Streamlining NMR Chemical Shift Predictions for Intrinsically Disordered Proteins: Design of Ensembles with Dimensionality Reduction and Clustering

By merging advanced dimensionality reduction (DR) and clustering algorithm (CA) techniques, our study advances the sampling procedure for predicting NMR chemical shifts (CS) in intrinsically disordered proteins (IDPs), making a significant leap forward in the field of protein analysis/modeling. We enhance NMR CS sampling by generating clustered ensembles that accurately reflect the different properties and phenomena encapsulated by the IDP trajectories. This investigation critically assessed different rapid CS predictors, both neural network (e.g., Sparta+ and ShiftX2) and database-driven (ProCS-15), and highlighted the need for more advanced quantum calculations and the subsequent need for more tractable-sized conformational ensembles. Although neural network CS predictors outperformed ProCS-15 for all atoms, all tools showed poor agreement with HN CSs, and the neural network CS predictors were unable to capture the influence of phosphorylated residues, highly relevant for IDPs. This study also addressed the limitations of using direct clustering with collective variables, such as the widespread implementation of the GROMOS algorithm. Clustered ensembles (CEs) produced by this algorithm showed poor performance with chemical shifts compared to sequential ensembles (SEs) of similar size. Instead, we implement a multiscale DR and CA approach and explore the challenges and limitations of applying these algorithms to obtain more robust and tractable CEs. The novel feature of this investigation is the use of solvent-accessible surface area (SASA) as one of the fingerprints for DR alongside previously investigated α carbon distance/angles or ϕ/ψ dihedral angles. The ensembles produced with SASA tSNE DR produced CEs better aligned with the experimental CS of between 0.17 and 0.36 r2 (0.18-0.26 ppm) depending on the system and replicate. Furthermore, this technique produced CEs with better agreement than traditional SEs in 85.7% of all ensemble sizes. This study investigates the quality of ensembles produced based on different input features, comparing latent spaces produced by linear vs nonlinear DR techniques and a novel integrated silhouette score scanning protocol for tSNE DR.

New Insights on the Chemical Origin of Life: The Role of Aqueous Polymerization of N-carboxyanhydrides (NCA)

At the origin, the emergence of proteins was based on crucial prebiotic stages in which simple amino acids-based building blocks spontaneously evolved from the prebiotic soup into random proto-polymers called protoproteins. Despite advances in modern peptide synthesis, these prebiotic chemical routes to protoproteins remain puzzling. We discuss in this perspective how polymer science and systems chemistry are reaching a point of convergence in which simple monomers called N-carboxyanhydrides would be able to form such protoproteins via the emergence of a protometabolic cycle involving aqueous polymerization and featuring macromolecular Darwinism behavior.

An ANXA11 P93S variant dysregulates TDP-43 and causes corticobasal syndrome

INTRODUCTION

Variants of uncertain significance (VUS) surged with affordable genetic testing, posing challenges for determining pathogenicity. We examine the pathogenicity of a novel VUS P93S in Annexin A11 (ANXA11) - an amyotrophic lateral sclerosis/frontotemporal dementia-associated gene - in a corticobasal syndrome kindred. Established ANXA11 mutations cause ANXA11 aggregation, altered lysosomal-RNA granule co-trafficking, and transactive response DNA binding protein of 43 kDa (TDP-43) mis-localization.

METHODS

We described the clinical presentation and explored the phenotypic diversity of ANXA11 variants. P93S's effect on ANXA11 function and TDP-43 biology was characterized in induced pluripotent stem cell-derived neurons alongside multiomic neuronal and microglial profiling.

RESULTS

ANXA11 mutations were linked to corticobasal syndrome cases. P93S led to decreased lysosome colocalization, neuritic RNA, and nuclear TDP-43 with cryptic exon expression. Multiomic microglial signatures implicated immune dysregulation and interferon signaling pathways.

DISCUSSION

This study establishes ANXA11 P93S pathogenicity, broadens the phenotypic spectrum of ANXA11 mutations, underscores neuronal and microglial dysfunction in ANXA11 pathophysiology, and demonstrates the potential of cellular models to determine variant pathogenicity.

HIGHLIGHTS

ANXA11 P93S is a pathogenic variant. Corticobasal syndrome is part of the ANXA11 phenotypic spectrum. Hybridization chain reaction fluorescence in situ hybridization (HCR FISH) is a new tool for the detection of cryptic exons due to TDP-43-related loss of splicing regulation. Microglial ANXA11 and related immune pathways are important drivers of disease. Cellular models are powerful tools for adjudicating variants of uncertain significance.

The Conformational Contribution to Molecular Complexity and Its Implications for Information Processing in Living Beings and Chemical Artificial Intelligence

This work highlights the relevant contribution of conformational stereoisomers to the complexity and functions of any molecular compound. Conformers have the same molecular and structural formulas but different orientations of the atoms in the three-dimensional space. Moving from one conformer to another is possible without breaking covalent bonds. The interconversion is usually feasible through the thermal energy available in ordinary conditions. The behavior of most biopolymers, such as enzymes, antibodies, RNA, and DNA, is understandable if we consider that each exists as an ensemble of conformers. Each conformational collection confers multi-functionality and adaptability to the single biopolymers. The conformational distribution of any biopolymer has the features of a fuzzy set. Hence, every compound that exists as an ensemble of conformers allows the molecular implementation of a fuzzy set. Since proteins, DNA, and RNA work as fuzzy sets, it is fair to say that life's logic is fuzzy. The power of processing fuzzy logic makes living beings capable of swift decisions in environments dominated by uncertainty and vagueness. These performances can be implemented in chemical robots, which are confined molecular assemblies mimicking unicellular organisms: they are supposed to help humans "colonise" the molecular world to defeat diseases in living beings and fight pollution in the environment.

