Intrinsically Disordered Proteins in Chronic Diseases

Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. We provide first-of-its-kind assessment that comprehensively covers the taxonomy and evaluates predictions at the residue and disordered region levels. We curate a benchmark dataset that uniformly covers eukaryotic, archaeal, bacterial, and viral proteins. We find that predictive performance differs substantially across taxonomy, where viruses are predicted most accurately, followed by protists and higher eukaryotes, while bacterial and archaeal proteins suffer lower levels of accuracy. These trends are consistent across predictors. We also find that current tools, except for flDPnn, struggle with reproducing native distributions of the numbers and sizes of the disordered regions. Moreover, analysis of two variants of disorder predictions derived from the AlphaFold2 predicted structures reveals that they produce accurate residue-level propensities for archaea, bacteria and protists. However, they underperform for higher eukaryotes and generally struggle to accurately identify disordered regions. Our results motivate development of new predictors that target bacteria and archaea and which produce accurate results at both residue and region levels. We also stress the need to include the region-level assessments in future assessments.

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

A New Tool to Study the Binding Behavior of Intrinsically Disordered Proteins

Understanding the binding behavior and conformational dynamics of intrinsically disordered proteins (IDPs) is crucial for unraveling their regulatory roles in biological processes. However, their lack of stable 3D structures poses challenges for analysis. To address this, we propose an algorithm that explores IDP binding behavior with protein complexes by extracting topological and geometric features from the protein surface model. Our algorithm identifies a geometrically favorable binding pose for the IDP and plans a feasible trajectory to evaluate its transition to the docking position. We focus on IDPs from Homo sapiens and Mus-musculus, investigating their interaction with the Plasmodium falciparum (PF) pathogen associated with malaria-related deaths. We compare our algorithm with HawkDock and HDOCK docking tools for quantitative (computation time) and qualitative (binding affinity) measures. Our results indicated that our method outperformed the compared methods in computation performance and binding affinity in experimental conformations.

Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions. © 2023 Wiley Periodicals LLC.

Cellular Protein Aggregates: Formation, Biological Effects, and Ways of Elimination

The accumulation of protein aggregates is the hallmark of many neurodegenerative diseases. The dysregulation of protein homeostasis (or proteostasis) caused by acute proteotoxic stresses or chronic expression of mutant proteins can lead to protein aggregation. Protein aggregates can interfere with a variety of cellular biological processes and consume factors essential for maintaining proteostasis, leading to a further imbalance of proteostasis and further accumulation of protein aggregates, creating a vicious cycle that ultimately leads to aging and the progression of age-related neurodegenerative diseases. Over the long course of evolution, eukaryotic cells have evolved a variety of mechanisms to rescue or eliminate aggregated proteins. Here, we will briefly review the composition and causes of protein aggregation in mammalian cells, systematically summarize the role of protein aggregates in the organisms, and further highlight some of the clearance mechanisms of protein aggregates. Finally, we will discuss potential therapeutic strategies that target protein aggregates in the treatment of aging and age-related neurodegenerative diseases.

DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction

Intrinsic disorder in proteins is relatively abundant in nature and essential for a broad spectrum of cellular functions. While disorder can be accurately predicted from protein sequences, as it was empirically demonstrated in recent community-organized assessments, it is rather challenging to collect and compile a comprehensive prediction that covers multiple disorder functions. To this end, we introduce the DEPICTER2 (DisorderEd PredictIon CenTER) webserver that offers convenient access to a curated collection of fast and accurate disorder and disorder function predictors. This server includes a state-of-the-art disorder predictor, flDPnn, and five modern methods that cover all currently predictable disorder functions: disordered linkers and protein, peptide, DNA, RNA and lipid binding. DEPICTER2 allows selection of any combination of the six methods, batch predictions of up to 25 proteins per request and provides interactive visualization of the resulting predictions. The webserver is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER2/.

Fuzzy Drug Targets: Disordered Proteins in the Drug-Discovery Realm

Intrinsically disordered proteins (IDPs) and regions (IDRs) form a large part of the eukaryotic proteome. Contrary to the structure-function paradigm, the disordered proteins perform a myriad of functions in vivo. Consequently, they are involved in various disease pathways and are plausible drug targets. Unlike folded proteins, that have a defined structure and well carved out drug-binding pockets that can guide lead molecule selection, the disordered proteins require alternative drug-development methodologies that are based on an acceptable picture of their conformational ensemble. In this review, we discuss various experimental and computational techniques that contribute toward understanding IDP "structure" and describe representative pursuances toward IDP-targeting drug development. We also discuss ideas on developing rational drug design protocols targeting IDPs.

Computational prediction of disordered binding regions

One of the key features of intrinsically disordered regions (IDRs) is their ability to interact with a broad range of partner molecules. Multiple types of interacting IDRs were identified including molecular recognition fragments (MoRFs), short linear sequence motifs (SLiMs), and protein-, nucleic acids- and lipid-binding regions. Prediction of binding IDRs in protein sequences is gaining momentum in recent years. We survey 38 predictors of binding IDRs that target interactions with a diverse set of partners, such as peptides, proteins, RNA, DNA and lipids. We offer a historical perspective and highlight key events that fueled efforts to develop these methods. These tools rely on a diverse range of predictive architectures that include scoring functions, regular expressions, traditional and deep machine learning and meta-models. Recent efforts focus on the development of deep neural network-based architectures and extending coverage to RNA, DNA and lipid-binding IDRs. We analyze availability of these methods and show that providing implementations and webservers results in much higher rates of citations/use. We also make several recommendations to take advantage of modern deep network architectures, develop tools that bundle predictions of multiple and different types of binding IDRs, and work on algorithms that model structures of the resulting complexes.

