Introducing protein intrinsic disorder

PredIDR: Accurate prediction of protein intrinsic disorder regions using deep convolutional neural network

The involvement of protein intrinsic disorder in essential biological processes, it is well known in structural biology. However, experimental methods for detecting intrinsic structural disorder and directly measuring highly dynamic behavior of protein structure are limited. To address this issue, several computational methods to predict intrinsic disorder from protein sequences were developed and their performance is evaluated by the Critical Assessment of protein Intrinsic Disorder (CAID). In this paper, we describe a new computational method, PredIDR, which provides accurate prediction of intrinsically disordered regions in proteins, mimicking experimental X-ray missing residues. Indeed, missing residues in Protein Data Bank (PDB) were used as positive examples to train a deep convolutional neural network which produces two types of output for short and long regions. PredIDR took part in the second round of CAID and was as accurate as the top state-of-the-art IDR prediction methods. PredIDR can be freely used through the CAID Prediction Portal available at https://caid.idpcentral.org/portal or downloaded as a Singularity container from https://biocomputingup.it/shared/caid-predictors/.

Rlip76 in ageing and Alzheimer's disease: Focus on oxidative stress and mitochondrial mechanisms

RLIP76 (Rlip), a stress-responsive protein, plays a multifaceted role in cellular function. This protein acts primarily as a glutathione-electrophile conjugate (GS-E) transporter, crucial for detoxifying hazardous compounds and converting them into mercapturic acids. RLIP76 also modulates cytoskeletal motility and membrane plasticity through its role in the Ral-signaling pathway, interacting with RalA and RalB, key small GTPases involved in growth and metastasis. Beyond its ATP-dependent transport functions in various tissues, RLIP76 also demonstrates GTPase Activating Protein (GAP) activity towards Rac1 and Cdc42, with a preference for Ral-GTP over Ral-GDP. Its functions span critical physiological processes including membrane dynamics, oxidative stress response, and mitochondrial dynamics. The protein's widespread expression and evolutionary conservation underscore its significance. Our lab discovered that Rlip interacts with Alzheimer's disease (AD) proteins, amyloid beta and phosphorylated and induce oxidative stress, mitochondrial dysfnction and synaptic damage in AD. Our in vitro studies revealed that overexpression of Rlip reduces mitochondrial abnormalities. Further, our in vivo studies (Rlip+/- mice) revealed that a partial reduction of Rlip in mice (Rlip+/-), leads to mitochondrial abnormalities, elevated oxidative stress, and cognitive deficits resembling late-onset AD, emphasizing the protein's crucial role in neuronal health and disease. Finally, we discuss the experimental cross-breedings of overexpression of mice Rlip TG/TG or Rlip + /- mice with Alzheimer's disease models - earlyonset 5XFAD, late-onset APPKI and Tau transgenic mice, providing new insights into RLIP76's role in AD progression and development. This review summarizes RLIP76's structure, function, and cellular pathways, highlighting its implications in AD and its potential as a therapeutic target.

Accurate and Fast Prediction of Intrinsic Disorder Using flDPnn

Intrinsically disordered proteins (IDPs) that include one or more intrinsically disordered regions (IDRs) are abundant across all domains of life and viruses and play numerous functional roles in various cellular processes. Due to a relatively low throughput and high cost of experimental techniques for identifying IDRs, there is a growing need for fast and accurate computational algorithms that accurately predict IDRs/IDPs from protein sequences. We describe one of the leading disorder predictors, flDPnn. Results from a recent community-organized Critical Assessment of Intrinsic Disorder (CAID) experiment show that flDPnn provides fast and state-of-the-art predictions of disorder, which are supplemented with the predictions of several major disorder functions. This chapter provides a practical guide to flDPnn, which includes a brief explanation of its predictive model, descriptions of its web server and standalone versions, and a case study that showcases how to read and understand flDPnn's predictions.

Prediction of Disordered Linkers Using APOD

Intrinsically disordered linkers (DLs) connect protein domains and structural elements within domains and facilitate allosteric regulation. Computational studies suggest that thousands of proteins have DLs. Since there are only about 250 proteins with manually curated DL annotations (DisProt database ver. 9.3), computational approaches that make accurate predictions of DLs from the protein sequences are essential for reducing this annotation gap. To this end, we recently released the Accurate Predictor Of DLs (APOD) method. Empirical tests show that APOD achieves Area Under the ROC Curve (AUC) of 0.82 and Matthews Correlation Coefficient (MCC) of 0.42 on a low-similarity test dataset. We implement APOD as a freely available and convenient web server at https://yanglab.qd.sdu.edu.cn/APOD/ . This web server takes a protein sequence as the input and outputs an easy-to-parse prediction result, with the entire prediction process done on the server side. We also provide a standalone version of APOD for users who want to process large datasets of sequences. This version must be installed and run locally on the end user's computer. In this chapter, we overview APOD, explain how to locate and use the web server and the standalone implementation, and discuss how to read and interpret APOD's outputs. We also demonstrate utility of APOD based on a case study protein.

The strand exchange domain of tumor suppressor PALB2 is intrinsically disordered and promotes oligomerization-dependent DNA compaction

The partner and localizer of BRCA2 (PALB2) is a scaffold protein linking BRCA1 with BRCA2 and RAD51 during homologous recombination (HR). PALB2 interaction with DNA strongly enhances HR in cells, while the PALB2 DNA-binding domain (PALB2-DBD) supports DNA strand exchange in vitro. We determined that PALB2-DBD is intrinsically disordered beyond a single N-terminal α-helix. Coiled-coil mediated dimerization is stabilized by interaction between intrinsically disordered regions (IDRs) leading to a 2-fold structural compaction. Single-stranded (ss)DNA binding promotes additional structural compaction and protein tetramerization. Using confocal single-molecule FRET, we observed bimodal and oligomerization-dependent compaction of ssDNA bound to PALB2-DBD, suggesting a novel strand exchange mechanism. Bioinformatics analysis and preliminary observations indicate that PALB2 forms protein-nucleic acids condensates. Intrinsically disordered DBDs are prevalent in the human proteome. PALB2-DBD and similar IDRs may use a chaperone-like mechanism to aid formation and resolution of DNA and RNA multichain intermediates during DNA replication, repair and recombination.