A Conserved Ribosomal Protein Has Entirely Dissimilar Structures in Different Organisms

Ribosomes from different species can markedly differ in their composition by including dozens of ribosomal proteins that are unique to specific lineages but absent in others. However, it remains unknown how ribosomes acquire new proteins throughout evolution. Here, to help answer this question, we describe the evolution of the ribosomal protein msL1/msL2 that was recently found in ribosomes from the parasitic microorganism clade, microsporidia. We show that this protein has a conserved location in the ribosome but entirely dissimilar structures in different organisms: in each of the analyzed species, msL1/msL2 exhibits an altered secondary structure, an inverted orientation of the N-termini and C-termini on the ribosomal binding surface, and a completely transformed 3D fold. We then show that this fold switching is likely caused by changes in the ribosomal msL1/msL2-binding site, specifically, by variations in rRNA. These observations allow us to infer an evolutionary scenario in which a small, positively charged, de novo-born unfolded protein was first captured by rRNA to become part of the ribosome and subsequently underwent complete fold switching to optimize its binding to its evolving ribosomal binding site. Overall, our work provides a striking example of how a protein can switch its fold in the context of a complex biological assembly, while retaining its specificity for its molecular partner. This finding will help us better understand the origin and evolution of new protein components of complex molecular assemblies-thereby enhancing our ability to engineer biological molecules, identify protein homologs, and peer into the history of life on Earth.

Distinct dynamical features of plasmodial and human HSP70-HSP110 highlight the divergence in their chaperone-assisted protein folding

HSP70 and its evolutionarily diverged co-chaperone HSP110, forms an important node in protein folding cascade. How these proteins maintain the aggregation-prone proteome of malaria parasite in functional state remains underexplored, in contrast to its human orthologs. In this study, we have probed into conformational dynamics of plasmodial HSP70 and HSP110 through multiple μs MD-simulations (ATP-state) and compared with their respective human counterparts. Simulations covered sampling of 3.4 and 2.8 μs for HSP70 and HSP110, respectively, for parasite and human orthologs. We provide a comprehensive description of the dynamic behaviors that characterize the systems and also introduce a parameter for quantifying protein rigidity. For HSP70, the interspecies comparison reveals enhanced flexibility in IA and IB subdomain within the conserved NBD, lesser solvent accessibility of the interdomain linker and distinct dynamics of the SBDβ of Pf HSP70 in comparison to Hs HSP70. In the case of HSP110, notable contrast in the dynamics of NBD, SBDβ and SBDα was observed between parasite and human ortholog. Although HSP70 and HSP110 are members of the same superfamily, we identified specific differences in the subdomain contacts in NBD, linker properties and interdomain movements in their human and parasite orthologs. Our study suggests that differences in conformational dynamics may translate into species-specific differences in the chaperoning activities of HSP70-HSP110 in the parasite and human, respectively. Dynamical features of Pf HSP70-HSP110 may contribute to the maintenance of proteostasis in the parasite during its intracellular survival in the host.

An ANXA11 P93S variant dysregulates TDP-43 and causes corticobasal syndrome

As genetic testing has become more accessible and affordable, variants of uncertain significance (VUS) are increasingly identified, and determining whether these variants play causal roles in disease is a major challenge. The known disease-associated Annexin A11 (ANXA11) mutations result in ANXA11 aggregation, alterations in lysosomal-RNA granule co-trafficking, and TDP-43 mis-localization and present as amyotrophic lateral sclerosis or frontotemporal dementia. We identified a novel VUS in ANXA11 (P93S) in a kindred with corticobasal syndrome and unique radiographic features that segregated with disease. We then queried neurodegenerative disorder clinic databases to identify the phenotypic spread of ANXA11 mutations. Multi-modal computational analysis of this variant was performed and the effect of this VUS on ANXA11 function and TDP-43 biology was characterized in iPSC-derived neurons. Single-cell sequencing and proteomic analysis of iPSC-derived neurons and microglia were used to determine the multiomic signature of this VUS. Mutations in ANXA11 were found in association with clinically diagnosed corticobasal syndrome, thereby establishing corticobasal syndrome as part of ANXA11 clinical spectrum. In iPSC-derived neurons expressing mutant ANXA11, we found decreased colocalization of lysosomes and decreased neuritic RNA as well as decreased nuclear TDP-43 and increased formation of cryptic exons compared to controls. Multiomic assessment of the P93S variant in iPSC-derived neurons and microglia indicates that the pathogenic omic signature in neurons is modest compared to microglia. Additionally, omic studies reveal that immune dysregulation and interferon signaling pathways in microglia are central to disease. Collectively, these findings identify a new pathogenic variant in ANXA11, expand the range of clinical syndromes caused by ANXA11 mutations, and implicate both neuronal and microglia dysfunction in ANXA11 pathophysiology. This work illustrates the potential for iPSC-derived cellular models to revolutionize the variant annotation process and provides a generalizable approach to determining causality of novel variants across genes.