Reciprocal regulatory balance within the CLEC16A-RNF41 mitophagy complex depends on an intrinsically disordered protein region

CLEC16A is an E3 ubiquitin ligase that regulates mitochondrial quality control through mitophagy and is associated with over 20 human diseases. CLEC16A forms a complex with another E3 ligase, RNF41, and a ubiquitin-specific peptidase, USP8; however, regions that regulate CLEC16A activity or the assembly of the tripartite mitophagy regulatory complex are unknown. Here, we report that CLEC16A contains an internal intrinsically disordered protein region (IDPR) that is crucial for CLEC16A function and turnover. IDPRs lack a fixed secondary structure and possess emerging, yet still equivocal roles in protein stability, interactions, and enzymatic activity. We find that the internal IDPR of CLEC16A is crucial for its degradation. CLEC16A turnover was promoted by RNF41, which binds and acts upon the internal IDPR to destabilize CLEC16A. Loss of this internal IDPR also destabilized the ubiquitin-dependent tripartite CLEC16A-RNF41-USP8 complex. Finally, the presence of an internal IDPR within CLEC16A was confirmed using NMR and circular dichroism spectroscopy. Together, our studies reveal that an IDPR is essential to control the reciprocal regulatory balance between CLEC16A and RNF41, which could be targeted to improve mitochondrial health in disease.

An intrinsically disordered protein region encoded by the human disease gene CLEC16A regulates mitophagy

CLEC16A regulates mitochondrial health through mitophagy and is associated with over 20 human diseases. However, the key structural and functional regions of CLEC16A, and their relevance for human disease, remain unknown. Here, we report that a disease-associated CLEC16A variant lacks a C-terminal intrinsically disordered protein region (IDPR) that is critical for mitochondrial quality control. IDPRs comprise nearly half of the human proteome, yet their mechanistic roles in human disease are poorly understood. Using carbon detect NMR, we find that the CLEC16A C terminus lacks secondary structure, validating the presence of an IDPR. Loss of the CLEC16A C-terminal IDPR in vivo impairs mitophagy, mitochondrial function, and glucose-stimulated insulin secretion, ultimately causing glucose intolerance. Deletion of the CLEC16A C-terminal IDPR increases CLEC16A ubiquitination and degradation, thus impairing assembly of the mitophagy regulatory machinery. Importantly, CLEC16A stability is dependent on proline bias within the C-terminal IDPR, but not amino acid sequence order or charge. Together, we elucidate how an IDPR in CLEC16A regulates mitophagy and implicate pathogenic human gene variants that disrupt IDPRs as novel contributors to diabetes and other CLEC16A-associated diseases.Abbreviations : CAS: carbon-detect amino-acid specific; IDPR: intrinsically disordered protein region; MEFs: mouse embryonic fibroblasts; NMR: nuclear magnetic resonance.

Developments in rapid hydrogen-deuterium exchange methods

Biological macromolecules, such as proteins, nucleic acids, and carbohydrates, contain heteroatom-bonded hydrogens that undergo exchange with solvent hydrogens on timescales ranging from microseconds to hours. In hydrogen-deuterium exchange mass spectrometry (HDX-MS), this exchange process is used to extract information about biomolecular structure and dynamics. This minireview focuses on millisecond timescale HDX-MS measurements, which, while less common than 'conventional' timescale (seconds to hours) HDX-MS, provide a unique window into weakly structured species, weak (or fast cycling) binding interactions, and subtle shifts in conformational dynamics. This includes intrinsically disordered proteins and regions (IDPs/IDRs) that are associated with cancer and amyloidotic neurodegenerative disease. For nucleic acids and carbohydrates, structures such as isomers, stems, and loops, can be elucidated and overall structural rigidity can be assessed. We will provide a brief overview of technical developments in rapid HDX followed by highlights of various applications, emphasising the importance of broadening the HDX timescale to improve throughput and to capture a wider range of function-relevant dynamic and structural shifts.

In Silico Study of the Interactions of Anle138b Isomer, an Inhibitor of Amyloid Aggregation, with Partner Proteins

Herein, we aimed to highlight current "gaps" in the understanding of the potential interactions between the Anle138b isomer ligand, a promising agent for clinical research, and the intrinsically disordered alpha-synuclein protein. The presence of extensive unstructured areas in alpha-synuclein determines its existence in the cell of partner proteins, including the cyclophilin A chaperone, which prevents the aggregation of alpha-synuclein molecules that are destructive to cell life. Using flexible and cascaded molecular docking techniques, we aimed to expand our understanding of the molecular architecture of the protein complex between alpha-synuclein, cyclophilin A and the Anle138b isomer ligand. We demonstrated the possibility of intricate complex formation under cellular conditions and revealed that the main interactions that stabilize the complex are hydrophobic and involve hydrogen.

