the dynamics of side chains and order-disorder transitions of the protein backbone as two modes or realizations of "entropic reservoirs" capable of tuning coupled thermodynamic processes.

Structural and functional analysis of "non-smelly" proteins

Cysteine and aromatic residues are major structure-promoting residues. We assessed the abundance, structural coverage, and functional characteristics of the "non-smelly" proteins, i.e., proteins that do not contain cysteine residues (C-depleted) or cysteine and aromatic residues (CFYWH-depleted), across 817 proteomes from all domains of life. The analysis revealed that although these proteomes contained significant levels of the C-depleted proteins, with prokaryotes being significantly more enriched in such proteins than eukaryotes, the CFYWH-depleted proteins were relatively rare, accounting for about 0.05% of proteomes. Furthermore, CFYWH-depleted proteins were virtually never found in PDB. Depletion in cysteine and in aromatic residues was associated with the substantially increased intrinsic disorder levels across all domains of life. Archaeal and eukaryotic organisms with higher levels of the C-depleted proteins were shown to have higher levels of the intrinsic disorder and lower levels of structural coverage. We also showed that the "non-smelly" proteins typically did not independently fold into monomeric structures, and instead, they fold by interacting with nucleic acids as constituents of the ribosome and nucleosome complexes. They were shown to be involved in translation, transcription, nucleosome assembly, transmembrane transport, and protein folding functions, all of which are known to be associated with the intrinsic disorder. Our data suggested that, in general, structure of monomeric proteins is crucially dependent on the presence of cysteine and aromatic residues.

Intrinsic Disorder in Tetratricopeptide Repeat Proteins

Among the realm of repeat containing proteins that commonly serve as “scaffolds” promoting protein-protein interactions, there is a family of proteins containing between 2 and 20 tetratricopeptide repeats (TPRs), which are functional motifs consisting of 34 amino acids. The most distinguishing feature of TPR domains is their ability to stack continuously one upon the other, with these stacked repeats being able to affect interaction with binding partners either sequentially or in combination. It is known that many repeat-containing proteins are characterized by high levels of intrinsic disorder, and that many protein tandem repeats can be intrinsically disordered. Furthermore, it seems that TPR-containing proteins share many characteristics with hybrid proteins containing ordered domains and intrinsically disordered protein regions. However, there has not been a systematic analysis of the intrinsic disorder status of TPR proteins. To fill this gap, we analyzed 166 human TPR proteins to determine the degree to which proteins containing TPR motifs are affected by intrinsic disorder. Our analysis revealed that these proteins are characterized by different levels of intrinsic disorder and contain functional disordered regions that are utilized for protein-protein interactions and often serve as targets of various posttranslational modifications.

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

Post-translational modifications (PTMs) play very important roles in various cell signaling pathways and biological process. Due to PTMs' extremely important roles, many major PTMs have been studied, while the functional and mechanical characterization of major PTMs is well documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17 145 non-redundant modification sites on 3919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features and PTM sites' data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence-structural-functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript and HTML with all major browsers supported.

Quality assessment for the putative intrinsic disorder in proteins

MOTIVATION

While putative intrinsic disorder is widely used, none of the predictors provides quality assessment (QA) scores. QA scores estimate the likelihood that predictions are correct at a residue level and have been applied in other bioinformatics areas. We recently reported that QA scores derived from putative disorder propensities perform relatively poorly for native disordered residues. Here we design and validate a general approach to construct QA predictors for disorder predictions.

RESULTS

The QUARTER (QUality Assessment for pRotein inTrinsic disordEr pRedictions) toolbox of methods accommodates a diverse set of ten disorder predictors. It builds upon several innovative design elements including use and scaling of selected physicochemical properties of the input sequence, post-processing of disorder propensity scores, and a feature selection that optimizes the predictive models to a specific disorder predictor. We empirically establish that each one of these elements contributes to the overall predictive performance of our tool and that QUARTER's outputs significantly outperform QA scores derived from the outputs generated the disorder predictors. The best performing QA scores for a single disorder predictor identify 13% of residues that are predicted with 98% precision. QA scores computed by combining results of the ten disorder predictors cover 40% of residues with 95% precision. Case studies are used to show how to interpret the QA scores. QA scores based on the high precision combined predictions are applied to analyze disorder in the human proteome.

AVAILABILITY AND IMPLEMENTATION

http://biomine.cs.vcu.edu/servers/QUARTER/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protein promiscuity in drug discovery, drug-repurposing and antibiotic resistance

Proteins are supposed to bind to their substrates/ligands in a specific manner via their pre-formed binding sites, according to classical biochemistry. In recent years, several types of deviations from this norm have been observed and called promiscuous behavior. Enzymatic promiscuities allow several biochemical functions to be carried out by the same enzyme. The promiscuous activity can also be the origin of "new proteins" via gene duplication. In more recent years, proteins from prokaryotes, eukaryotes and viruses have been found to have intrinsic disorder and lack a preformed binding site. Intrinsic disorder is exploited in regulatory proteins such as those that are involved in transcription and signal transduction. Such proteins function by folding locally while binding to their ligands or interacting with other proteins. These phenomena have also been classified as examples of protein promiscuity and encompass diverse kinds of ligands that can bind to a protein. Given the significant extent of structural homology in many protein families, it is not surprising that ligands also have been found to display promiscuity. Promiscuous behavior of proteins offers both challenges and opportunities to the drug discovery programs such as drug repurposing. Pathogens when exposed to antibiotics exploit protein promiscuity in several ways to develop resistance to the drug. There is increasing evidence now to support that the disorder in proteins is a major tool used by pathogens for virulence and evade drug action by exploiting protein promiscuity. This review provides a holistic view of this multi-faceted phenomenon called protein promiscuity.