Structure-based clustering and mutagenesis of bacterial tannases reveals the importance and diversity of active site-capping domains

Tannins are critical plant defense metabolites, enriched in bark and leaves, that protect against microorganisms and insects by binding to and precipitating proteins. Hydrolyzable tannins contain ester bonds which can be cleaved by tannases-serine hydrolases containing so-called "cap" domains covering their active sites. However, comprehensive insights into the biochemical properties and structural diversity of tannases are limited, especially regarding their cap domains. We here present a code pipeline for structure prediction-based hierarchical clustering to categorize the whole family of bacterial tannases, and have used it to discover new types of cap domains and other structural insertions among these enzymes. Subsequently, we used two recently identified tannases from the gut/soil bacterium Clostridium butyricum as model systems to explore the biochemical and structural properties of the cap domains of tannases. We demonstrate using molecular dynamics and mutagenesis that the cap domain covering the active site plays a major role in enzyme substrate preference, inhibition, and activity-despite not directly interacting with smaller substrates. The present work provides deeper knowledge into the mechanism, structural dynamics, and diversity of tannases. The structure-based clustering approach presents a new way of classifying any other enzyme family, and will be of relevance for enzyme types where activity is influenced by variable loop or insert regions appended to a core protein fold.

Global analysis of endogenous protein disorder in cells

Disorder and flexibility in protein structures are essential for biological function but can also contribute to diseases, such as neurodegenerative disorders. However, characterizing protein folding on a proteome-wide scale within biological matrices remains challenging. Here we present a method using a bifunctional chemical probe, named TME, to capture in situ, enrich and quantify endogenous protein disorder in cells. TME exhibits a fluorescence turn-on effect upon selective conjugation with proteins with free cysteines in surface-exposed and flexible environments-a distinctive signature of protein disorder. Using an affinity-based proteomic approach, we identify both basal disordered proteins and those whose folding status changes under stress, with coverage to proteins even of low abundance. In lymphoblastoid cells from individuals with Parkinson's disease and healthy controls, our TME-based strategy distinguishes the two groups more effectively than lysate profiling methods. High-throughput TME fluorescence and proteomics further reveal a universal cellular quality-control mechanism in which cells adapt to proteostatic stress by adopting aggregation-prone distributions and sequestering disordered proteins, as illustrated in Huntington's disease cell models.

Molecular recognition of peptides and proteins by cucurbit[n]urils: systems and applications

The development of methodology for attaching ligand binding sites to proteins of interest has accelerated biomedical science. Such protein tags have widespread applications as well as properties that significantly limit their utility. This review describes the mechanisms and applications of supramolecular systems comprising the synthetic receptors cucurbit[7]uril (Q7) or cucurbit[8]uril (Q8) and their polypeptide ligands. Molecular recognition of peptides and proteins occurs at sites of 1-3 amino acids with high selectivity and affinity via several distinct mechanisms, which are supported by extensive thermodynamic and structural studies in aqueous media. The commercial availability, low cost, high stability, and biocompatibility of these synthetic receptors has led to the development of myriad applications. This comprehensive review compiles the molecular recognition studies and the resulting applications with the goals of providing a valuable resource to the community and inspiring the next generation of innovation.

MFIB 2.0: a major update of the database of protein complexes formed by mutual folding of the constituting protein chains

While the majority of proteins with available structures are able to fold independently and mediate interactions only after acquiring their folded state, a subset of the known protein complexes contains protein chains that are intrinsically disordered in isolation. The Mutual Folding Induced by Binding (MFIB) database collects and classifies protein complexes, wherein all constituent protein chains would be unstable/disordered in isolation but fold into a well-defined 3D complex structure upon binding. This phenomenon is often termed as cooperative folding and binding or mutual synergistic folding (MSF). Here we present a major update to the database: we collected and annotated hundreds of new protein complexes fulfilling the criteria of MSF, leading to an almost six-fold increase in the size of the database. Many novel features have also been introduced, such as clustering of the complexes based on structural similarity and domain types, assigning different evidence levels to each entry and adding the evidence coverage label that allowed us to include complexes of multi(sub)domain monomers with partial MSF. The MFIB 2.0 database is available at https://mfib.pbrg.hu.

Profiling genetically driven alternative splicing across the Indonesian archipelago

One of the regulatory mechanisms influencing the functional capacity of genes is alternative splicing (AS). Previous studies exploring the splicing landscape of human tissues have shown that AS has contributed to human biology, especially in disease progression and the immune response. Nonetheless, this phenomenon remains poorly characterized across human populations, and it is unclear how genetic and environmental variation contribute to AS. Here, we examine a set of 115 Indonesian samples from three traditional island populations spanning the genetic ancestry cline that characterizes Island Southeast Asia. We conduct a global AS analysis between islands to ascertain the degree of functionally significant AS events and their consequences. Using an event-based statistical model, we detected over 1,500 significant differential AS events across all comparisons. Additionally, we identify over 6,000 genetic variants associated with changes in splicing (splicing quantitative trait loci [sQTLs]), some of which are driven by Papuan-like genetic ancestry, and only show partial overlap with other publicly available sQTL datasets derived from other populations. Computational predictions of RNA binding activity reveal that a fraction of these sQTLs directly modulate the binding propensity of proteins involved in the splicing regulation of immune genes. Overall, these results contribute toward elucidating the role of genetic variation in shaping gene regulation in one of the most diverse regions in the world.