Rapid prediction and analysis of protein intrinsic disorder

Protein intrinsic disorder is found in all kingdoms of life and is known to underpin numerous physiological and pathological processes. Computational methods play an important role in characterizing and identifying intrinsically disordered proteins and protein regions. Herein, we present a new high-efficiency web-based disorder predictor named Rapid Intrinsic Disorder Analysis Online (RIDAO) that is designed to facilitate the application of protein intrinsic disorder analysis in genome-scale structural bioinformatics and comparative genomics/proteomics. RIDAO integrates six established disorder predictors into a single, unified platform that reproduces the results of individual predictors with near-perfect fidelity. To demonstrate the potential applications, we construct a test set containing more than one million sequences from one hundred organisms comprising over 420 million residues. Using this test set, we compare the efficiency and accessibility (i.e., ease of use) of RIDAO to five well-known and popular disorder predictors, namely: AUCpreD, IUPred3, metapredict V2, flDPnn, and SPOT-Disorder2. We show that RIDAO yields per-residue predictions at a rate two to six orders of magnitude greater than the other predictors and completely processes the test set in under an hour. RIDAO can be accessed free of charge at https://ridao.app.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E)

Background:

Zika virus, which is widely spread and infects humans through the bites of Aedes albopictus and Aedes aegypti female mosquitoes, represents a serious global health issue.

Objective:

The objective of the present study is to computationally characterize Zika virus polyproteins (UniProt Name: PRO_0000443018 [residues 1-3423], PRO_0000445659 [residues 1-3423] and PRO_0000435828 [residues 1-3419]) and their envelope proteins using their physico-chemical properties.

Methods:

To achieve this, the Polarity Index Method (PIM) profile and the Protein Intrinsic Disorder Predisposition (PIDP) profile of 3 main groups of proteins were evaluated: structural proteins extracted from specific Databases, Zika virus polyproteins, and their envelope proteins (E) extracted from UniProt Database. Once the PIM profile of the Zika virus envelope proteins (E) was obtained and since the Zika virus polyproteins were also identified with this profile, the proteins defined as “reviewed proteins” extracted from the UniProt Database were searched for the similar PIM profile. Finally, the difference between the PIM profiles of the Zika virus polyproteins and their envelope proteins (E) was tested using 2 non-parametric statistical tests.

Results:

It was found and tested that the PIM profile is an efficient discriminant that allows obtaining a “computational fingerprint” of each Zika virus polyprotein from its envelope protein (E).

Conclusion:

PIM profile represents a computational tool, which can be used to effectively discover Zika virus polyproteins from Databases, from their envelope proteins (E) sequences.

Intrinsically disordered proteins in viral pathogenesis and infections

Disordered proteins serve a crucial part in many biological processes that go beyond the capabilities of ordered proteins. A large number of virus-encoded proteins have extremely condensed proteomes and genomes, which results in highly disordered proteins. The presence of these IDPs allows them to rapidly adapt to changes in their biological environment and play a significant role in viral replication and down-regulation of host defense mechanisms. Since viruses undergo rapid evolution and have a high rate of mutation and accumulation in their proteome, IDPs' insights into viruses are critical for understanding how viruses hijack cells and cause disease. There are many conformational changes that IDPs can adopt in order to interact with different protein partners and thus stabilize the particular fold and withstand high mutation rates. This chapter explains the molecular mechanism behind viral IDPs, as well as the significance of recent research in the field of IDPs, with the goal of gaining a deeper comprehension of the essential roles and functions played by viral proteins.

Structural characterisation of amyloidogenic intrinsically disordered zinc finger protein isoforms DPF3b and DPF3a

Double PHD fingers 3 (DPF3) is a zinc finger protein, found in the BAF chromatin remodelling complex, and is involved in the regulation of gene expression. Two DPF3 isoforms have been identified, respectively named DPF3b and DPF3a. Very limited structural information is available for these isoforms, and their specific functionality still remains poorly studied. In a previous work, we have demonstrated the first evidence of DPF3a being a disordered protein sensitive to amyloid fibrillation. Intrinsically disordered proteins (IDPs) lack a defined tertiary structure, existing as a dynamic conformational ensemble, allowing them to act as hubs in protein-protein interaction networks. In the present study, we have more thoroughly characterised DPF3a in vitro behaviour, as well as unravelled and compared the structural properties of the DPF3b isoform, using an array of predictors and biophysical techniques. Predictions, spectroscopy, and dynamic light scattering have revealed a high content in disorder: prevalence of random coil, aromatic residues partially to fully exposed to the solvent, and large hydrodynamic diameters. DPF3a appears to be more disordered than DPF3b, and exhibits more expanded conformations. Furthermore, we have shown that they both time-dependently aggregate into amyloid fibrils, as revealed by typical circular dichroism, deep-blue autofluorescence, and amyloid-dye binding assay fingerprints. Although spectroscopic and microscopic analyses have unveiled that they share a similar aggregation pathway, DPF3a fibrillates at a faster rate, likely through reordering of its C-terminal domain.

Intrinsically Disordered Proteins: Critical Components of the Wetware

Despite the wealth of knowledge gained about intrinsically disordered proteins (IDPs) since their discovery, there are several aspects that remain unexplored and, hence, poorly understood. A living cell is a complex adaptive system that can be described as a wetware─a metaphor used to describe the cell as a computer comprising both hardware and software and attuned to logic gates─capable of "making" decisions. In this focused Review, we discuss how IDPs, as critical components of the wetware, influence cell-fate decisions by wiring protein interaction networks to keep them minimally frustrated. Because IDPs lie between order and chaos, we explore the possibility that they can be modeled as attractors. Further, we discuss how the conformational dynamics of IDPs manifests itself as conformational noise, which can potentially amplify transcriptional noise to stochastically switch cellular phenotypes. Finally, we explore the potential role of IDPs in prebiotic evolution, in forming proteinaceous membrane-less organelles, in the origin of multicellularity, and in protein conformation-based transgenerational inheritance of acquired characteristics. Together, these ideas provide a new conceptual framework to discern how IDPs may perform critical biological functions despite their lack of structure.