A Kuhnian revolution in molecular biology: Most genes in complex organisms express regulatory RNAs

Thomas Kuhn described the progress of science as comprising occasional paradigm shifts separated by interludes of 'normal science'. The paradigm that has held sway since the inception of molecular biology is that genes (mainly) encode proteins. In parallel, theoreticians posited that mutation is random, inferred that most of the genome in complex organisms is non-functional, and asserted that somatic information is not communicated to the germline. However, many anomalies appeared, particularly in plants and animals: the strange genetic phenomena of paramutation and transvection; introns; repetitive sequences; a complex epigenome; lack of scaling of (protein-coding) genes and increase in 'noncoding' sequences with developmental complexity; genetic loci termed 'enhancers' that control spatiotemporal gene expression patterns during development; and a plethora of 'intergenic', overlapping, antisense and intronic transcripts. These observations suggest that the original conception of genetic information was deficient and that most genes in complex organisms specify regulatory RNAs, some of which convey intergenerational information. Also see the video abstract here: https://youtu.be/qxeGwahBANw.

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.

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes

Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.

Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology

Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.

LEAfing through literature: late embryogenesis abundant proteins coming of age-achievements and perspectives

To deal with increasingly severe periods of dehydration related to global climate change, it becomes increasingly important to understand the complex strategies many organisms have developed to cope with dehydration and desiccation. While it is undisputed that late embryogenesis abundant (LEA) proteins play a key role in the tolerance of plants and many anhydrobiotic organisms to water limitation, the molecular mechanisms are not well understood. In this review, we summarize current knowledge of the physiological roles of LEA proteins and discuss their potential molecular functions. As these are ultimately linked to conformational changes in the presence of binding partners, post-translational modifications, or water deprivation, we provide a detailed summary of current knowledge on the structure-function relationship of LEA proteins, including their disordered state in solution, coil to helix transitions, self-assembly, and their recently discovered ability to undergo liquid-liquid phase separation. We point out the promising potential of LEA proteins in biotechnological and agronomic applications, and summarize recent advances. We identify the most relevant open questions and discuss major challenges in establishing a solid understanding of how these intriguing molecules accomplish their tasks as cellular sentinels at the limits of surviving water scarcity.

Insights from analyses of low complexity regions with canonical methods for protein sequence comparison

Low complexity regions are fragments of protein sequences composed of only a few types of amino acids. These regions frequently occur in proteins and can play an important role in their functions. However, scientists are mainly focused on regions characterized by high diversity of amino acid composition. Similarity between regions of protein sequences frequently reflect functional similarity between them. In this article, we discuss strengths and weaknesses of the similarity analysis of low complexity regions using BLAST, HHblits and CD-HIT. These methods are considered to be the gold standard in protein similarity analysis and were designed for comparison of high complexity regions. However, we lack specialized methods that could be used to compare the similarity of low complexity regions. Therefore, we investigated the existing methods in order to understand how they can be applied to compare such regions. Our results are supported by exploratory study, discussion of amino acid composition and biological roles of selected examples. We show that existing methods need improvements to efficiently search for similar low complexity regions. We suggest features that have to be re-designed specifically for comparing low complexity regions: scoring matrix, multiple sequence alignment, e-value, local alignment and clustering based on a set of representative sequences. Results of this analysis can either be used to improve existing methods or to create new methods for the similarity analysis of low complexity regions.

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

A major challenge to the characterization of intrinsically disordered regions (IDRs), which are widespread in the proteome, but relatively poorly understood, is the identification of molecular features that mediate functions of these regions, such as short motifs, amino acid repeats and physicochemical properties. Here, we introduce a proteome-scale feature discovery approach for IDRs. Our approach, which we call “reverse homology”, exploits the principle that important functional features are conserved over evolution. We use this as a contrastive learning signal for deep learning: given a set of homologous IDRs, the neural network has to correctly choose a held-out homolog from another set of IDRs sampled randomly from the proteome. We pair reverse homology with a simple architecture and standard interpretation techniques, and show that the network learns conserved features of IDRs that can be interpreted as motifs, repeats, or bulk features like charge or amino acid propensities. We also show that our model can be used to produce visualizations of what residues and regions are most important to IDR function, generating hypotheses for uncharacterized IDRs. Our results suggest that feature discovery using unsupervised neural networks is a promising avenue to gain systematic insight into poorly understood protein sequences.

Intrinsically disordered regions (IDRs) are widespread in proteins but are poorly understood on a systematic level because they evolve too rapidly for classic bioinformatics methods to be effective. We designed a neural network that learns what features (for example, electrostatic charge, or the presence of certain motifs) might be important to the function of IDRs, even when we don’t have prior knowledge of function. Our neural network learns by exploiting principles of evolution. Important features tend to be conserved over species, so guessing what sequences evolved from the same common ancestor helps the neural network identify these features. Importantly, training a neural network this way can be defined as a fully automatic operation, so no manual effort is required. After our neural network is trained, we can apply interpretation techniques to understand what kinds of features are important to IDRs globally in the proteome, and to form hypotheses about specific IDRs. We show that many of the features our neural network learns are consistent with features we already know to be important to IDRs. We hope that our neural network can be applied to help biologists form hypotheses about poorly characterized IDRs.

Intrinsic disorder, extraterrestrial peptides, and prebiotic life on the earth

The discovery of mechanisms for the synthesis of homo-polymeric oligopeptides, such as polyglycine under conditions relevant to the astrophysical environment as well as in scenarios resembling primordial conditions that prevailed soon after Earth was formed, raises hopes in the search of extraterrestrial life. It also raises the possibility of extraterrestrial contribution to origin of life on Earth in the form of simple polypeptides. Bioinformatics analyses strongly predict such homo-polymeric peptides to be intrinsically disordered underscoring the potential involvement of IDPs in the origin of life which, even in its simplest form, could emerge spontaneously by autocatalysis of the primordial IDPs in self-organizing systems that evolved over time following natural selection.Communicated by Ramaswamy H. Sarma.