Disentangling the Complexity in Protein Complexes Using Complementary Isotope-Labeling and Multiple-Receiver NMR Spectroscopy

Intrinsically disordered proteins are abundant in eukaryotic systems, but they remain largely elusive pharmacological targets. NMR spectroscopy proved to be a suitable method to study these proteins and their interaction with one another or with drug candidates. Although NMR can give atomistic information about these interplays, molecular complexity due to severe spectral overlap, limited sample stability, and quantity remain an issue and hamper widespread applications. Here, we propose an approach to simultaneously map protein-protein binding sites onto two interacting partners by employing a complementary isotope-labeling strategy and a multiple receiver NMR detection scheme. With one partner being 15N,2H labeled and the interacting one being 13C,1H-labeled, we exploited proton and carbon detection to obtain clean and easily readable information. The method is illustrated with an application to the 50 kDa ternary protein complex formed between the prominent oncogenic transcription factor complex Myc/MAX and the tumor suppressor BRCA1.

Conformational analysis of the IQSEC2 protein by statistical thermodynamics

Mutations in the IQSEC2 gene result in severe intellectual disability, epilepsy and autism. The primary function of IQSEC2 is to serve as a guanine exchange factor (GEF) controlling the activation of ARF6 which in turn mediates membrane trafficking and synaptic connections between neurons. As IQSEC2 is a large intrinsically disordered protein little is known of the structure of the protein and how this influences its function. Understanding this structure and function relationship is critical for the development of novel therapies to treat IQSEC2 disease. We therefore sought to identify IQSEC2 conformers in unfolded and folded states and analyze how conformers differ when binding to ARF6 and thereby influence GEF catalysis. We simulated the folding process of IQSEC2 by accelerated molecular dynamics (aMD). Following the ensemble method of Gibbs, we proposed that the number of microstates in the ensemble replicating a protein macroscopic system is the total number of MD snapshots sampled on the production MD trajectory. We divided the entire range of reaction coordinate into a series of consecutive, non-overlapping bins. Thermal fluctuations of biomolecules in local equilibrium states are Gaussian in form. To predict the free energy and entropy of different conformational states using statistical thermodynamics, the density of states was estimated taking into account how many MD snapshots constitute each conformational state. IQSEC2 dimers derived from the most stable folded and unfolded conformers of IQSEC2 were generated by protein-protein docking and then used to construct IQSEC2-ARF6 encounter complexes. We suggest that IQSEC2 folding and dimerization are two competing processes that may be used by nature to regulate the process of GDP exchange on ARF6 catalyzed by IQSEC2.

Exploring the shared pathogenic strategies of independently evolved effectors across distinct plant viruses

Plants have developed very diverse strategies to defend themselves against viral pathogens, among which plant hormones play pivotal roles. In response, some viruses have also deployed multifunctional viral effectors that effectively hijack key component hubs to counter or evade plant immune surveillance. Although significant progress has been made toward understanding counter-defense strategies that manipulate plant hormone regulatory molecules, these efforts have often been limited to an individual virus or specific host target/pathway. This review provides new insights into broad-spectrum antiviral responses in rice triggered by key components of phytohormone signaling, and highlights the common features of counter-defense strategies employed by distinct rice-infecting RNA viruses. These strategies involve the secretion of multifunctional virulence effectors that target the sophisticated phytohormone system, dampening immune responses by engaging with the same host targets. Additionally, the review provides an in-depth exploration of various viral effectors, emphasizing tertiary structure-based research and shared host targets. Understanding these conserved characteristics in detail may pave the way for molecular drug design, opening new opportunities to enhance broad-spectrum antiviral trials through precise engineering.

When an underdog becomes a major player: the role of protein structural disorder in the Atg8 conjugation system

The noncanonical ubiquitin-like conjugation cascade involving the E1 (Atg7), E2 (Atg3, Atg10), and E3 (Atg12-Atg5-Atg16 complex) enzymes is essential for incorporation of Atg8 into the growing phagophore via covalent linkage to PE. This process is an indispensable step in autophagy. Atg8 and E1-E3 enzymes are the first subset from the core autophagy protein machinery structures that were investigated in earlier studies by crystallographic analyses of globular domains. However, research over the past decade shows that many important functions in the conjugation machinery are mediated by intrinsically disordered protein regions (IDPRs) - parts of the protein that do not adopt a stable secondary or tertiary structure, which are inherently dynamic and well suited for protein-membrane interactions but are invisible in protein crystals. Here, we summarize earlier and recent findings on the autophagy conjugation machinery by focusing on the IDPRs. This summary reveals that IDPRs, originally considered dispensable, are in fact major players and a driving force in the function of the autophagy conjugation system. Abbreviation: AD, activation domain of Atg7; AH, amphipathic helix; AIM, Atg8-family interacting motif; CL, catalytic loop (of Atg7); CTD, C-terminal domain; FR, flexible region (of Atg3 or Atg10); GUV, giant unilammelar vesicles; HR, handle region (of Atg3); IDPR, intrinsically disordered protein region; IDPs: intrinsically disordered proteins; LIR, LC3-interacting region; NHD: N-terminal helical domain; NMR, nuclear magnetic resonance; PE, phosphatidylethanolamine; UBL, ubiquitin like.