Proteomic analysis of heat-stable proteins revealed an increased proportion of proteins with compositionally biased regions

Intrinsically disordered proteins (IDPs) have been in the spotlight for their unique properties, such as their lack of secondary structures and low sequence complexity. Alpha-synuclein and tau are representative disease-related IDPs with low complexity regions in their sequences, accumulating in the brains of patients with Parkinson disease and Alzheimer disease, respectively. Their heat resistance in particular was what attracted our attention. We assumed that there exist many other unidentified proteins that are resistant to heat-treatment, referred to as heat-stable proteins, which would also have low sequence complexity. In this study, we performed proteomic analysis of heat-stable proteins of mouse brains and found that proteins with compositionally biased regions are abundant in the heat-stable proteins. The proteins related to neurodegeneration are known to undergo different types of post-translational modifications (PTMs) such as phosphorylation and ubiquitination. We then investigated the heat-stability and aggregation properties of phosphorylated synuclein and tau with different phosphorylation sites. We suggest that PTMs can be important factors that determine the heat-stability and aggregation properties of a protein. IDPs identified in the heat-stable proteins of mouse brains would be candidates for the pathogenic proteins for neurodegeneration.

Intrinsically Disordered Proteins: Perspective on COVID-19 Infection and Drug Discovery

Since the beginning of the COVID-19 pandemic caused by SARS-CoV-2, millions of patients have been diagnosed and many of them have died from the disease worldwide. The identification of novel therapeutic targets are of utmost significance for prevention and treatment of COVID-19. SARS-CoV-2 is a single-stranded RNA virus with a 30 kb genome packaged into a membrane-enveloped virion, transcribing several tens of proteins. The belief that the amino acid sequence of proteins determines their 3D structure which, in turn, determines their function has been a central principle of molecular biology for a long time. Recently, it has been increasingly realized, however, that there is a large group of proteins that lack a fixed or ordered 3D structure, yet they exhibit important biological activities─so-called intrinsically disordered proteins and protein regions (IDPs/IDRs). Disordered regions in viral proteins are generally associated with viral infectivity and pathogenicity because they endow the viral proteins the ability to easily and promiscuously bind to host proteins; therefore, the proteome of SARS-CoV-2 has been thoroughly examined for intrinsic disorder. It has been recognized that, in fact, the SARS-CoV-2 proteome exhibits significant levels of structural order, with only the nucleocapsid (N) structural protein and two of the nonstructural proteins being highly disordered. The spike (S) protein of SARS-CoV-2 exhibits significant levels of structural order, yet its predicted percentage of intrinsic disorder is still higher than that of the spike protein of SARS-CoV. Noteworthy, however, even though IDPs/IDRs are not common in the SARS-CoV-2 proteome, the existing ones play major roles in the functioning and virulence of the virus and are thus promising drug targets for rational antiviral drug design. Presented here is a COVID-19 perspective on the intrinsically disordered proteins, summarizing recent results on the SARS-CoV-2 proteome disorder features, their physiological and pathological relevance, and their prominence as prospective drug target sites.

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.

How well does molecular simulation reproduce environment-specific conformations of the intrinsically disordered peptides PLP, TP2 and ONEG?

Understanding the conformational ensembles of intrinsically disordered proteins and peptides (IDPs) in their various biological environments is essential for understanding their mechanisms and functional roles in the proteome, leading to a greater knowledge of, and potential treatments for, a broad range of diseases. To determine whether molecular simulation is able to generate accurate conformational ensembles of IDPs, we explore the structural landscape of the PLP peptide (an intrinsically disordered region of the proteolipid membrane protein) in aqueous and membrane-mimicking solvents, using replica exchange with solute scaling (REST2), and examine the ability of four force fields (ff14SB, ff14IDPSFF, CHARMM36 and CHARMM36m) to reproduce literature circular dichroism (CD) data. Results from variable temperature (VT) 1H and Rotating frame Overhauser Effect SpectroscopY (ROESY) nuclear magnetic resonance (NMR) experiments are also presented and are consistent with the structural observations obtained from the simulations and CD. We also apply the optimum simulation protocol to TP2 and ONEG (a cell-penetrating peptide (CPP) and a negative control peptide, respectively) to gain insight into the structural differences that may account for the observed difference in their membrane-penetrating abilities. Of the tested force fields, we find that CHARMM36 and CHARMM36m are best suited to the study of IDPs, and accurately predict a disordered to helical conformational transition of the PLP peptide accompanying the change from aqueous to membrane-mimicking solvents. We also identify an α-helical structure of TP2 in the membrane-mimicking solvents and provide a discussion of the mechanistic implications of this observation with reference to the previous literature on the peptide. From these results, we recommend the use of CHARMM36m with the REST2 protocol for the study of environment-specific IDP conformations. We believe that the simulation protocol will allow the study of a broad range of IDPs that undergo conformational transitions in different biological environments.