The return of the rings: Evolutionary convergence of aromatic residues in the intrinsically disordered regions of RNA-binding proteins for liquid-liquid phase separation

Aromatic residues appeared relatively late in the evolution of protein sequences to stabilize the globular proteins' folding core and are less in the intrinsically disordered regions (IDRs). Recent advances in protein liquid-liquid phase separation (LLPS) studies have also shown that aromatic residues in IDRs often act as "stickers" to promote multivalent interactions in forming higher-order oligomers. To study how general these structure-promoting residues are in IDRs, we compared levels of sequence disorder in RNA binding proteins (RBPs), which are often found to undergo LLPS, and the human proteome. We found that aromatic residues appear more frequently than expected in the IDRs of RBPs and, through multiple sequence alignment analysis, those aromatic residues are often conserved among chordates. Using TDP-43, FUS, and some other well-studied LLPS proteins as examples, the conserved aromatic residues are important to their LLPS-related functions. These analyses suggest that aromatic residues may have contributed twice to evolution: stabilizing structured proteins and assembling biomolecular condensates.

idpr: A package for profiling and analyzing Intrinsically Disordered Proteins in R

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are proteins or protein-domains that do not have a single native structure, rather, they are a class of flexible peptides that can rapidly adopt multiple conformations. IDPs are quite abundant, and their dynamic characteristics provide unique advantages for various biological processes. The field of “unstructured biology” has emerged, in part, because of numerous computational studies that had identified the unique characteristics of IDPs and IDRs. The package ‘idpr’, short for Intrinsically Disordered Proteins in R, implements several R functions that match the established characteristics of IDPs to protein sequences of interest. This includes calculations of residue composition, charge-hydropathy relationships, and predictions of intrinsic disorder. Additionally, idpr integrates several amino acid substitution matrices and calculators to supplement IDP-based workflows. Overall, idpr aims to integrate tools for the computational analysis of IDPs within R, facilitating the analysis of these important, yet under-characterized, proteins. The idpr package can be downloaded from Bioconductor (https://bioconductor.org/packages/idpr/).

Identification of Intrinsically Disordered Proteins and Regions in a Non-Model Insect Species Ostrinia nubilalis (Hbn.)

Research in previous decades has shown that intrinsically disordered proteins (IDPs) and regions in proteins (IDRs) are as ubiquitous as highly ordered proteins. Despite this, research on IDPs and IDRs still has many gaps left to fill. Here, we present an approach that combines wet lab methods with bioinformatics tools to identify and analyze intrinsically disordered proteins in a non-model insect species that is cold-hardy. Due to their known resilience to the effects of extreme temperatures, these proteins likely play important roles in this insect's adaptive mechanisms to sub-zero temperatures. The approach involves IDP enrichment by sample heating and double-digestion of proteins, followed by peptide and protein identification. Next, proteins are bioinformatically analyzed for disorder content, presence of long disordered regions, amino acid composition, and processes they are involved in. Finally, IDP detection is validated with an in-house 2D PAGE. In total, 608 unique proteins were identified, with 39 being mostly disordered, 100 partially disordered, 95 nearly ordered, and 374 ordered. One-third contain at least one long disordered segment. Functional information was available for only 90 proteins with intrinsic disorders out of 312 characterized proteins. Around half of the 90 proteins are cytoskeletal elements or involved in translational processes.

BMI1 Silencing Induces Mitochondrial Dysfunction in Lung Epithelial Cells Exposed to Hyperoxia

Acute Lung Injury (ALI), characterized by bilateral pulmonary infiltrates that restrict gas exchange, leads to respiratory failure. It is caused by an innate immune response with white blood cell infiltration of the lungs, release of cytokines, an increase in reactive oxygen species (ROS), oxidative stress, and changes in mitochondrial function. Mitochondrial alterations, changes in respiration, ATP production and the unbalancing fusion and fission processes are key events in ALI pathogenesis and increase mitophagy. Research indicates that BMI1 (B cell-specific Moloney murine leukemia virus integration site 1), a protein of the Polycomb repressive complex 1, is a cell cycle and survival regulator that plays a role in mitochondrial function. BMI1-silenced cultured lung epithelial cells were exposed to hyperoxia to determine the role of BMI1 in mitochondrial metabolism. Its expression significantly decreases in human lung epithelial cells (H441) following hyperoxic insult, as determined by western blot, Qrt-PCR, and functional analysis. This decrease correlates with an increase in mitophagy proteins, PINK1, Parkin, and DJ1; an increase in the expression of tumor suppressor PTEN; changes in the expression of mitochondrial biomarkers; and decreases in the oxygen consumption rate (OCR) and tricarboxylic acid enzyme activity. Our bioinformatics analysis suggested that the BMI1 multifunctionality is determined by its high level of intrinsic disorder that defines the ability of this protein to bind to numerous cellular partners. These results demonstrate a close relationship between BMI1 expression and mitochondrial health in hyperoxia-induced acute lung injury (HALI) and indicate that BMI1 is a potential therapeutic target to treat ALI and Acute Respiratory Distress Syndrome.

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.

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.