Inhibitor Development for α-Synuclein Fibril's Disordered Region to Alleviate Parkinson's Disease Pathology

The amyloid fibrils of α-synuclein (α-syn) are crucial in the pathology of Parkinson's disease (PD), with the intrinsically disordered region (IDR) of its C-terminal playing a key role in interacting with receptors like LAG3 and RAGE, facilitating pathological neuronal spread and inflammation. In this study, we identified Givinostat (GS) as an effective inhibitor that disrupts the interaction of α-syn fibrils with receptors such as LAG3 and RAGE through high-throughput screening. By exploring the structure-activity relationship and optimizing GS, we developed several lead compounds, including GSD-16-24. Utilizing solution-state and solid-state NMR, along with cryo-EM techniques, we demonstrated that GSD-16-24 binds directly to the C-terminal IDR of α-syn monomer and fibril, preventing the fibril from binding to the receptors. Furthermore, GSD-16-24 significantly inhibits the association of α-syn fibrils with membrane receptors, thereby reducing neuronal propagation and pro-inflammatory effects of α-syn fibrils. Our findings introduce a novel approach to mitigate the pathological effects of α-syn fibrils by targeting their IDR with small molecules, offering potential leads for the development of clinical drugs to treat PD.

flDPnn2: Accurate and Fast Predictor of Intrinsic Disorder in Proteins

Prediction of the intrinsic disorder in protein sequences is an active research area, with well over 100 predictors that were released to date. These efforts are motivated by the functional importance and high levels of abundance of intrinsic disorder, combined with relatively low amounts of experimental annotations. The disorder predictors are periodically evaluated by independent assessors in the Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiments. The recently completed CAID2 experiment assessed close to 40 state-of-the-art methods demonstrating that some of them produce accurate results. In particular, flDPnn2 method, which is the successor of flDPnn that performed well in the CAID1 experiment, secured the overall most accurate results on the Disorder-NOX dataset in CAID2. flDPnn2 implements a number of improvements when compared to its predecessor including changes to the inputs, increased size of the deep network model that we retrained on a larger training set, and addition of an alignment module. Using results from CAID2, we show that flDPnn2 produces accurate predictions very quickly, modestly improving over the accuracy of flDPnn and reducing the runtime by half, to about 27 s per protein. flDPnn2 is freely available as a convenient web server at http://biomine.cs.vcu.edu/servers/flDPnn2/.

Experimental Considerations for the Evaluation of Viral Biomolecular Condensates

Biomolecular condensates are nonmembrane-bound assemblies of biological polymers such as protein and nucleic acids. An increasingly accepted paradigm across the viral tree of life is (a) that viruses form biomolecular condensates and (b) that the formation is required for the virus. Condensates can promote viral replication by promoting packaging, genome compaction, membrane bending, and co-opting of host translation. This review is primarily concerned with exploring methodologies for assessing virally encoded biomolecular condensates. The goal of this review is to provide an experimental framework for virologists to consider when designing experiments to (a) identify viral condensates and their components, (b) reconstitute condensation cell free from minimal components, (c) ask questions about what conditions lead to condensation, (d) map these questions back to the viral life cycle, and (e) design and test inhibitors/modulators of condensation as potential therapeutics. This experimental framework attempts to integrate virology, cell biology, and biochemistry approaches.

Dissecting Henipavirus W proteins conformational and fibrillation properties: contribution of their N- and C-terminal constituent domains

The Nipah and Hendra viruses are severe human pathogens. In addition to the P protein, their P gene also encodes the V and W proteins that share with P their N-terminal intrinsically disordered domain (NTD) and possess distinct C-terminal domains (CTDs). The W protein is a key player in the evasion of the host innate immune response. We previously showed that the W proteins are intrinsically disordered and can form amyloid-like fibrils. However, structural information on W CTD (CTDW) and its potential contribution to the fibrillation process is lacking. In this study, we demonstrate that CTDWS are disordered and able to form dimers mediated by disulfide bridges. We also show that the NTD and the CTDW interact with each other and that this interaction triggers both a gain of secondary structure and a chain compaction within the NTD. Finally, despite the lack of intrinsic fibrillogenic properties, we show that the CTDW favors the formation of fibrils by the NTD both in cis and in trans. Altogether, the results herein presented shed light on the molecular mechanisms underlying Henipavirus pathogenesis and may thus contribute to the development of targeted therapies.

Protein Fold Usages in Ribosomes: Another Glance to the Past

The analysis of protein fold usage, similar to codon usage, offers profound insights into the evolution of biological systems and the origins of modern proteomes. While previous studies have examined fold distribution in modern genomes, our study focuses on the comparative distribution and usage of protein folds in ribosomes across bacteria, archaea, and eukaryotes. We identify the prevalence of certain 'super-ribosome folds,' such as the OB fold in bacteria and the SH3 domain in archaea and eukaryotes. The observed protein fold distribution in the ribosomes announces the future power-law distribution where only a few folds are highly prevalent, and most are rare. Additionally, we highlight the presence of three copies of proto-Rossmann folds in ribosomes across all kingdoms, showing its ancient and fundamental role in ribosomal structure and function. Our study also explores early mechanisms of molecular convergence, where different protein folds bind equivalent ribosomal RNA structures in ribosomes across different kingdoms. This comparative analysis enhances our understanding of ribosomal evolution, particularly the distinct evolutionary paths of the large and small subunits, and underscores the complex interplay between RNA and protein components in the transition from the RNA world to modern cellular life. Transcending the concept of folds also makes it possible to group a large number of ribosomal proteins into five categories of urfolds or metafolds, which could attest to their ancestral character and common origins. This work also demonstrates that the gradual acquisition of extensions by simple but ordered folds constitutes an inexorable evolutionary mechanism. This observation supports the idea that simple but structured ribosomal proteins preceded the development of their disordered extensions.