Allosteric binding on nuclear receptors: Insights on screening of non-competitive endocrine-disrupting chemicals

Endocrine-disrupting chemicals (EDCs) can compete with endogenous hormones and bind to the orthosteric site of nuclear receptors (NRs), affecting normal endocrine system function and causing severe symptoms. Recently, a series of pharmaceuticals and personal care products (PPCPs) have been discovered to bind to the allosteric sites of NRs and induce similar effects. However, it remains unclear how diverse EDCs work in this new way. Therefore, we have systematically summarized the allosteric sites and underlying mechanisms based on existing studies, mainly regarding drugs belonging to the PPCP class. Advanced methods, classified as structural biology, biochemistry and computational simulation, together with their advantages and hurdles for allosteric site recognition and mechanism insight have also been described. Furthermore, we have highlighted two available strategies for virtual screening of numerous EDCs, relying on the structural features of allosteric sites and lead compounds, respectively. We aim to provide reliable theoretical and technical support for a broader view of various allosteric interactions between EDCs and NRs, and to drive high-throughput and accurate screening of potential EDCs with non-competitive effects.

Transactivation domain of Adenovirus Early Region 1A (E1A): Investigating folding dynamics and aggregation

Transactivation domain of Adenovirus Early region 1A (E1A) oncoprotein is an intrinsically disordered molecular hub protein. It is involved in binding to different domains of human cell transcriptional co-activators such as retinoblastoma (pRb), CREB-binding protein (CBP), and its paralogue p300. The conserved region 1 (TAD) of E1A is known to undergo structural transitions and folds upon interaction with transcriptional adaptor zinc finger 2 (TAZ2). Previous reports on Taz2-E1A studies have suggested the formation of helical conformations of E1A-TAD. However, the folding behavior of the TAD region in isolation has not been studied in detail. Here, we have elucidated the folding behavior of E1A peptide at varied temperatures and solution conditions. Further, we have studied the effects of macromolecular crowding on E1A-TAD peptide. Additionally, we have also predicted the molecular recognition features of E1A using MoRF predictors. The predicted MoRFs are consistent with its structural transitions observed during TAZ2 interactions for transcriptional regulation in literature. Also, as a general rule of MoRFs, E1A undergoes helical transitions in alcohol and osmolyte solution. Finally, we studied the aggregation behavior of E1A, where we observed that the E1A could form amyloid-like aggregates that are cytotoxic to mammalian cells.

Drugging the Undruggable: Targeting the N-Terminal Domain of Nuclear Hormone Receptors

This chapter focuses on the development of drugs targeting the N-terminal domain of nuclear hormone receptors, using progress with the androgen receptor as an example. Historically, development of therapies targeting nuclear hormone receptors has focused on the folded C-terminal ligand-binding domain. Therapies were traditionally not developed to target the intrinsically disordered N-terminal domain as it was considered "undruggable". Recent developments have now shown it is possible to direct therapies to the N-terminal domain. This chapter will provide an introduction of the structure and function of the domains of nuclear hormone receptors, followed by a discussion of the rationale supporting the development of N-terminal domain inhibitors. Chemistry and mechanisms of action of small molecule inhibitors will be described with emphasis on N-terminal domain inhibitors developed to the androgen receptor including those in clinical trials.

Disorder-to-order transition of the amyloid-β peptide upon lipid binding

There is mounting evidence that Alzheimer's disease progression and severity are linked to neuronal membrane damage caused by aggregates of the amyloid-β (Aβ) peptide. However, the detailed mechanism behind the membrane damage is not well understood yet. Recently, the lipid-chaperone hypothesis has been put forward, based on which the formation of complexes between Aβ and free lipids enables an easy insertion of Aβ into membranes. In order to test this hypothesis, we performed numerous all-atom molecular dynamics simulations. We studied the complex formation between individual lipids, considering both POPC and DPPC, and Aβ and examined whether the resulting complexes would be able to insert into lipid membranes. Complex formation at a one-to-one ratio was readily observed, yet with minimal effects on Aβ's characteristics. Most importantly, the peptide remains largely disordered in 1:1 complexes, and the complex does not insert into the membrane; instead, it is adsorbed to the membrane surface. The results change considerably once Aβ forms a complex with a POPC cluster composed of three lipid molecules. The hydrophobic interactions between Aβ and the lipid tails cause the peptide to fold into either a helical or a β-sheet structure. These observations provide atomic insight into the disorder-to-order transition that is needed for membrane insertion or amyloid aggregation to proceed.

In Silico Modeling of the Influence of Environment on Amyloid Folding Using FOD-M Model

The role of the environment in amyloid formation based on the fuzzy oil drop model (FOD) is discussed here. This model assumes that the hydrophobicity distribution within a globular protein is consistent with a 3D Gaussian (3DG) distribution. Such a distribution is interpreted as the idealized effect of the presence of a polar solvent-water. A chain with a sequence of amino acids (which are bipolar molecules) determined by evolution recreates a micelle-like structure with varying accuracy. The membrane, which is a specific environment with opposite characteristics to the polar aquatic environment, directs the hydrophobic residues towards the surface. The modification of the FOD model to the FOD-M form takes into account the specificity of the cell membrane. It consists in "inverting" the 3DG distribution (complementing the Gaussian distribution), which expresses the exposure of hydrophobic residues on the surface. It turns out that the influence of the environment for any protein (soluble or membrane-anchored) is the result of a consensus factor expressing the participation of the polar environment and the "inverted" environment. The ratio between the proportion of the aqueous and the "reversed" environment turns out to be a characteristic property of a given protein, including amyloid protein in particular. The structure of amyloid proteins has been characterized in the context of prion, intrinsically disordered, and other non-complexing proteins to cover a wider spectrum of molecules with the given characteristics based on the FOD-M model.