Intrinsically disordered regions are abundant in simplexvirus proteomes and display signatures of positive selection

Whereas the majority of herpesviruses co-speciated with their mammalian hosts, human herpes simplex virus 2 (HSV-2, genus Simplexvirus) most likely originated from the cross-species transmission of chimpanzee herpesvirus 1 to an ancestor of modern humans. We exploited the peculiar evolutionary history of HSV-2 to investigate the selective events that drove herpesvirus adaptation to a new host. We show that HSV-2 intrinsically disordered regions (IDRs)-that is, protein domains that do not adopt compact three-dimensional structures-are strongly enriched in positive selection signals. Analysis of viral proteomes indicated that a significantly higher portion of simplexvirus proteins is disordered compared with the proteins of other human herpesviruses. IDR abundance in simplexvirus proteomes was not a consequence of the base composition of their genomes (high G + C content). Conversely, protein function determines the IDR fraction, which is significantly higher in viral proteins that interact with human factors. We also found that the average extent of disorder in herpesvirus proteins tends to parallel that of their human interactors. These data suggest that viruses that interact with fast-evolving, disordered human proteins, in turn, evolve disordered viral interactors poised for innovation. We propose that the high IDR fraction present in simplexvirus proteomes contributes to their wider host range compared with other herpesviruses.

Robosample: A rigid-body molecular simulation program based on robot mechanics

BACKGROUND

Compared with all-atom molecular dynamics (MD), constrained MD methods allow for larger time steps, potentially reducing computational cost. For this reason, there has been continued interest in improving constrained MD algorithms to increase configuration space sampling in molecular simulations.

METHODS

Here, we introduce Robosample, a software package that implements high-performance constrained dynamics algorithms, originally developed for robotics, and applies them to simulations of biomolecular systems. As in the gMolmodel package developed by Spiridon and Minh in 2017, Robosample uses Constrained Dynamics Hamiltonian Monte Carlo (CDHMC) as a Gibbs sampling move - a type of Monte Carlo move where a subset of coordinates is allowed to change. In addition to the previously described Cartesian and torsional dynamics moves, Robosample implements spherical and cylindrical joints that can be distributed along the molecule by the user.

RESULTS

In alanine dipeptide simulations, the free energy surface is recovered by mixing fully flexible with torsional, cylindrical, or spherical dynamics moves. Ramachandran dynamics, where only the two key torsions are mobile, accelerate the slowest transition by an order of magnitude. We also show that simulations of a complex glycan cover significantly larger regions of the configuration space when mixed with constrained dynamics.

MAJOR CONCLUSIONS

Robosample is a tool of choice for efficient conformational sampling of large biomolecules.

GENERAL SIGNIFICANCE

Robosample is intended as a reliable and user-friendly simulation package for fast biomolecular sampling that does not require extensive expertise in mechanical engineering or in the statistical mechanics of reduced coordinates.

Intrinsically disordered proteins of viruses: Involvement in the mechanism of cell regulation and pathogenesis

Intrinsically disordered proteins (IDPs) possess the property of inherent flexibility and can be distinguished from other proteins in terms of lack of any fixed structure. Such dynamic behavior of IDPs earned the name "Dancing Proteins." The exploration of these dancing proteins in viruses has just started and crucial details such as correlation of rapid evolution, high rate of mutation and accumulation of disordered contents in viral proteome at least understood partially. In order to gain a complete understanding of this correlation, there is a need to decipher the complexity of viral mediated cell hijacking and pathogenesis in the host organism. Further there is necessity to identify the specific patterns within viral and host IDPs such as aggregation; Molecular recognition features (MoRFs) and their association to virulence, host range and rate of evolution of viruses in order to tackle the viral-mediated diseases. The current book chapter summarizes the aforementioned details and suggests the novel opportunities for further research of IDPs senses in viruses.

Torches, Candles, Lamps, Lanterns, Flashlights, Spotlights, Night Vision Goggles… You Need Them All to See in Darkness

Articles assembled in the second part of this Special Issue describe some experimental and computational approaches for the structural and functional characterization of intrinsically disordered proteins. Since these tools represent specialized gear for the focused analysis of various aspects of dark proteome, they can be viewed as torches, candles, lamps, lanterns, flashlights, spotlights, night vision goggles, and other means needed to see in darkness.

SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning

Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination of intrinsic disorder and the exponential increase of unannotated protein sequences, developing complementary computational prediction methods has been an active area of research for several decades. Here, we employed an ensemble of deep Squeeze-and-Excitation residual inception and long short-term memory (LSTM) networks for predicting protein intrinsic disorder with input from evolutionary information and predicted one-dimensional structural properties. The method, called SPOT-Disorder2, offers substantial and consistent improvement not only over our previous technique based on LSTM networks alone, but also over other state-of-the-art techniques in three independent tests with different ratios of disordered to ordered amino acid residues, and for sequences with either rich or limited evolutionary information. More importantly, semi-disordered regions predicted in SPOT-Disorder2 are more accurate in identifying molecular recognition features (MoRFs) than methods directly designed for MoRFs prediction. SPOT-Disorder2 is available as a web server and as a standalone program at https://sparks-lab.org/server/spot-disorder2/.

New technologies to analyse protein function: an intrinsic disorder perspective

Functions of intrinsically disordered proteins do not require structure. Such structure-independent functionality has melted away the classic rigid "lock and key" representation of structure-function relationships in proteins, opening a new page in protein science, where molten keys operate on melted locks and where conformational flexibility and intrinsic disorder, structural plasticity and extreme malleability, multifunctionality and binding promiscuity represent a new-fangled reality. Analysis and understanding of this new reality require novel tools, and some of the techniques elaborated for the examination of intrinsically disordered protein functions are outlined in this review.