Exploring Intrinsic Disorder in Human Synucleins and Associated Proteins

In this work, we explored the intrinsic disorder status of the three members of the synuclein family of proteins-α-, β-, and γ-synucleins-and showed that although all three human synucleins are highly disordered, the highest levels of disorder are observed in γ-synuclein. Our analysis of the peculiarities of the amino acid sequences and modeled 3D structures of the human synuclein family members revealed that the pathological mutations A30P, E46K, H50Q, A53T, and A53E associated with the early onset of Parkinson's disease caused some increase in the local disorder propensity of human α-synuclein. A comparative sequence-based analysis of the synuclein proteins from various evolutionary distant species and evaluation of their levels of intrinsic disorder using a set of commonly used bioinformatics tools revealed that, irrespective of their origin, all members of the synuclein family analyzed in this study were predicted to be highly disordered proteins, indicating that their intrinsically disordered nature represents an evolutionary conserved and therefore functionally important feature. A detailed functional disorder analysis of the proteins in the interactomes of the human synuclein family members utilizing a set of commonly used disorder analysis tools showed that the human α-synuclein interactome has relatively higher levels of intrinsic disorder as compared with the interactomes of human β- and γ- synucleins and revealed that, relative to the β- and γ-synuclein interactomes, α-synuclein interactors are involved in a much broader spectrum of highly diversified functional pathways. Although proteins interacting with three human synucleins were characterized by highly diversified functionalities, this analysis also revealed that the interactors of three human synucleins were involved in three common functional pathways, such as the synaptic vesicle cycle, serotonergic synapse, and retrograde endocannabinoid signaling. Taken together, these observations highlight the critical importance of the intrinsic disorder of human synucleins and their interactors in various neuronal processes.

Site-directed allostery perturbation to probe the negative regulation of hypoxia inducible factor-1α

The interaction between the intrinsically disordered transcription factor HIF-1α and the coactivator proteins p300/CBP is essential in the fast response to low oxygenation. The negative feedback regulator, CITED2, switches off the hypoxic response through a very efficient irreversible mechanism. The negative cooperativity with HIF-1α relies on the formation of a ternary intermediate that leads to allosteric structural changes in p300/CBP, in which the cooperative folding/binding of the CITED2 sequence motifs plays a key role. Understanding the contribution of a binding motif to the structural changes in relation to competition efficiency provides invaluable insights into the molecular mechanism. Our strategy is to site-directedly perturb the p300-CITED2 complex's structure without significantly affecting binding thermodynamics. In this way, the contribution of a sequence motif to the negative cooperativity with HIF-1α would mainly depend on the induced structural changes, and to a lesser extent on binding affinity. Using biophysical assays and NMR measurements, we show here that the interplay between the N-terminal tail and the rest of the binding motifs of CITED2 is crucial for the unidirectional displacement of HIF-1α. We introduce an advantageous approach for evaluating the roles of the different sequence parts with the help of motif-by-motif backbone perturbations.

Gonadal Transcriptomic Analysis Reveals Novel Sex-Related Genes in Bactrocera dorsalis

Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) is one of the most devastating agricultural pests worldwide due to its high reproductive and invasive abilities. The elucidation of its gonadal developmental characteristics and the identification of sex-related genes will provide a useful genetic basis for reproductive-based pest control. Here, the gonadal transcriptome of B. dorsalis was sequenced, and novel gonad-specific expressed genes were analyzed. A total of 1338, 336, 35, and 479 differentially expressed genes (DEGs) were found in the testis (TE), ovary (OV), female accessory gland (FAG), and male accessory gland (MAG), respectively. Furthermore, 463 highly expressed gonad-specific genes were identified, with the TE having the highest number of specific highly expressed genes, at 402, followed by 51 in the OV, 9 in the MAG, and only 1 in the FAG. Strikingly, approximately half of highly expressed gonad-specific genes were uncharacterized. Then, it was found that 35, 17, 3, 2, and 1 of 202 uncharacterized highly expressed TE-specific genes encoded proteins that contained transmembrane domains, signal peptides, high-mobility group boxes, the zinc finger domain, and the BTB/POZ domain, respectively. Interestingly, approximately 40% of uncharacterized highly expressed gonad-specific genes encoding proteins were not predicted to possess functional motifs or domains. Finally, the spatiotemporal expression and sequence characterization of six novel highly expressed gonad-specific genes were analyzed. Altogether, our findings provide a valuable dataset for future functional analyses of sex-related genes and potential target sites for pest control.

General Characterization of Properties of Ordered and Disordered Proteins by Wide-Line 1H NMR

Wide-line 1H NMR is an efficient spectroscopic method to determine the disorder tendency of a protein. It directly measures the properties of the hydration shell of proteins, delivering exact and measurable values of their disorder/order content. A comparison is performed between several globular and disordered proteins. The common properties of the subzero mobile hydration water of these two groups were investigated. The amount of the mobile hydration water and the shape of the melting diagram at subzero temperatures together provide a possibility to distinguish globular proteins from disordered proteins. The shape of the melting diagram also gives information about the presence of secondary structural elements. The disordered and globular protein regions' fundamentally different structures are reflected in their melting diagrams, allowing one to directly determine the level of disorder in a specific protein structure. Intrinsically disordered proteins bind water more strongly than globular proteins, which is shown by the somewhat higher temperature values where mobile hydration water first appears but with a significantly higher heterogeneity in the energy distributions of protein-water interactions.

Unveiling the genetic tapestry: Rare disease genomics of spinal muscular atrophy and phenylketonuria proteins

Rare diseases, defined by their low prevalence, present significant challenges, including delayed detection, expensive treatments, and limited research. This study delves into the genetic basis of two noteworthy rare diseases in Saudi Arabia: Phenylketonuria (PKU) and Spinal Muscular Atrophy (SMA). PKU, resulting from mutations in the phenylalanine hydroxylase (PAH) gene, exhibits geographical variability and impacts intellectual abilities. SMA, characterized by motor neuron loss, is linked to mutations in the survival of motor neuron 1 (SMN1) gene. Recognizing the importance of unveiling signature genomics in rare diseases, we conducted a quantitative study on PAH and SMN1 proteins of multiple organisms by employing various quantitative techniques to assess genetic variations. The derived signature-genomics contributes to a deeper understanding of these critical genes, paving the way for enhanced diagnostics for disorders associated with PAH and SMN1.