A targeted bioinformatics approach identifies highly variable cell surface proteins that are unique to Glomeromycotina

Diversity in arbuscular mycorrhizal fungi (AMF) contributes to biodiversity and resilience in natural environments and healthy agricultural systems. Functional complementarity exists among species of AMF in symbiosis with their plant hosts, but the molecular basis of this is not known. We hypothesise this is in part due to the difficulties that current sequence assembly methodologies have assembling sequences for intrinsically disordered proteins (IDPs) due to their low sequence complexity. IDPs are potential candidates for functional complementarity because they often exist as extended (non-globular) proteins providing additional amino acids for molecular interactions. Rhizophagus irregularis arabinogalactan-protein-like proteins (AGLs) are small secreted IDPs with no known orthologues in AMF or other fungi. We developed a targeted bioinformatics approach to identify highly variable AGLs/IDPs in RNA-sequence datasets. The approach includes a modified multiple k-mer assembly approach (Oases) to identify candidate sequences, followed by targeted sequence capture and assembly (mirabait-mira). All AMF species analysed, including the ancestral family Paraglomeraceae, have small families of proteins rich in disorder promoting amino acids such as proline and glycine, or glycine and asparagine. Glycine- and asparagine-rich proteins also were found in Geosiphon pyriformis (an obligate symbiont of a cyanobacterium), from the same subphylum (Glomeromycotina) as AMF. The sequence diversity of AGLs likely translates to functional diversity, based on predicted physical properties of tandem repeats (elastic, amyloid, or interchangeable) and their broad pI ranges. We envisage that AGLs/IDPs could contribute to functional complementarity in AMF through processes such as self-recognition, retention of nutrients, soil stability, and water movement.

Examining the Ensembles of Amyloid-β Monomer Variants and Their Propensities to Form Fibers Using an Energy Landscape Visualization Method

The amyloid-β (Aβ) monomer, an intrinsically disordered peptide, is produced by the cleavage of the amyloid precursor protein, leading to Aβ-40 and Aβ-42 as major products. These two isoforms generate pathological aggregates, whose accumulation correlates with Alzheimer's disease (AD). Experiments have shown that even though the natural abundance of Aβ-42 is smaller than that for Aβ-40, the Aβ-42 is more aggregation-prone compared to Aβ-40. Moreover, several single-point mutations are associated with early onset forms of AD. This work analyzes coarse-grained associative-memory, water-mediated, structure and energy model (AWSEM) simulations of normal Aβ-40 and Aβ-42 monomers, along with six single-point mutations associated with early onset disease. We analyzed the simulations using the energy landscape visualization method (ELViM), a reaction-coordinate-free approach suited to explore the frustrated energy landscapes of intrinsically disordered proteins. ELViM is shown to distinguish the monomer ensembles of variants that rapidly form fibers from those that do not form fibers as readily. It also delineates the amino acid contacts characterizing each ensemble. The results shed light on the potential of ELViM to probe intrinsically disordered proteins.

NLIP and HAD-like Domains of Pah1 and Lipin 1 Phosphatidate Phosphatases Are Essential for Their Catalytic Activities

Saccharomyces cerevisiae Pah1 phosphatidate phosphatase (PAP) catalyzes the dephosphorylation of phosphatidate to yield diacylglycerol, controlling phospholipids and triacylglycerol metabolisms. Pah1 and human Lipin 1 are intrinsically disordered proteins with 56% and 43% unfolded regions, respectively. Truncation analysis of the conserved and non-conserved regions showed that N- and C-conserved regions are essential for the catalytic activity of Pah1. PAP activities can be detected in the conserved N-terminal Lipin (NLIP) domain and C-terminal Lipin (CLIP)/haloacid dehalogenase (HAD)-like domain of Pah1 and Lipin 1, suggesting that the evolutionarily conserved domains are essential for the catalytic activity. The removal of disordered hydrophilic regions drastically reduced the protein solubility of Pah1. Thioredoxin is an efficient fusion protein for production of soluble NLIP–HAD recombinant proteins in Escherichia coli.

Design in biology and rational design in vaccinology: A conceptual analysis

This review discusses the philosophical foundations of what used to be called "the scientific method" and is nowadays often known as the scientific attitude. It used to be believed that scientific theories and methods aimed at the truth especially in the case of physics, chemistry and astronomy because these sciences were able to develop numerous scientific laws that made it possible to understand and predict many physical phenomena. The situation is different in the case of the biological sciences which deal with highly complex living organisms made up of huge numbers of constituents that undergo continuous dynamic processes; this leads to novel emergent properties in organisms that cannot be predicted because they are not present in the constituents before they have interacted with each other. This is one of the reasons why there are no universal scientific laws in biology. Furthermore, all scientific theories can only achieve a restricted level of predictive success because they remain valid only under the limited range of conditions that were used for establishing the theory' in the first place. Many theories that used to be accepted were subsequently shown to be false, demonstrating that scientific theories always remain tentative and can never be proven beyond and doubt. It is ironical that as scientists have finally accepted that approximate truths are perfectly adequate and that absolute truth is an illusion, a new irrational sociological phenomenon called Post-Truth conveyed by social media, the Internet and fake news has developed in the Western world that is convincing millions of people that truth simply does not exist. Misleading information is circulated with the intention to deceive and science denialism is promoted by denying the remarkable achievements of science and technology during the last centuries. Although the concept of intentional design is widely used to describe the methods that biologists use to make discoveries and inventions, it will be argued that the term is not appropriate for explaining the appearance of life on our planet nor for describing the scientific creativity of scientific investigators. The term rational for describing the development of new vaccines is also unjustified. Because the analysis of the COVID-19 pandemic requires contributions from biomedical and psycho-socioeconomic sciences, one scientific method alone would be insufficient for combatting the pandemic.