Analysis of a Nuclear Intrinsically Disordered Proteome

Intrinsically disordered proteins (IDPs) play crucial roles in cell functioning, although they do not possess defined three-dimensional architecture. They are highly abundant in the cell nucleus, and the vast majority of transcription factors (TFs) contain extended regions of intrinsic disorder. IDPs do not respond to denaturing conditions in a standard manner, and this can be used for their separation from structured proteins. Here we describe a protocol for the isolation and characterization of nuclear IDPs in which heat treatment is used for enrichment of IDPs in samples. The whole workflow comprises the following steps: nuclei isolation from HEK293 (human embryonic kidney) cells, protein extraction, enrichment of IDPs, sample preparation for mass spectrometric analysis, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, in silico assessment of protein disorder, and Gene Ontology analysis.

Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor

Intrinsically disordered proteins are either entirely disordered or contain disordered regions in their native state. These proteins and regions function without the prerequisite of a stable structure and were found to be abundant across all kingdoms of life. Experimental annotation of disorder lags behind the rapidly growing number of sequenced proteins, motivating the development of computational methods that predict disorder in protein sequences. DisCoP is a user-friendly webserver that provides accurate sequence-based prediction of protein disorder. It relies on meta-architecture in which the outputs generated by multiple disorder predictors are combined together to improve predictive performance. The architecture of disCoP is presented, and its accuracy relative to several other disorder predictors is briefly discussed. We describe usage of the web interface and explain how to access and read results generated by this computational tool. We also provide an example of prediction results and interpretation. The disCoP's webserver is publicly available at http://biomine.cs.vcu.edu/servers/disCoP/ .

Potyviral coat protein and genomic RNA: A striking partnership leading virion assembly and more

Potyvirus genus clusters a significant and expanding number of widely distributed plant viruses, responsible for large losses impacting most crops of economic interest. The potyviral genome is a single-stranded, linear, positive-sense RNA of around 10kb that is encapsidated in flexuous rod-shaped filaments, mostly made up of a helically arranged coat protein (CP). Beyond its structural role of protecting the viral genome, the potyviral CP is a multitasking protein intervening in practically all steps of the virus life cycle. In particular, interactions between the CP and the viral RNA must be tightly controlled to allow the correct assignment of the RNA to each of its functions through the infection process. This review attempts to bring together the most relevant available information regarding the architecture and modus operandi of potyviral CP and virus particles, highlighting significant discoveries, but also substantial gaps in the existing knowledge on mechanisms orchestrating virion assembly and disassembly. Biotechnological applications based on potyvirus nanoparticles is another important topic addressed here.

Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins

Protein-coding nucleic acids exhibit composition and codon biases between sequences coding for intrinsically disordered regions (IDRs) and those coding for structured regions. IDRs are regions of proteins that are folding self-insufficient and which function without the prerequisite of folded structure. Several authors have investigated composition bias or codon selection in regions encoding for IDRs, primarily in Eukaryota, and concluded that elevated GC content is the result of the biased amino acid composition of IDRs. We substantively extend previous work by examining GC content in regions encoding IDRs, from 44 species in Eukaryota, Archaea, and Bacteria, spanning a wide range of GC content. We confirm that regions coding for IDRs show a significantly elevated GC content, even across all domains of life. Although this is largely attributable to the amino acid composition bias of IDRs, we show that this bias is independent of the overall GC content and, most importantly, we are the first to observe that GC content bias in IDRs is significantly different than expected from IDR amino acid composition alone. We empirically find compensatory codon selection that reduces the observed GC content bias in IDRs. This selection is dependent on the overall GC content of the organism. The codon selection bias manifests as use of infrequent, AT-rich codons in encoding IDRs. Further, we find these relationships to be independent of the intrinsic disorder prediction method used, and independent of estimated translation efficiency. These observations are consistent with the previous work, and we speculate on whether the observed biases are causal or symptomatic of other driving forces.

Analyzing IDPs in Interactomes

Intrinsically disordered proteins (IDPs) and regions (IDRs) are commonly found in all proteomes analyzed so far. These proteins/regions are subject to numerous posttranslational modifications (PTMs) and alternative splicing, are involved in a wide range of cellular functions, and often facilitate protein-protein interactions (PPIs). Some of these proteins contain molecular recognition features (MoRFs), which are IDRs that bind to partner proteins and undergo disorder-to-order transitions. Although many IDPs/IDRs can fold upon binding, a large fraction of these proteins are known to maintain significant amounts of disorder in their bound states. Being well-recognized interaction specialists, IDPs/IDRs can participate in one-to-many and many-to-one interactions, where one IDP/IDR binds to multiple partners potentially gaining very different structures in the bound state, or where multiple unrelated IDPs/IDRs bind to one partner. As a result, IDPs frequently serve as hubs (i.e., proteins with many links) in complex PPI networks. The goal of this chapter is to describe computational and bioinformatics tools that can be used to look at the disorder status of proteins within a given PPI network and also to gain some knowledge on the disorder-based functionality of the members of this network. To this end, description is provided for some of the use of UniProt and DisProt databases, several databases generating PPI networks (BioGRID, IntAct, DIP, MINT, HPRD, APID, KEGG, and STRING), Composition profiler, some tools for the per-residue disorder predictions (PONDR^® VLXT, PONDR^® VL3, PONDR^® VSL2, PONDR-FIT, and IUPred), binary disorder classifiers CH-plot and CDF-plot and their combined CH-CDF analysis, web-based tools for the visualization of disorder distribution in a query protein (D²P² and MobiDB), as well as some tools for evaluation disorder-based functionality of proteins (ANCHOR, MoRFpred, DEPP, and ModPred).