The strand exchange domain of tumor suppressor PALB2 is intrinsically disordered and promotes oligomerization-dependent DNA compaction

The Partner and Localizer of BRCA2 (PALB2) is a scaffold protein that links BRCA1 with BRCA2 to initiate homologous recombination (HR). PALB2 interaction with DNA strongly enhances HR efficiency in cells. The PALB2 DNA-binding domain (PALB2-DBD) supports strand exchange, a complex multistep reaction conducted by only a few proteins such as RecA-like recombinases and Rad52. Using bioinformatics analysis, small-angle X-ray scattering, circular dichroism, and electron paramagnetic spectroscopy, we determined that PALB2-DBD is an intrinsically disordered region (IDR) forming compact molten globule-like dimer. IDRs contribute to oligomerization synergistically with the coiled-coil interaction. Using confocal single-molecule FRET we demonstrated that PALB2-DBD compacts single-stranded DNA even in the absence of DNA secondary structures. The compaction is bimodal, oligomerization-dependent, and is driven by IDRs, suggesting a novel strand exchange mechanism. Intrinsically disordered proteins (IDPs) are prevalent in the human proteome. Novel DNA binding properties of PALB2-DBD and the complexity of strand exchange mechanism significantly expands the functional repertoire of IDPs. Multivalent interactions and bioinformatics analysis suggest that PALB2 function is likely to depend on formation of protein-nucleic acids condensates. Similar intrinsically disordered DBDs may use chaperone-like mechanism to aid formation and resolution of DNA and RNA multichain intermediates during DNA replication, repair and recombination.

Dynamics of Single-Chain Nanoparticles under Crowding: A Neutron Spin Echo Study

We present a neutron spin echo (NSE) investigation to examine the impact of macromolecular crowding on the dynamics of single-chain nanoparticles (SCNPs), serving as synthetic models for biomacromolecules with flexibility and internal degrees of freedom, such as intrinsically disordered proteins (IDPs). In particular, we studied the dynamics of a medium-size poly(methyl methacrylate) (PMMA)-based SCNP (33 kDa) in solutions with low- (10 kDa) and high- (100 kDa) molecular weight analogous deuterated PMMA linear crowders. The dynamic structure factors of the SCNPs in dilute solution show certain degrees of freedom, yet the analysis in terms of the Zimm model reveals high internal friction that effectively stiffens the chain-a phenomenon also observed for IDPs. Under crowding conditions, the internal dynamics remains essentially unchanged, but the center-of-mass diffusion slows down. The effective viscosity felt by the SCNPs at the timescales probed by NSE is lower than the macroscopic viscosity of the crowder solution, and it does not depend significantly on the molecular weight.

4,4-Difluoroproline as a Unique 19F NMR Probe of Proline Conformation

Despite the importance of proline conformational equilibria (trans versus cis amide and exo versus endo ring pucker) on protein structure and function, there is a lack of convenient ways to probe proline conformation. 4,4-Difluoroproline (Dfp) was identified to be a sensitive 19F NMR-based probe of proline conformational biases and cis-trans isomerism. Within model compounds and disordered peptides, the diastereotopic fluorines of Dfp exhibit similar chemical shifts (ΔδFF = 0-3 ppm) when a trans X-Dfp amide bond is present. In contrast, the diastereotopic fluorines exhibit a large (ΔδFF = 5-12 ppm) difference in chemical shift in a cis X-Dfp prolyl amide bond. DFT calculations, X-ray crystallography, and solid-state NMR spectroscopy indicated that ΔδFF directly reports on the relative preference of one proline ring pucker over the other: a fluorine which is pseudo-axial (i.e., the pro-4R-F in an exo ring pucker, or the pro-4S-F in an endo ring pucker) is downfield, while a fluorine which is pseudo-equatorial (i.e., pro-4S-F when exo, or pro-4R-F when endo) is upfield. Thus, when a proline is disordered (a mixture of exo and endo ring puckers, as at trans-Pro in peptides in water), it exhibits a small Δδ. In contrast, when the Pro is ordered (i.e., when one ring pucker is strongly preferred, as in cis-Pro amide bonds, where the endo ring pucker is strongly favored), a large Δδ is observed. Dfp can be used to identify inherent induced order in peptides and to quantify proline cis-trans isomerism. Using Dfp, we discovered that the stable polyproline II helix (PPII) formed in the denatured state (8 M urea) exhibits essentially equal populations of the exo and endo proline ring puckers. In addition, the data with Dfp suggested the specific stabilization of PPII by water over other polar solvents. These data strongly support the importance of carbonyl solvation and n → π* interactions for the stabilization of PPII. Dfp was also employed to quantify proline cis-trans isomerism as a function of phosphorylation and the R406W mutation in peptides derived from the intrinsically disordered protein tau. Dfp is minimally sterically disruptive and can be incorporated in expressed proteins, suggesting its broad application in understanding proline cis-trans isomerization, protein folding, and local order in intrinsically disordered proteins.

The green cupredoxin CopI is a multicopper protein able to oxidize Cu(I)

Anthropogenic activities in agriculture and health use the antimicrobial properties of copper. This has led to copper accumulation in the environment and contributed to the emergence of copper resistant microorganisms. Understanding bacterial copper homeostasis diversity is therefore highly relevant since it could provide valuable targets for novel antimicrobial treatments. The periplasmic CopI protein is a monodomain cupredoxin comprising several copper binding sites and is directly involved in copper resistance in bacteria. However, its structure and mechanism of action are yet to be determined. To study the different binding sites for cupric and cuprous ions and to understand their possible interactions, we have used mutants of the putative copper binding modules of CopI and spectroscopic methods to characterize their properties. We show that CopI is able to bind a cuprous ion in its central histidine/methionine-rich region and oxidize it thanks to its cupredoxin center. The resulting cupric ion can bind to a third site at the N-terminus of the protein. Nuclear magnetic resonance spectroscopy revealed that the central histidine/methionine-rich region exhibits a dynamic behavior and interacts with the cupredoxin binding region. CopI is therefore likely to participate in copper resistance by detoxifying the cuprous ions from the periplasm.