Conformational dynamics of 13 amino acids long NSP11 of SARS-CoV-2 under membrane mimetics and different solvent conditions

The intrinsically disordered proteins/regions (IDPs/IDPRs) are known to be responsible for multiple cellular processes and are associated with many chronic diseases. In viruses, the existence of a disordered proteome is also proven and is related to its conformational dynamics inside the host. The SARS-CoV-2 has a large proteome, in which, structure and functions of all proteins are not known yet, along with non-structural protein 11 (nsp11). In this study, we have performed extensive experimentation on nsp11. Our results based on the CD spectroscopy gives characteristic disordered spectrum for IDPs. Further, we investigated the conformational behavior of nsp11 in the presence of membrane mimetic environment, α-helix inducer, and natural osmolyte. In the presence of negatively charged and neutral liposomes, nsp11 remains disordered. However, with SDS micelle, it adopted an α-helical conformation, suggesting the helical propensity of nsp11. Finally, we again confirmed the IDP behavior of nsp11 using MD simulations. In future, this conformational dynamic study could help to clarify its functional importance in SARS-CoV-2 infection.

RAD51AP1 mediates RAD51 activity through nucleosome interaction

RAD51-associated protein 1 (RAD51AP1) is a key protein in the homologous recombination (HR) DNA repair pathway. Loss of RAD51AP1 leads to defective HR, genome instability, and telomere erosion. RAD51AP1 physically interacts with the RAD51 recombinase and promotes RAD51-mediated capture of donor DNA, synaptic complex assembly, and displacement-loop formation when tested with nucleosome-free DNA substrates. In cells, however, DNA is packaged into chromatin, posing an additional barrier to the complexities of the HR reaction. In this study, we show that RAD51AP1 binds to nucleosome core particles (NCPs), the minimum basic unit of chromatin in which approximately two superhelical turns of 147 bp double-stranded DNA are wrapped around one histone octamer with no free DNA ends remaining. We identified a C-terminal region in RAD51AP1, including its previously mapped DNA-binding domain, as critical for mediating the association between RAD51AP1 and both the NCP and the histone octamer. Using in vitro surrogate assays of HR activity, we show that RAD51AP1 is capable of promoting duplex DNA capture and initiating joint-molecule formation with the NCP and chromatinized template DNA, respectively. Together, our results suggest that RAD51AP1 directly assists in the RAD51-mediated search for donor DNA in chromatin. We present a model, in which RAD51AP1 anchors the DNA template through affinity for its nucleosomes to the RAD51-ssDNA nucleoprotein filament.

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

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

Proteostasis in the Male and Female Germline: A New Outlook on the Maintenance of Reproductive Health

For fully differentiated, long lived cells the maintenance of protein homeostasis (proteostasis) becomes a crucial determinant of cellular function and viability. Neurons are the most well-known example of this phenomenon where the majority of these cells must survive the entire course of life. However, male and female germ cells are also uniquely dependent on the maintenance of proteostasis to achieve successful fertilization. Oocytes, also long-lived cells, are subjected to prolonged periods of arrest and are largely reliant on the translation of stored mRNAs, accumulated during the growth period, to support meiotic maturation and subsequent embryogenesis. Conversely, sperm cells, while relatively ephemeral, are completely reliant on proteostasis due to the absence of both transcription and translation. Despite these remarkable, cell-specific features there has been little focus on understanding protein homeostasis in reproductive cells and how/whether proteostasis is "reset" during embryogenesis. Here, we seek to capture the momentum of this growing field by highlighting novel findings regarding germline proteostasis and how this knowledge can be used to promote reproductive health. In this review we capture proteostasis in the context of both somatic cell and germline aging and discuss the influence of oxidative stress on protein function. In particular, we highlight the contributions of proteostasis changes to oocyte aging and encourage a focus in this area that may complement the extensive analyses of DNA damage and aneuploidy that have long occupied the oocyte aging field. Moreover, we discuss the influence of common non-enzymatic protein modifications on the stability of proteins in the male germline, how these changes affect sperm function, and how they may be prevented to preserve fertility. Through this review we aim to bring to light a new trajectory for our field and highlight the potential to harness the germ cell's natural proteostasis mechanisms to improve reproductive health. This manuscript will be of interest to those in the fields of proteostasis, aging, male and female gamete reproductive biology, embryogenesis, and life course health.

IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell

Intrinsic disorder can be found in all proteomes of all kingdoms of life and in viruses, being particularly prevalent in the eukaryotes. We conduct a comprehensive analysis of the intrinsic disorder in the human proteins while mapping them into 24 compartments of the human cell. In agreement with previous studies, we show that human proteins are significantly enriched in disorder relative to a generic protein set that represents the protein universe. In fact, the fraction of proteins with long disordered regions and the average protein-level disorder content in the human proteome are about 3 times higher than in the protein universe. Furthermore, levels of intrinsic disorder in the majority of human subcellular compartments significantly exceed the average disorder content in the protein universe. Relative to the overall amount of disorder in the human proteome, proteins localized in the nucleus and cytoskeleton have significantly increased amounts of disorder, measured by both high disorder content and presence of multiple long intrinsically disordered regions. We empirically demonstrate that, on average, human proteins are assigned to 2.3 subcellular compartments, with proteins localized to few subcellular compartments being more disordered than the proteins that are localized to many compartments. Functionally, the disordered proteins localized in the most disorder-enriched subcellular compartments are primarily responsible for interactions with nucleic acids and protein partners. This is the first-time disorder is comprehensively mapped into the human cell. Our observations add a missing piece to the puzzle of functional disorder and its organization inside the cell.