Prediction of Intrinsic Disorder with Quality Assessment Using QUARTER

Intrinsically disordered regions (IDRs) are estimated to be highly abundant in nature. While only several thousand proteins are annotated with experimentally derived IDRs, computational methods can be used to predict IDRs for the millions of currently uncharacterized protein chains. Several dozen disorder predictors were developed over the last few decades. While some of these methods provide accurate predictions, unavoidably they also make some mistakes. Consequently, one of the challenges facing users of these methods is how to decide which predictions can be trusted and which are likely incorrect. This practical problem can be solved using quality assessment (QA) scores that predict correctness of the underlying (disorder) predictions at a residue level. We motivate and describe a first-of-its-kind toolbox of QA methods, QUARTER (QUality Assessment for pRotein inTrinsic disordEr pRedictions), which provides the scores for a diverse set of ten disorder predictors. QUARTER is available to the end users as a free and convenient webserver at http://biomine.cs.vcu.edu/servers/QUARTER/ . We briefly describe the predictive architecture of QUARTER and provide detailed instructions on how to use the webserver. We also explain how to interpret results produced by QUARTER with the help of a case study.

DISOselect: Disorder predictor selection at the protein level

The intense interest in the intrinsically disordered proteins in the life science community, together with the remarkable advancements in predictive technologies, have given rise to the development of a large number of computational predictors of intrinsic disorder from protein sequence. While the growing number of predictors is a positive trend, we have observed a considerable difference in predictive quality among predictors for individual proteins. Furthermore, variable predictor performance is often inconsistent between predictors for different proteins, and the predictor that shows the best predictive performance depends on the unique properties of each protein sequence. We propose a computational approach, DISOselect, to estimate the predictive performance of 12 selected predictors for individual proteins based on their unique sequence-derived properties. This estimation informs the users about the expected predictive quality for a selected disorder predictor and can be used to recommend methods that are likely to provide the best quality predictions. Our solution does not depend on the results of any disorder predictor; the estimations are made based solely on the protein sequence. Our solution significantly improves predictive performance, as judged with a test set of 1,000 proteins, when compared to other alternatives. We have empirically shown that by using the recommended methods the overall predictive performance for a given set of proteins can be improved by a statistically significant margin. DISOselect is freely available for non-commercial users through the webserver at http://biomine.cs.vcu.edu/servers/DISOselect/.

DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server

Computational predictions of the intrinsic disorder and its functions are instrumental to facilitate annotation for the millions of unannotated proteins. However, access to these predictors is fragmented and requires substantial effort to find them and to collect and combine their results. The DEPICTER (DisorderEd PredictIon CenTER) server provides first-of-its-kind centralized access to 10 popular disorder and disorder function predictions that cover protein and nucleic acids binding, linkers, and moonlighting regions. It automates the prediction process, runs user-selected methods on the server side, visualizes the results, and outputs all predictions in a consistent and easy-to-parse format. DEPICTER also includes two accurate consensus predictors of disorder and disordered protein binding. Empirical tests on an independent (low similarity) benchmark dataset reveal that the computational tools included in DEPICTER generate accurate predictions that are significantly better than the results secured using sequence alignment. The DEPICTER server is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER/.

Life in Phases: Intra- and Inter- Molecular Phase Transitions in Protein Solutions

Proteins, these evolutionarily-edited biological polymers, are able to undergo intramolecular and intermolecular phase transitions. Spontaneous intramolecular phase transitions define the folding of globular proteins, whereas binding-induced, intra- and inter- molecular phase transitions play a crucial role in the functionality of many intrinsically-disordered proteins. On the other hand, intermolecular phase transitions are the behind-the-scenes players in a diverse set of macrosystemic phenomena taking place in protein solutions, such as new phase nucleation in bulk, on the interface, and on the impurities, protein crystallization, protein aggregation, the formation of amyloid fibrils, and intermolecular liquid-liquid or liquid-gel phase transitions associated with the biogenesis of membraneless organelles in the cells. This review is dedicated to the systematic analysis of the phase behavior of protein molecules and their ensembles, and provides a description of the major physical principles governing intramolecular and intermolecular phase transitions in protein solutions.

Sequence-Derived Markers of Drug Targets and Potentially Druggable Human Proteins

Recent research shows that majority of the druggable human proteome is yet to be annotated and explored. Accurate identification of these unexplored druggable proteins would facilitate development, screening, repurposing, and repositioning of drugs, as well as prediction of new drug–protein interactions. We contrast the current drug targets against the datasets of non-druggable and possibly druggable proteins to formulate markers that could be used to identify druggable proteins. We focus on the markers that can be extracted from protein sequences or names/identifiers to ensure that they can be applied across the entire human proteome. These markers quantify key features covered in the past works (topological features of PPIs, cellular functions, and subcellular locations) and several novel factors (intrinsic disorder, residue-level conservation, alternative splicing isoforms, domains, and sequence-derived solvent accessibility). We find that the possibly druggable proteins have significantly higher abundance of alternative splicing isoforms, relatively large number of domains, higher degree of centrality in the protein-protein interaction networks, and lower numbers of conserved and surface residues, when compared with the non-druggable proteins. We show that the current drug targets and possibly druggable proteins share involvement in the catalytic and signaling functions. However, unlike the drug targets, the possibly druggable proteins participate in the metabolic and biosynthesis processes, are enriched in the intrinsic disorder, interact with proteins and nucleic acids, and are localized across the cell. To sum up, we formulate several markers that can help with finding novel druggable human proteins and provide interesting insights into the cellular functions and subcellular locations of the current drug targets and potentially druggable proteins.

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

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

Multi-functionality of proteins involved in GPCR and G protein signaling: making sense of structure-function continuum with intrinsic disorder-based proteoforms

GPCR-G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signaling cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand-GPCR and GPCR-G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defines an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR-G protein system represents an illustrative example of the protein structure-function continuum, where structures of the involved proteins represent a complex mosaic of differently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fine-tuned by various post-translational modifications and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specific partners. In other words, GPCRs and G proteins exist as sets of conformational/basic, inducible/modified, and functioning proteoforms characterized by a broad spectrum of structural features and possessing various functional potentials.