Hydrophobic Clusters Regulate Surface Hydration Dynamics of Bacillus subtilis Lipase A

The surface hydration diffusivity of Bacillus subtilis Lipase A (BSLA) has been characterized by low-field Overhauser dynamic nuclear polarization (ODNP) relaxometry using a series of spin-labeled constructs. Sites for spin-label incorporation were previously designed via an atomistic computational approach that screened for surface exposure, reflective of the surface hydration comparable to other proteins studied by this method, as well as minimal impact on protein function, dynamics, and structure of BSLA by excluding any surface site that participated in greater than 30% occupancy of a hydrogen bonding network within BSLA. Experimental ODNP relaxometry coupling factor results verify the overall surface hydration behavior for these BSLA spin-labeled sites similar to other globular proteins. Here, by plotting the ODNP parameters of relative diffusive water versus the relative bound water, we introduce an effective "phase-space" analysis, which provides a facile visual comparison of the ODNP parameters of various biomolecular systems studied to date. We find notable differences when comparing BSLA to other systems, as well as when comparing different clusters on the surface of BSLA. Specifically, we find a grouping of sites that correspond to the spin-label surface location within the two main hydrophobic core clusters of the branched aliphatic amino acids isoleucine, leucine, and valine cores observed in the BSLA crystal structure. The results imply that hydrophobic clustering may dictate local surface hydration properties, perhaps through modulation of protein conformations and samplings of the unfolded states, providing insights into how the dynamics of the hydration shell is coupled to protein motion and fluctuations.

Reexamining the diverse functions of arginine in biochemistry

Arginine in a free-state and as part of peptides and proteins shows distinct tendency to form clusters. In free-form, it has been found useful in cryoprotection, as a drug excipient for both solid and liquid formulations, as an aggregation suppressor, and an eluent in protein chromatography. In many cases, the mechanisms by which arginine acts in all these applications is either debatable or at least continues to attract interest. It is quite possible that arginine clusters may be involved in many such applications. Furthermore, it is possible that such clusters are likely to behave as intrinsically disordered polypeptides. These considerations may help in understanding the roles of arginine in diverse applications and may even lead to better strategies for using arginine in different situations.

Accurate and Fast Prediction of Intrinsically Disordered Protein by Multiple Protein Language Models and Ensemble Learning

Intrinsically disordered proteins (IDPs) play a vital role in various biological processes and have attracted increasing attention in the past few decades. Predicting IDPs from the primary structures of proteins offers a rapid and facile means of protein analysis without necessitating crystal structures. In particular, machine learning methods have demonstrated their potential in this field. Recently, protein language models (PLMs) are emerging as a promising approach to extracting essential information from protein sequences and have been employed in protein modeling to utilize their advantages of precision and efficiency. In this article, we developed a novel IDP prediction method named IDP-ELM to predict the intrinsically disordered regions (IDRs) as well as their functions including disordered flexible linkers and disordered protein binding. This method utilizes high-dimensional representations extracted from several state-of-the-art PLMs and predicts IDRs by ensemble learning based on bidirectional recurrent neural networks. The performance of the method was evaluated on two independent test data sets from CAID (critical assessment of protein intrinsic disorder prediction) and CAID2, indicating notable improvements in terms of area under the receiver operating characteristic (AUC), Matthew's correlation coefficient (MCC), and F1 score. Moreover, IDP-ELM requires solely protein sequences as inputs and does not entail a time-consuming process of protein profile generation, which is a prerequisite for most existing state-of-the-art methods, enabling an accurate, fast, and convenient tool for proteome-level analysis. The corresponding reproducible source code and model weights are available at https://github.com/xu-shi-jie/idp-elm.

Location of S-nitrosylated cysteines in protein three-dimensional structures

Although S-nitrosylation of cysteines is a common protein posttranslational modification, little is known about its three-dimensional structural features. This paper describes a systematic survey of the data available in the Protein Data Bank. Several interesting observations could be made. (1) As a result of radiation damage, S-nitrosylated cysteines (Snc) are frequently reduced, at least partially. (2) S-nitrosylation may be a protection against irreversible thiol oxidation; because the NO group of Snc is relatively accessible to the solvent, it may act as a cork to protect the sulfur atoms of cysteines from oxidation by molecular oxygen to sulfenic, sulfinic, and sulfonic acid; moreover, Snc are frequently found at the start or end of helices and strands and this might shield secondary structural elements from unfolding.

The disordered C-terminal tail of fungal LPMOs from phytopathogens mediates protein dimerization and impacts plant penetration

Lytic polysaccharide monooxygenases (LPMOs) are monocopper enzymes that oxidatively degrade various polysaccharides, such as cellulose. Despite extensive research on this class of enzymes, the role played by their C-terminal regions predicted to be intrinsically disordered (dCTR) has been overlooked. Here, we investigated the function of the dCTR of an LPMO, called CoAA9A, up-regulated during plant infection by Colletotrichum orbiculare, the causative agent of anthracnose. After recombinant production of the full-length protein, we found that the dCTR mediates CoAA9A dimerization in vitro, via a disulfide bridge, a hitherto-never-reported property that positively affects both binding and activity on cellulose. Using SAXS experiments, we show that the homodimer is in an extended conformation. In vivo, we demonstrate that gene deletion impairs formation of the infection-specialized cell called appressorium and delays penetration of the plant. Using immunochemistry, we show that the protein is a dimer not only in vitro but also in vivo when secreted by the appressorium. As these peculiar LPMOs are also found in other plant pathogens, our findings open up broad avenues for crop protection.