Advanced Sampling Methods for Multiscale Simulation of Disordered Proteins and Dynamic Interactions

Intrinsically disordered proteins (IDPs) are highly prevalent and play important roles in biology and human diseases. It is now also recognized that many IDPs remain dynamic even in specific complexes and functional assemblies. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for a mechanistic understanding of IDPs in biology, diseases, and therapeutics. Here, we provide an in-depth review of recent advances in the multi-scale simulation of disordered protein states, with a particular emphasis on the development and application of advanced sampling techniques for studying IDPs. These techniques are critical for adequate sampling of the manifold functionally relevant conformational spaces of IDPs. Together with dramatically improved protein force fields, these advanced simulation approaches have achieved substantial success and demonstrated significant promise towards the quantitative and predictive modeling of IDPs and their dynamic interactions. We will also discuss important challenges remaining in the atomistic simulation of larger systems and how various coarse-grained approaches may help to bridge the remaining gaps in the accessible time- and length-scales of IDP simulations.

Pathogen Effectors: Exploiting the Promiscuity of Plant Signaling Hubs

Pathogens produce effectors to overcome plant immunity, thereby threatening crop yields and global food security. Large-scale interactomic studies have revealed that pathogens from different kingdoms of life target common plant proteins during infection, the so-called effector hubs. These hubs often play central roles in numerous plant processes through their ability to interact with multiple plant proteins. This ability arises partly from the presence of intrinsically disordered domains (IDDs) in their structure. Here, we highlight the role of the TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) and JASMONATE-ZIM DOMAIN (JAZ) transcription regulator families as plant signaling and effector hubs. We consider different evolutionary hypotheses to rationalize the existence of diverse effectors sharing common targets and the possible role of IDDs in this interaction.

Liquid-Liquid Phase Separation in the Presence of Macromolecular Crowding and State-dependent Kinetics

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) are increasingly being shown to play major roles in cellular self-organization dynamics in health and disease. It is well established that macromolecular crowding has a profound impact on protein interactions, particularly those that lead to LLPS. Although synthetic crowding agents are used during in vitro LLPS experiments, they are considerably different from the highly crowded nucleo-/cytoplasm and the effects of in vivo crowding remain poorly understood. In this work, we applied computational modeling to investigate the effects of macromolecular crowding on LLPS. To include biologically relevant LLPS dynamics, we extended the conventional Cahn-Hilliard model for phase separation by coupling it to experimentally derived macromolecular crowding dynamics and state-dependent reaction kinetics. Through extensive field-theoretic computer simulations, we show that the inclusion of macromolecular crowding results in late-stage coarsening and the stabilization of relatively smaller condensates. At a high crowding concentration, there is an accelerated growth and late-stage arrest of droplet formation, effectively resulting in anomalous labyrinthine morphologies akin to protein gelation observed in experiments. These results not only elucidate the crowder effects observed in experiments, but also highlight the importance of including state-dependent kinetics in LLPS models, and may help in designing further experiments to probe the intricate roles played by LLPS in self-organization dynamics of cells.

On the specificity of protein-protein interactions in the context of disorder

With the increased focus on intrinsically disordered proteins (IDPs) and their large interactomes, the question about their specificity — or more so on their multispecificity — arise. Here we recapitulate how specificity and multispecificity are quantified and address through examples if IDPs in this respect differ from globular proteins. The conclusion is that quantitatively, globular proteins and IDPs are similar when it comes to specificity. However, compared with globular proteins, IDPs have larger interactome sizes, a phenomenon that is further enabled by their flexibility, repetitive binding motifs and propensity to adapt to different binding partners. For IDPs, this adaptability, interactome size and a higher degree of multivalency opens for new interaction mechanisms such as facilitated exchange through trimer formation and ultra-sensitivity via threshold effects and ensemble redistribution. IDPs and their interactions, thus, do not compromise the definition of specificity. Instead, it is the sheer size of their interactomes that complicates its calculation. More importantly, it is this size that challenges how we conceptually envision, interpret and speak about their specificity.

Integrating an Enhanced Sampling Method and Small-Angle X-Ray Scattering to Study Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) have been paid more and more attention over the past decades because they are involved in a multitude of crucial biological functions. Despite their functional importance, IDPs are generally difficult to investigate because they are very flexible and lack stable structures. Computer simulation may serve as a useful tool in studying IDPs. With the development of computer software and hardware, computational methods, such as molecular dynamics (MD) simulations, are popularly used. However, there is a sampling problem in MD simulations. In this work, this issue is investigated using an IDP called unique long region 11 (UL11), which is the conserved outer tegument component from herpes simplex virus 1. After choosing a proper force field and water model that is suitable for simulating IDPs, integrative modeling by combining an enhanced sampling method and experimental data like small-angle X-ray scattering (SAXS) is utilized to efficiently sample the conformations of UL11. The simulation results are in good agreement with experimental data. This work may provide a general protocol to study structural ensembles of IDPs.