The Significance of the Intrinsically Disordered Regions for the Functions of the bHLH Transcription Factors

The bHLH proteins are a family of eukaryotic transcription factors regulating expression of a wide range of genes involved in cell differentiation and development. They contain the Helix-Loop-Helix (HLH) domain, preceded by a stretch of basic residues, which are responsible for dimerization and binding to E-box sequences. In addition to the well-preserved DNA-binding bHLH domain, these proteins may contain various additional domains determining the specificity of performed transcriptional regulation. According to this, the family has been divided into distinct classes. Our aim was to emphasize the significance of existing disordered regions within the bHLH transcription factors for their functionality. Flexible, intrinsically disordered regions containing various motives and specific sequences allow for multiple interactions with transcription co-regulators. Also, based on in silico analysis and previous studies, we hypothesize that the bHLH proteins have a general ability to undergo spontaneous phase separation, forming or participating into liquid condensates which constitute functional centers involved in transcription regulation. We shortly introduce recent findings on the crucial role of the thermodynamically liquid-liquid driven phase separation in transcription regulation by disordered regions of regulatory proteins. We believe that further experimental studies should be performed in this field for better understanding of the mechanism of gene expression regulation (among others regarding oncogenes) by important and linked to many diseases the bHLH transcription factors.

Intrinsic Disorder of the BAF Complex: Roles in Chromatin Remodeling and Disease Development

The two-meter-long DNA is compressed into chromatin in the nucleus of every cell, which serves as a significant barrier to transcription. Therefore, for processes such as replication and transcription to occur, the highly compacted chromatin must be relaxed, and the processes required for chromatin reorganization for the aim of replication or transcription are controlled by ATP-dependent nucleosome remodelers. One of the most highly studied remodelers of this kind is the BRG1- or BRM-associated factor complex (BAF complex, also known as SWItch/sucrose non-fermentable (SWI/SNF) complex), which is crucial for the regulation of gene expression and differentiation in eukaryotes. Chromatin remodeling complex BAF is characterized by a highly polymorphic structure, containing from four to 17 subunits encoded by 29 genes. The aim of this paper is to provide an overview of the role of BAF complex in chromatin remodeling and also to use literature mining and a set of computational and bioinformatics tools to analyze structural properties, intrinsic disorder predisposition, and functionalities of its subunits, along with the description of the relations of different BAF complex subunits to the pathogenesis of various human diseases.

Accuracy of protein-level disorder predictions

Experimental annotations of intrinsic disorder are available for 0.1% of 147 000 000 of currently sequenced proteins. Over 60 sequence-based disorder predictors were developed to help bridge this gap. Current benchmarks of these methods assess predictive performance on datasets of proteins; however, predictions are often interpreted for individual proteins. We demonstrate that the protein-level predictive performance varies substantially from the dataset-level benchmarks. Thus, we perform first-of-its-kind protein-level assessment for 13 popular disorder predictors using 6200 disorder-annotated proteins. We show that the protein-level distributions are substantially skewed toward high predictive quality while having long tails of poor predictions. Consequently, between 57% and 75% proteins secure higher predictive performance than the currently used dataset-level assessment suggests, but as many as 30% of proteins that are located in the long tails suffer low predictive performance. These proteins typically have relatively high amounts of disorder, in contrast to the mostly structured proteins that are predicted accurately by all 13 methods. Interestingly, each predictor provides the most accurate results for some number of proteins, while the best-performing at the dataset-level method is in fact the best for only about 30% of proteins. Moreover, the majority of proteins are predicted more accurately than the dataset-level performance of the most accurate tool by at least four disorder predictors. While these results suggests that disorder predictors outperform their current benchmark performance for the majority of proteins and that they complement each other, novel tools that accurately identify the hard-to-predict proteins and that make accurate predictions for these proteins are needed.

Supramolecular Fuzziness of Intracellular Liquid Droplets: Liquid-Liquid Phase Transitions, Membrane-Less Organelles, and Intrinsic Disorder

Cells are inhomogeneously crowded, possessing a wide range of intracellular liquid droplets abundantly present in the cytoplasm of eukaryotic and bacterial cells, in the mitochondrial matrix and nucleoplasm of eukaryotes, and in the chloroplast’s stroma of plant cells. These proteinaceous membrane-less organelles (PMLOs) not only represent a natural method of intracellular compartmentalization, which is crucial for successful execution of various biological functions, but also serve as important means for the processing of local information and rapid response to the fluctuations in environmental conditions. Since PMLOs, being complex macromolecular assemblages, possess many characteristic features of liquids, they represent highly dynamic (or fuzzy) protein–protein and/or protein–nucleic acid complexes. The biogenesis of PMLOs is controlled by specific intrinsically disordered proteins (IDPs) and hybrid proteins with ordered domains and intrinsically disordered protein regions (IDPRs), which, due to their highly dynamic structures and ability to facilitate multivalent interactions, serve as indispensable drivers of the biological liquid–liquid phase transitions (LLPTs) giving rise to PMLOs. In this article, the importance of the disorder-based supramolecular fuzziness for LLPTs and PMLO biogenesis is discussed.

Intrinsically Disordered Transactivation Domains Bind to TAZ1 Domain of CBP via Diverse Mechanisms

CREB-binding protein is a multidomain transcriptional coactivator whose transcriptional adaptor zinc-binding 1 (TAZ1) domain mediates interactions with a number of intrinsically disordered transactivation domains (TADs), including the CREB-binding protein/p300-interacting transactivator with ED-rich tail, the hypoxia inducible factor 1α, p53, the signal transducer and activator of transcription 2, and the NF-κB p65 subunit. These five disordered TADs undergo partial disorder-to-order transitions upon binding TAZ1, forming fuzzy complexes with helical segments. Interestingly, they wrap around TAZ1 with different orientations and occupy the binding sites with various orders. To elucidate the microscopic molecular details of the binding processes of TADs with TAZ1, in this work, we carried out extensive molecular dynamics simulations using a coarse-grained topology-based model. After careful calibration of the models to reproduce the residual helical contents and binding affinities, our simulations were able to recapitulate the experimentally observed flexibility profiles. Although great differences exist in the complex structures, we found similarities between hypoxia inducible factor 1α and signal transducer and activator of transcription 2 as well as between CREB-binding protein/p300-interacting transactivator with ED-rich tail and NF-κB p65 subunit in the binding kinetics and binding thermodynamics. Although the origins of similarities and differences in the binding mechanisms remain unclear, our results provide some clues that indicate that binding of TADs to TAZ1 could be templated by the target as well as encoded by the TADs.