On the irrationality of rational design of an HIV vaccine in light of protein intrinsic disorder

The lack of progress in finding an efficient vaccine for a human immunodeficiency virus (HIV) is daunting. In fact, this search has spanned nearly four decades without much success. There are several objective reasons for such a failure, which include the highly glycosylated nature of HIV-1, the presence of neotopes, and high mutation rates. This article argues that the presence of highly flexible and intrinsically disordered regions in both human anti-HIV-1 antibodies and the major HIV-1immunogen, its surface glycoprotein gp120, represent one of the major causes for the lack of success in utilization of structure-based reverse vaccinology.

Fundamental Challenges and Outlook in Simulating Liquid-Liquid Phase Separation of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) populate an ensemble of dynamic conformations, making their structural characterization by experiments challenging. Many IDPs undergo liquid-liquid phase separation into dense membraneless organelles with myriad cellular functions. Multivalent interactions in low-complexity IDPs promote the formation of these subcellular coacervates. While solution NMR, Förster resonance energy transfer (FRET), and small-angle X-ray scattering (SAXS) studies on IDPs have their own challenges, recent computational methods draw a rational trade-off to characterize the driving forces underlying phase separation. In this Perspective, we critically evaluate the scope of approximation-free field theoretic simulations, well-tempered ensemble methods, enhanced sampling techniques, coarse-grained force fields, and slab simulation approaches to offer an improved understanding of phase separation. A synergy between simulation length scale and model resolution would reduce the existing caveats and enable theories of polymer physics to elucidate finer details of liquid-liquid phase separation (LLPS). These computational advances offer promise for rigorous characterization of the IDP proteome and designing peptides with tunable material and self-assembly properties.

Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

With over 60 disorder predictors, users need help navigating the predictor selection task. We review 28 surveys of disorder predictors, showing that only 11 include assessment of predictive performance. We identify and address a few drawbacks of these past surveys. To this end, we release a novel benchmark dataset with reduced similarity to the training sets of the considered predictors. We use this dataset to perform a first-of-its-kind comparative analysis that targets two large functional families of disordered proteins that interact with proteins and with nucleic acids. We show that limiting sequence similarity between the benchmark and the training datasets has a substantial impact on predictive performance. We also demonstrate that predictive quality is sensitive to the use of the well-annotated order and inclusion of the fully structured proteins in the benchmark datasets, both of which should be considered in future assessments. We identify three predictors that provide favorable results using the new benchmark set. While we find that VSL2B offers the most accurate and robust results overall, ESpritz-DisProt and SPOT-Disorder perform particularly well for disordered proteins. Moreover, we find that predictions for the disordered protein-binding proteins suffer low predictive quality compared to generic disordered proteins and the disordered nucleic acids-binding proteins. This can be explained by the high disorder content of the disordered protein-binding proteins, which makes it difficult for the current methods to accurately identify ordered regions in these proteins. This finding motivates the development of a new generation of methods that would target these difficult-to-predict disordered proteins. We also discuss resources that support users in collecting and identifying high-quality disorder predictions.

Roles, Characteristics, and Analysis of Intrinsically Disordered Proteins: A Minireview

In recent years, there has been a growing understanding that a significant fraction of the eukaryotic proteome is intrinsically disordered, and that these conformationally dynamic proteins play a myriad of vital biological roles in both normal and pathological states. In this review, selected examples of intrinsically disordered proteins are highlighted, with particular attention for a few which are relevant in neurological disorders and in viral infection. Next, the underlying causes for the intrinsic disorder are discussed, along with computational methods used to predict whether a given amino acid sequence is likely to adopt a folded or unfolded state in the solution. Finally, biophysical methods for the analysis of intrinsically disordered proteins will be discussed, as well as the unique challenges they pose in this context due to their highly dynamic nature.

Intrinsically Disordered Proteins: Insights from Poincaré, Waddington, and Lamarck

The past quarter-century may justly be referred to as a period analogous to the "Cambrian explosion" in the history of proteins. This period is marked by the appearance of the intrinsically disordered proteins (IDPs) on the scene since their discovery in the mid-1990s. Here, I first reflect on how we accidentally stumbled on these fascinating molecules. Next, I describe our research on the IDPs over the past decade and identify six areas as important for future research in this field. In addition, I draw on discoveries others in the field have made to present a more comprehensive essay. More specifically, I discuss the role of IDPs in two fundamental aspects of life: in phenotypic switching, and in multicellularity that marks one of the major evolutionary transitions. I highlight how serendipity, imagination, and an interdisciplinary approach embodying empirical evidence and theoretical insights from the works of Poincaré, Waddington, and Lamarck, shaped our thinking, and how this led us to propose the MRK hypothesis, a conceptual framework addressing phenotypic switching, the emergence of new traits, and adaptive evolution via nongenetic and IDP conformation-based mechanisms. Finally, I present a perspective on the evolutionary link between phenotypic switching and the origin of multicellularity.