Understanding disorder-to-order transitions in protein-RNA complexes using molecular dynamics simulations

Intrinsically disordered regions (IDRs) in proteins are characterized by their flexibilities and low complexity regions, which lack unique 3 D structures in solution. IDRs play a significant role in signaling, regulation, and binding multiple partners, including DNA, RNA, and proteins. Although various experiments have shown the role of disordered regions in binding with RNA, a detailed computational analysis is required to understand their binding and recognition mechanism. In this work, we performed molecular dynamics simulations of 10 protein-RNA complexes to understand the binding governed by intrinsically disordered regions. The simulation results show that most of the disordered regions are important for RNA-binding and have a transition from disordered-to-ordered conformation upon binding, which often contribute significantly towards the binding affinity. Interestingly, most of the disordered residues are present at the interface or located as a linker between two regions having similar movements. The DOT regions are overlaped or flanked with experimentally reported functionally important residues in the recognition of protein-RNA complexes. This study provides additional insights for understanding the role and recognition mechanism of disordered regions in protein-RNA complexes.Communicated by Ramaswamy H. Sarma.

Unstructural Biology of TRP Ion Channels: The Role of Intrinsically Disordered Regions in Channel Function and Regulation

The first genuine high-resolution single particle cryo-electron microscopy structure of a membrane protein determined was a transient receptor potential (TRP) ion channel, TRPV1, in 2013. This methodical breakthrough opened up a whole new world for structural biology and ion channel aficionados alike. TRP channels capture the imagination due to the sheer endless number of tasks they carry out in all aspects of animal physiology. To date, structures of at least one representative member of each of the six mammalian TRP channel subfamilies as well as of a few non-mammalian families have been determined. These structures were instrumental for a better understanding of TRP channel function and regulation. However, all of the TRP channel structures solved so far are incomplete since they miss important information about highly flexible regions found mostly in the channel N- and C-termini. These intrinsically disordered regions (IDRs) can represent between a quarter to almost half of the entire protein sequence and act as important recruitment hubs for lipids and regulatory proteins. Here, we analyze the currently available TRP channel structures with regard to the extent of these "missing" regions and compare these findings to disorder predictions. We discuss select examples of intra- and intermolecular crosstalk of TRP channel IDRs with proteins and lipids as well as the effect of splicing and post-translational modifications, to illuminate their importance for channel function and to complement the prevalently discussed structural biology of these versatile and fascinating proteins with their equally relevant 'unstructural' biology.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

RNA-protein interactions: Central players in coordination of regulatory networks

Changes in the abundance of protein and RNA molecules can impair the formation of complexes in the cell leading to toxicity and death. Here we exploit the information contained in protein, RNA and DNA interaction networks to provide a comprehensive view of the regulation layers controlling the concentration-dependent formation of assemblies in the cell. We present the emerging concept that RNAs can act as scaffolds to promote the formation ribonucleoprotein complexes and coordinate the post-transcriptional layer of gene regulation. We describe the structural and interaction network properties that characterize the ability of protein and RNA molecules to interact and phase separate in liquid-like compartments. Finally, we show that presence of structurally disordered regions in proteins correlate with the propensity to undergo liquid-to-solid phase transitions and cause human diseases. Also see the video abstract here https://youtu.be/kfpqibsNfS0.

Catalytic and lectin domains in neuraminidase A from Streptococcus pneumoniae are capable of an intermolecular assembly: Implications for biofilm formation

Neuraminidase A from Streptococcus pneumoniae (NanA) is a cell wall-bound modular enzyme containing one lectin and one catalytic domain. Unlike homologous NanB and NanC expressed by the same bacterium, the two domains within one NanA molecule do not form a stable interaction and are spatially separated by a 16-amino acid-long flexible linker. In this work, the ability of NanA to form intermolecular assemblies was characterized using the methods of molecular modeling and bioinformatic analysis based on crystallographic data and by bringing together previously published experimental data. It was concluded that two catalytic domains, as well as one catalytic and one lectin domain, originating from two cell wall-bound NanA molecules, can interact through a previously uncharacterized interdomain interface to form complexes stabilized by a network of intermolecular hydrogen bonds and salt bridges. Supercomputer modeling strongly indicated that artocarpin, an earlier experimentally discovered inhibitor of the pneumococcal biofilm formation, is able to bind to a site located in the catalytic domain of one NanA entity and prevent its interaction with the lectin or catalytic domain of another NanA entity, thus directly precluding the generation of intermolecular assemblies. The revealed structural adaptation is discussed as one plausible mechanism of noncatalytic participation of this potentially key pathogenicity enzyme in pneumococcal biofilm formation.

Criticality in the conformational phase transition among self-similar groups in intrinsically disordered proteins: Probed by salt-bridge dynamics

Intrinsically disordered proteins (IDP) serve as one of the key components in the global proteome. In contrast to globular proteins, they harbor an enormous amount of physical flexibility enforcing them to be retained in conformational ensembles rather than stable folds. Previous studies in an aligned direction have revealed the importance of transient dynamical phenomena like that of salt-bridge formation in IDPs to support their physical flexibility and have further highlighted their functional relevance. For this characteristic flexibility, IDPs remain amenable and accessible to different ordered binding partners, supporting their potential multi-functionality. The current study further addresses this complex structure-functional interplay in IDPs using phase transition dynamics to conceptualize the underlying (avalanche type) mechanism of their being distributed across and hopping around degenerate structural states (conformational ensembles). For this purpose, extensive molecular dynamics simulations have been done and the data analyzed from a statistical physics perspective. Investigation of the plausible scope of 'self-organized criticality' (SOC) to fit into the complex dynamics of IDPs was found to be assertive, relating the conformational degeneracy of these proteins to their functional multiplicity. In accordance with the transient nature of 'salt-bridge dynamics', the study further uses it as a probe to explain the structural basis of the proposed criticality in the conformational phase transition among self-similar groups in IDPs. The analysis reveal scale-invariant self-similar fractal geometries in the structural conformations of different IDPs. The insights from the study has the potential to be extended further to benefit structural tinkering of IDPs in their functional characterization and drugging.