Intrinsically disordered proteins and structured proteins with intrinsically disordered regions have different functional roles in the cell

Many studies about classification and the functional annotation of intrinsically disordered proteins (IDPs) are based on either the occurrence of long disordered regions or the fraction of disordered residues in the sequence. Taking into account both criteria we separate the human proteome, taken as a case study, into three variants of proteins: i) ordered proteins (ORDPs), ii) structured proteins with intrinsically disordered regions (IDPRs), and iii) intrinsically disordered proteins (IDPs). The focus of this work is on the different functional roles of IDPs and IDPRs, which up until now have been generally considered as a whole. Previous studies assigned a large set of functional roles to the general category of IDPs. We show here that IDPs and IDPRs have non-overlapping functional spectra, play different roles in human diseases, and deserve to be treated as distinct categories of proteins. IDPs enrich only a few classes, functions, and processes: nucleic acid binding proteins, chromatin binding proteins, transcription factors, and developmental processes. In contrast, IDPRs are spread over several functional protein classes and GO annotations which they partly share with ORDPs. As regards to diseases, we observe that IDPs enrich only cancer-related proteins, at variance with previous results reporting that IDPs are widespread also in cardiovascular and neurodegenerative pathologies. Overall, the operational separation of IDPRs from IDPs is relevant towards correct estimates of the occurrence of intrinsically disordered proteins in genome-wide studies and in the understanding of the functional spectra associated to different flavors of protein disorder.

Orchestration of algal metabolism by protein disorder

Intrinsically disordered proteins (IDPs) are proteins that provide many functional advantages in a large number of metabolic and signalling pathways. Because of their high flexibility that endows them with pressure-, heat- and acid-resistance, IDPs are valuable metabolic regulators that help algae to cope with extreme conditions of pH, temperature, pressure and light. They have, however, been overlooked in these organisms. In this review, we present some well-known algal IDPs, including the conditionally disordered CP12, a protein involved in the regulation of CO₂ assimilation, as probably the best known example, whose disorder content is strongly dependent on the redox conditions, and the essential pyrenoid component 1 that serves as a scaffold for ribulose-1, 5-bisphosphate carboxylase/oxygenase. We also describe how some enzymes are regulated by protein regions, called intrinsically disordered regions (IDRs), such as ribulose-1, 5-bisphosphate carboxylase/oxygenase activase, the A₂B₂ form of glyceraldehyde-3-phosphate dehydrogenase and the adenylate kinase. Several molecular chaperones, which are crucial for cell proteostasis, also display significant disorder propensities such as the algal heat shock proteins HSP33, HSP70 and HSP90. This review confirms the wide distribution of IDPs in algae but highlights that further studies are needed to uncover their full role in orchestrating algal metabolism.

Repeatability in protein sequences

Low complexity regions (LCRs) in protein sequences have special properties that are very different from those of globular proteins. The rules that define secondary structure elements do not apply when the distribution of amino acids becomes biased. While there is a tendency towards structural disorder in LCRs, various examples, and particularly homorepeats of single amino acids, suggest that very short repeats could adopt structures very difficult to predict. These structures are possibly variable and dependant on the context of intra- or inter-molecular interactions. In general, short repeats in LCRs can induce structure. This could explain the observation that very short (non-perfect) repeats are widespread and many define regions with a function in protein interactions. For these reasons, we have developed an algorithm to quickly analyze local repeatability along protein sequences, that is, how close a protein fragment is from a perfect repeat. Using this algorithm we identified that the proteins of the yeast Saccharomyces cerevisiae are depleted in short repeats (approximate or not) of odd-length, while the human proteins are not, that the fish Danio rerio has many proteins with repeats of length two and that the plant Arabidopsis thaliana has an unusually large amount of repeats of length seven. Our method (REpeatability Scanner, RES, accessible at http://cbdm-01.zdv.uni-mainz.de/~munoz/res/) allows to find regions with approximate short repeats in protein sequences, and helps to characterize the variable use of LCRs and compositional bias in different organisms.

IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding

The structural states of proteins include ordered globular domains as well as intrinsically disordered protein regions that exist as highly flexible conformational ensembles in isolation. Various computational tools have been developed to discriminate ordered and disordered segments based on the amino acid sequence. However, properties of IDRs can also depend on various conditions, including binding to globular protein partners or environmental factors, such as redox potential. These cases provide further challenges for the computational characterization of disordered segments. In this work we present IUPred2A, a combined web interface that allows to generate energy estimation based predictions for ordered and disordered residues by IUPred2 and for disordered binding regions by ANCHOR2. The updated web server retains the robustness of the original programs but offers several new features. While only minor bug fixes are implemented for IUPred, the next version of ANCHOR is significantly improved through a new architecture and parameters optimized on novel datasets. In addition, redox-sensitive regions can also be highlighted through a novel experimental feature. The web server offers graphical and text outputs, a RESTful interface, access to software download and extensive help, and can be accessed at a new location: http://iupred2a.elte.hu.