Influence of aminoacyl-tRNA synthetase complex-interacting multifunctional protein 1 on epithelial differentiation and organization during lung development

Proper development of the respiratory bronchiole and alveolar epithelium proceeds through coordinated cross talk between the interface of epithelium and neighboring mesenchyme. Signals that facilitate and coordinate the cross talk as the bronchial forming canalicular stage transitions to construction of air-exchanging capillary-alveoli niche in the alveolar stage are poorly understood. Expressed within this decisive region, levels of aminoacyl-tRNA synthetase complex-interacting multifunctional protein 1 (AIMP1) inversely correlate with the maturation of the lung. The present study addresses the role of AIMP1 in lung development through the generation and characterization of Aimp1^-/- mutant mice. Mating of Aimp1^+/- produced offspring in expected Mendelian ratios throughout embryonic development. However, newborn Aimp1^-/- pups exhibited neonatal lethality with mild cyanosis. Imaging both structure and ultrastructure of Aimp1^-/- lungs showed disorganized bronchial epithelium, decreased type I but not type II cell differentiation, increased distal vessels, and disruption of E-cadherin deposition in cell-cell junctions. Supporting the in vivo findings of disrupted epithelial cell-cell junctions, in vitro biochemical experiments show that a portion of AIMP1 binds to phosphoinositides, the lipid anchor of proteins that have a fundamental role in both cellular membrane and actin cytoskeleton organization; a dramatic disruption in F-actin cytoskeleton was observed in Aimp1^-/- mouse embryonic fibroblasts. Such observed structural defects may lead to disrupted cell-cell boundaries. Together, these results suggest a requirement of AIMP1 in epithelial cell differentiation in proper lung development.

Japanese encephalitis virus - exploring the dark proteome and disorder-function paradigm

Japanese encephalitis virus (JEV) is one of the major causes of viral encephalitis all around the globe. Approximately 3 billion people in endemic areas are at risk of Japanese encephalitis. To develop a wholistic understanding of the viral proteome, it is important to investigate both its ordered and disordered proteins. However, the functional and structural significance of disordered regions in the JEV proteome has not been systematically investigated as of yet. To fill this gap, we used here a set of bioinformatics tools to analyze the JEV proteome for the predisposition of its proteins for intrinsic disorder and for the presence of the disorder-based binding regions (also known as molecular recognition features, MoRFs). We also analyzed all JEV proteins for the presence of the probable nucleic acid-binding (DNA and RNA) sites. The results of these computational studies are experimentally validated using JEV capsid protein as an illustrative example. In agreement with bioinformatic analysis, we found that the N-terminal region of the JEV capsid (residues 1-30) is intrinsically disordered. We showed that this region is characterized by the temperature response typical for highly disordered proteins. Furthermore, we have experimentally shown that this disordered N-terminal domain of a capsid protein has a noticeable 'gain-of-structure' potential. In addition, using DOPS liposomes, we demonstrated the presence of pronounced membrane-mediated conformational changes in the N-terminal region of JEV capsid. In our view, this disorder-centric analysis would be helpful for a better understanding of the JEV pathogenesis.

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.

Probing the Proteomics Dark Regions by VAILase Cleavage at Aliphatic Amino Acids

Proteomics emerges from the protein identification to protein functional elucidation, which depends to a large extent on the characterization of protein sequences. However, a large part of proteome sequences remains unannotated due to the limitation in proteolytic digestion by golden standard protease trypsin. Herein, we demonstrated that a cyanobacterial protease VAILase could specifically cleave at the short-chain aliphatic amino acids valine, alanine, leucine, isoleucine and threonine with cleavage specificity about 92% in total for proteomic analysis. The unique features of VAILase cleavage facilitate the characterization of most proteins and exhibit high complementarity to trypsin, and 22% of the covered sequences by VAILase are unique. VAILase can greatly improve the coverages of sequences with abundant aliphatic residues that are usually dark regions in conventional proteomic analysis, such as the transmembrane regions within anion exchanger 1 and photosystem II.

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.

Measuring Interactions Between Tau and Aggregation Inducers with Single-Molecule Förster Resonance Energy Transfer

Tau is an intrinsically disordered protein implicated in the pathogenesis of Alzheimer's disease and other neurodegenerative disorders. Here we describe the application of single-molecule Förster resonance energy transfer (smFRET) for the characterization of the interactions between tau and polyphosphate, an intracellular polymer that accelerates tau aggregation. We describe the design of tau constructs, purification and fluorescent labeling of tau, and details of acquisition and analysis of smFRET data. The protocols provided here outline an approach that may be applied to the study of other intrinsically disordered proteins and their binding partners.

Macromolecular crowding induces compaction and DNA binding in the disordered N-terminal domain of hUNG2

Many human DNA repair proteins have disordered domains at their N- or C-termini with poorly defined biological functions. We recently reported that the partially structured N-terminal domain (NTD) of human uracil DNA glycosylase 2 (hUNG2), functions to enhance DNA translocation in crowded environments and also targets the enzyme to single-stranded/double-stranded DNA junctions. To understand the structural basis for these effects we now report high-resolution heteronuclear NMR studies of the isolated NTD in the presence and absence of an inert macromolecular crowding agent (PEG8K). Compared to dilute buffer, we find that crowding reduces the degrees of freedom for the structural ensemble, increases the order of a PCNA binding motif and dramatically promotes binding of the NTD for DNA through a conformational selection mechanism. These findings shed new light on the function of this disordered domain in the context of the crowded nuclear environment.

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.

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.

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.