Unstructured Biology of Proteins from Ubiquitin-Proteasome System: Roles in Cancer and Neurodegenerative Diseases

The 26S proteasome is a large (~2.5 MDa) protein complex consisting of at least 33 different subunits and many other components, which form the ubiquitin proteasomal system (UPS), an ATP-dependent protein degradation system in the cell. UPS serves as an essential component of the cellular protein surveillance machinery, and its dysfunction leads to cancer, neurodegenerative and immunological disorders. Importantly, the functions and regulations of proteins are governed by the combination of ordered regions, intrinsically disordered protein regions (IDPRs) and molecular recognition features (MoRFs). The structure-function relationships of UPS components have not been identified completely; therefore, in this study, we have carried out the functional intrinsic disorder and MoRF analysis for potential neurodegenerative disease and anti-cancer targets of this pathway. Our report represents the presence of significant intrinsic disorder and disorder-based binding regions in several UPS proteins, such as extraproteasomal polyubiquitin receptors (UBQLN1 and UBQLN2), proteasome-associated polyubiquitin receptors (ADRM1 and PSMD4), deubiquitinating enzymes (DUBs) (ATXN3 and USP14), and ubiquitinating enzymes (E2 (UBE2R2) and E3 (STUB1) enzyme). We believe this study will have implications for the conformation-specific roles of different regions of these proteins. This will lead to a better understanding of the molecular basis of UPS-associated diseases.

Dancing while self-eating: Protein intrinsic disorder in autophagy

Autophagy is a major catabolic pathway that must be tightly regulated to maintain cellular homeostasis. Protein intrinsic disorder provides a very suitable conformation for regulation; accordingly, the molecular machinery of autophagy is significantly enriched in intrinsically disordered proteins and protein regions (IDPs/IDPRs). Despite experimental challenges that the characterization of IDPRs encounters, remarkable progress has been made in recent years in revealing various roles of IDPs/IDPRs in autophagy. This chapter describes the autophagy pathway from a specific point of view, that of IDPRs. It focuses in detail on structural and mechanistic functions in autophagy that are executed by disordered regions. Via a description of autophagosome biogenesis, linking the cargo to the autophagy machinery, as well as a discussion of certain post-translational regulations, this review reveals many indispensable roles of IDPRs in the functional autophagy pathway. Devastating pathologies such as neurodegeneration, cancer, or diabetes have been linked to a malfunction in IDPs/IDPRs. The same pathologies are associated with dysfunctional autophagy, indicating that autophagic IDPRs may be a paramount causative factor. Several disease-related mechanisms of the autophagy pathway involving protein intrinsic disorder are reported in this chapter, to illustrate a wide-ranging potential of IDPRs in the therapeutic modulation of autophagy.

Changes in hydrophobicity mainly promotes the aggregation tendency of ALS associated SOD1 mutants

Protein misfolding and aggregation due to mutations, are associated with fatal neurodegenerative disorders. The mutations in Cu/Zn superoxide dismutase (SOD1) causing its misfolding and aggregation are found linked to the motor neuron disorder, amyotrophic lateral sclerosis. Since the mutations are scattered throughout SOD1 structure, determining the exact molecular mechanism underlying the ALS pathology remains unresolved. In this study, we have investigated the major molecular factors that mainly contribute to SOD1 destabilization, intrinsic disorder, and misfolding using sequence and structural information. We have analysed 153 ALS causing SOD1 point mutants for aggregation tendency using four different aggregation prediction tools, viz., Aggrescan3D (A3D), CamSol, GAP and Zyggregator. Our results suggest that 74-79 mutants are susceptible to aggregation, due to distorted native interactions originated at the mutation site. Majority of the aggregation prone mutants are located in the buried regions of SOD1 molecule. Further, the mutations at the hydrophobic amino acids primarily promote the aggregation tendency of SOD1 protein through different destabilizing mechanisms including changes in hydrophobic free energy, loss of electrostatic interactions in the protein's surface and loss of hydrogen bonds that bridges the protein core and surface.

Expanding the understanding of the heterogeneous nature of melanoma with bioinformatics and disorder-based proteomics

The past few decades show that incidences of melanoma are on the rise. The risk associated with this disease is an interplay between genetic and host factors and sun exposure. While scientific progress in the treatment of melanoma is remarkable, additional research is needed to improve patient outcomes and to better understand the heterogenous nature of this disease. Fortunately, as the clinical community enters the era of "big data" and personalized medicine, the rise of bioinformatics that stems from recent advances in high throughout profiling of biological information offers potential for innovative treatment options. This study aims to provide an example of the usefulness of bioinformatics and disorder-based proteomics to identify the molecular pathway in melanoma, garner information on selected proteins from this pathway and uncover their intrinsically disordered proteins regions (IDPRs) and investigate functionality implicated in these IDPRs. The present study provides a new look at the melanoma heterogeneity and suggests that, in addition to the well-established genetic heterogeneity of melanoma, there is another level of heterogeneity that lies within the conformational ensembles that stem from intrinsic disorder in melanoma-related proteins. The hope is that these insights will inspire future drug discovery campaigns.

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.