The dark proteome of cancer: Intrinsic disorderedness and functionality of HIF-1α along with its interacting proteins

The dark side of protein is the region (s) where molecular conformation is unknown. Intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) are the dark matter of biology due to inability to visualize them using standard structure elucidation technique such as X-ray crystallography due to lack in diffraction signal. IDPs are the functionally important class of proteins with entire protein or its parts lack ordered three-dimensional structure. Computational studies have predicted that nearly one-third of the human proteome is disordered, which gives the enormous flexibility and functional diversity to proteins. The conserved residues and elements in disordered proteins are critical for function and might be parts of peptide motifs or protein-protein interaction interfaces. For example, regions of proteins that are involved in disorder-based molecular recognition are known as molecular recognition features (MoRFs). Generally, MoRFs could undergo disorder to order transition or vice versa at interaction with specific partners. Hypoxia inducible factor 1α (HIF-1α) is a master transcriptional regulator involved in response to hypoxia, which is associated with many pathological conditions. Importantly, HIF-1α regulates various steps of cancer progression such as cell survival, tumor cell invasion, and metastasis. In this chapter, we have extensively analyzed the molecular recognition features and their relationship with disordered regions and associated structural islands of HIF-1α. We had also analyzed the disorderness and MoRFs of HIF-1α primary interaction partners that are enriched in IDPRs and MoRFs giving their role in protein-protein interaction and cancer regulation.

Ferroptosis - An iron- and disorder-dependent programmed cell death

Programmed cell death (PCD) is an integral component of both developmental and pathological features of an organism. Recently, ferroptosis, a new form of PCD that is dependent on reactive oxygen species and iron, has been described. As with apoptosis, necroptosis, and autophagy, ferroptosis is associated with a large set of proteins assembled in protein-protein interaction (PPI) networks, interactability of which is driven by the presence of intrinsically disordered proteins (IDPs) and IDP regions (IDPRs). Previous investigations have identified the prevalence and functionality of IDPs/IDPRs in non-ferroptosis PCD. The intrinsic disorder in protein structures is used to increase the regulatory powers of these processes. As uncontrolled PCD is associated with the onset of various pathological traits, uncovering the association between intrinsic disorder and ferroptosis-related proteins is crucial. To understand this association, 31 human ferroptosis-related proteins were analyzed via a multi-dimensional array of bioinformatics and computational techniques. In addition, a disorder meta-predictor (PONDR® FIT) was implored to look at the evolutionary conservation of intrinsic disorder in these proteins. This study presents evidence that IDPs and IDPRs are prevalent in ferroptosis. The intrinsic disorder found in ferroptosis has far-reaching functional implications related to ferroptosis-related PPIs and molecular interactions.

Intrinsic Disorder-Based Emergence in Cellular Biology: Physiological and Pathological Liquid-Liquid Phase Transitions in Cells

The visible outcome of liquid-liquid phase transitions (LLPTs) in cells is the formation and disintegration of various proteinaceous membrane-less organelles (PMLOs). Although LLPTs and related PMLOs have been observed in living cells for over 200 years, the physiological functions of these transitions (also known as liquid-liquid phase separation, LLPS) are just starting to be understood. While unveiling the functionality of these transitions is important, they have come into light more recently due to the association of abnormal LLPTs with various pathological conditions. In fact, several maladies, such as various cancers, different neurodegenerative diseases, and cardiovascular diseases, are known to be associated with either aberrant LLPTs or some pathological transformations within the resultant PMLOs. Here, we will highlight both the physiological functions of cellular liquid-liquid phase transitions as well as the pathological consequences produced through both dysregulated biogenesis of PMLOs and the loss of their dynamics. We will also discuss the potential downstream toxic effects of proteins that are involved in pathological formations.

Computational prediction of functions of intrinsically disordered regions

Intrinsically disorder regions (IDRs) are abundant in nature, particularly among Eukaryotes. While they facilitate a wide spectrum of cellular functions including signaling, molecular assembly and recognition, translation, transcription and regulation, only several hundred IDRs are annotated functionally. This annotation gap motivates the development of fast and accurate computational methods that predict IDR functions directly from protein sequences. We introduce and describe a comprehensive collection of 25 methods that provide accurate predictions of IDRs that interact with proteins and nucleic acids, that function as flexible linkers and that moonlight multiple functions. Virtually all of these predictors can be accessed online and many were developed in the last few years. They utilize a wide range of predictive architectures and take advantage of modern machine learning algorithms. Our empirical analysis shows that predictors that are available as webservers enjoy high rates of citations, attesting to their practical value and popularity. The most cited methods include DISOPRED3, ANCHOR, alpha-MoRFpred, MoRFpred, fMoRFpred and MoRFCHiBi. We present two case studies to demonstrate that predictions produced by these computational tools are relatively easy to interpret and that they deliver valuable functional clues. However, the current computational tools cover a relatively narrow range of disorder functions. Further development efforts that would cover a broader range of functions should be pursued. We demonstrate that a sufficient amount of functionally annotated IDRs that are associated with several other disorder functions is already available and can be used to design and validate novel predictors.

Stochasticity of Biological Soft Matter: Emerging Concepts in Intrinsically Disordered Proteins and Biological Phase Separation

At the turn of this century, cardinal changes took place in the perceptions of the structure and function of proteins, as well as in the organizational principles of membrane-less organelles. As a result, the model of the organization of living matter is changing to one described by highly dynamic biological soft matter positioned at the edge of chaos. Intrinsically disordered proteins (IDPs) and membrane-less organelles are key examples of this new outlook and may represent a critical foundation of life, defining its complexity and the evolution of living things.

Intrinsically disordered proteins and phenotypic switching: Implications in cancer

It is now well established that intrinsically disordered proteins (IDPs) that constitute a large part of the proteome across the three kingdoms, play critical roles in several biological processes including phenotypic switching. However, dysregulated expression of IDPs that engage in promiscuous interactions can lead to pathological states. In this chapter, using cancer as a paradigm, we discuss how IDP conformational dynamics and the resultant conformational noise can modulate phenotypic switching. Thus, contrary to the prevailing wisdom that phenotypic switching is highly deterministic (has a genetic underpinning) in cancer, emerging evidence suggests that non-genetic mechanisms, at least in part due to the conformational noise, may also be a confounding factor in phenotypic switching.

FlexiBAC: a versatile, open-source baculovirus vector system for protein expression, secretion, and proteolytic processing

Background

Baculovirus-mediated expression in insect cells is a powerful approach for protein production. However, many existing methods are time-consuming, offer limited options for protein tagging, and are unsuitable for secreted proteins requiring proteolytic maturation, such as TGF-β family growth factors.

Results

To overcome the limitations of traditional baculovirus expression systems, we engineered “FlexiBAC”. This system allows recombinant baculovirus formation inside insect cells and reduces the time between initial cloning and protein production to 13 days. FlexiBAC includes 143 shuttle vectors that append combinations of purification tags, fluorescent markers, proteolytic cleavage sites, trafficking signals, and chemical conjugation tags to the termini of the target protein. This system also overexpresses recombinant furin convertase to allow efficient proteolytic processing of secreted proteins. We demonstrate that FlexiBAC can be used to produce high levels of mature, active forms of TGF-β family growth factors, such as Activin A, as well as other proteins that are typically difficult to reconstitute, such as proteins rich in coiled-coil, low complexity, and disordered domains.

Conclusions

FlexiBAC is a protein expression system for production of both cytosolic proteins and secreted proteins that require proteolytic maturation. The design of FlexiBAC and its expansive complementary shuttle vector system reduces cloning steps and simplifies baculovirus production.

Electronic supplementary material

The online version of this article (10.1186/s12896-019-0512-z) contains supplementary material, which is available to authorized users.

Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions

Molecular recognition features (MoRFs) are short protein-binding regions that undergo disorder-to-order transitions (induced folding) upon binding protein partners. These regions are abundant in nature and can be predicted from protein sequences based on their distinctive sequence signatures. This first-of-its-kind survey covers 14 MoRF predictors and six related methods for the prediction of short protein-binding linear motifs, disordered protein-binding regions and semi-disordered regions. We show that the development of MoRF predictors has accelerated in the recent years. These predictors depend on machine learning-derived models that were generated using training datasets where MoRFs are annotated using putative disorder. Our analysis reveals that they generate accurate predictions. We identified eight methods that offer area under the ROC curve (AUC) ≥ 0.7 on experimentally-validated test datasets. We show that modern MoRF predictors accurately find experimentally annotated MoRFs even though they were trained using the putative disorder annotations. They are relatively highly-cited, particularly the methods available as webservers that on average secure three times more citations than methods without this option. MoRF predictions contribute to the experimental discovery of protein-protein interactions, annotation of protein functions and computational analysis of a variety of proteomes, protein families, and pathways. We outline future development and application directions for these tools, stressing the importance to develop novel tools that would target interactions of disordered regions with other types of partners.

Disorder in milk proteins: adipophilin and TIP47, important constituents of the milk fat globule membrane

Milk fat globules (MFGs), which are secreted by the epithelial cells of the lactating mammary glands, account for the most of the nutritional value of milk. They are enveloped by the milk fat globule membrane (MFGM), a complex structure consisting of three phospholipid membrane monolayers and containing various lipids. Depending on the origin of milk, specific proteins accounts for 5-70% of the MFGM mass. Proteome of MFGMs includes hundreds of proteins, with nine major components being adipophilin, butyrophilin, cluster of differentiation 36, fatty acid binding protein, lactadherin, mucin 1, mucin 15, tail-interacting protein 47 (TIP47), and xanthine oxidoreductase. Two of the MFGM components, adipophilin and TIP47, belong to the five-member perilipin family of lipid droplet proteins. Adipophilin is involved in the formation of cytoplasmic lipid droplets and secretion of MFGs. This protein is also related to the formation of other lipid droplets that exist in most cell types, playing an important role in the transport of lipids from ER to the surface of lipid droplets. TIP47 acts as a cytoplasmic sorting factor for mannose 6-phosphate receptors and is recruited to the MFGM. Therefore, both adipophilin and TIP47 are moonlighting proteins, each possessing several unrelated functions. This review focuses on the main functions and specific structural features of adipophilin and TIP47, analyzes similarities and differences of these proteins among different species, and describes these proteins in the context of other members of the perilipin family.Communicated by Ramaswamy H. Sarma.

Concomitant disorder and high-affinity zinc binding in the human zinc- and iron-regulated transport protein 4 intracellular loop

The human zinc- and iron-regulated transport protein 4 (hZIP4) protein is the major plasma membrane protein responsible for the uptake of zinc in the body, and as such it plays a key role in cellular zinc homeostasis. hZIP4 plasma membrane levels are regulated through post-translational modification of its large, disordered, histidine-rich cytosolic loop (ICL2) in response to intracellular zinc concentrations. Here, structural characteristics of the isolated disordered loop region, both in the absence and presence of zinc, were investigated using nuclear magnetic resonance (NMR) spectroscopy. NMR chemical shifts, coupling constants and temperature coefficients of the apoprotein, are consistent with a random coil with minor propensities for transient polyproline Type II helices and β-strand in regions implicated in post-translational modifications. The ICL2 protein remains disordered upon zinc binding, which induces exchange broadening. Paramagnetic relaxation enhancement experiments reveal that the histidine-rich region in the apoprotein makes transient tertiary contacts with predicted post-translational modification sites. The residue-specific data presented here strengthen the relationship between hZIP4 post-translational modifications, which impact its role in cellular zinc homeostasis, and zinc sensing by the intracellular loop. Furthermore, the zinc sensing mechanism employed by the ICL2 protein demonstrates that high-affinity interactions can occur in the presence of conformational disorder.