Best practices for the manual curation of intrinsically disordered proteins in DisProt

The DisProt database is a resource containing manually curated data on experimentally validated intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) from the literature. Developed in 2005, its primary goal was to collect structural and functional information into proteins that lack a fixed three-dimensional structure. Today, DisProt has evolved into a major repository that not only collects experimental data but also contributes to our understanding of the IDPs/IDRs roles in various biological processes, such as autophagy or the life cycle mechanisms in viruses or their involvement in diseases (such as cancer and neurodevelopmental disorders). DisProt offers detailed information on the structural states of IDPs/IDRs, including state transitions, interactions and their functions, all provided as curated annotations. One of the central activities of DisProt is the meticulous curation of experimental data from the literature. For this reason, to ensure that every expert and volunteer curator possesses the requisite knowledge for data evaluation, collection and integration, training courses and curation materials are available. However, biocuration guidelines concur on the importance of developing robust guidelines that not only provide critical information about data consistency but also ensure data acquisition.This guideline aims to provide both biocurators and external users with best practices for manually curating IDPs and IDRs in DisProt. It describes every step of the literature curation process and provides use cases of IDP curation within DisProt. Database URL: https://disprot.org/.

Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model

A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning-based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long timescale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We observe that folding-upon-binding predominantly proceeds through a multi-step induced fit mechanism with several intermediates and do not find evidence for the existence of canonical conformational selection pathways. We observe four kinetically separated native-like bound states that interconvert on timescales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.

Invariant BECN1 CXXC motifs bind Zn2+ and regulate structure and function of the BECN1 intrinsically disordered region

ABBREVIATIONS

AFM: aromatic finger mutant; BH3D: BCL2 homology 3 domain; CCD: coiled-coil domain; CD: circular dichroism spectroscopy; [CysDM1]: C18S and C21S double mutant; [CysDM2]: C137S, and C140S double mutant; [CysTM], C18S, C21S, C137S, and C140S tetrad mutant; Dmax: maximum particle diameter; dRI, differential refractive index; EFA: evolving factor analysis; FHD: flexible helical domain; FL: full length; GFP: green fluorescent protein; HDX-MS: hydrogen/deuterium exchange mass spectrometry; ICP-MS: inductively coupled plasma mass spectrometry; IDR: intrinsically disordered region; ITC, isothermal titration calorimetry; MALS, multi angle light scattering; MBP: maltose-binding protein; MoRFs: molecular recognition features; P(r): pairwise-distance distribution; PtdIns3K: class III phosphatidylinositol 3-kinase; Rg: radius of gyration; SASBDB: small angle scattering biological data bank; SEC: size-exclusion chromatography; SEC-SAXS: size-exclusion chromatography in tandem with small angle X-ray scattering; TEV: tobacco-etch virus; TFE: 2,2,2-trifluoroethanol; TPEN: N,N,N,N-tetrakis(2-pyridinylmethyl)-1,2-ethanediamine; Vc: volume of correlation; WT: wild-type.

Biological importance of arginine: A comprehensive review of the roles in structure, disorder, and functionality of peptides and proteins

Arginine shows Jekyll and Hyde behavior in several respects. It participates in protein folding via ionic and H-bonds and cation-pi interactions; the charge and hydrophobicity of its side chain make it a disorder-promoting amino acid. Its methylation in histones; RNA binding proteins; chaperones regulates several cellular processes. The arginine-centric modifications are important in oncogenesis and as biomarkers in several cardiovascular diseases. The cross-links involving arginine in collagen and cornea are involved in pathogenesis of tissues but have also been useful in tissue engineering and wound-dressing materials. Arginine is a part of active site of several enzymes such as GTPases, peroxidases, and sulfotransferases. Its metabolic importance is obvious as it is involved in production of urea, NO, ornithine and citrulline. It can form unusual functional structures such as molecular tweezers in vitro and sprockets which engage DNA chains as part of histones in vivo. It has been used in design of cell-penetrating peptides as drugs. Arginine has been used as an excipient in both solid and injectable drug formulations; its role in suppressing opalescence due to liquid-liquid phase separation is particularly very promising. It has been known as a suppressor of protein aggregation during protein refolding. It has proved its usefulness in protein bioseparation processes like ion-exchange, hydrophobic and affinity chromatographies. Arginine is an amino acid, whose importance in biological sciences and biotechnology continues to grow in diverse ways.

Helicity of a tardigrade disordered protein contributes to its protective function during desiccation

To survive extreme drying (anhydrobiosis), many organisms, spanning every kingdom of life, accumulate intrinsically disordered proteins (IDPs). For decades, the ability of anhydrobiosis-related IDPs to form transient amphipathic helices has been suggested to be important for promoting desiccation tolerance. However, evidence empirically supporting the necessity and/or sufficiency of helicity in mediating anhydrobiosis is lacking. Here, we demonstrate that the linker region of CAHS D, a desiccation-related IDP from the tardigrade Hypsibius exemplaris, that contains significant helical structure, is the protective portion of this protein. Perturbing the sequence composition and grammar of the linker region of CAHS D, through the insertion of helix-breaking prolines, modulating the identity of charged residues, or replacement of hydrophobic amino acids with serine or glycine residues results in variants with different degrees of helical structure. Importantly, correlation of protective capacity and helical content in variants generated through different helix perturbing modalities does not show as strong a trend, suggesting that while helicity is important, it is not the only property that makes a protein protective during desiccation. These results provide direct evidence for the decades-old theory that helicity of desiccation-related IDPs is linked to their anhydrobiotic capacity.

HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins

Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two distinct groups, those trained on binding annotations extracted from structured protein-DNA complexes (structure-trained) vs. intrinsically disordered proteins (disorder-trained). We complete the first empirical analysis of predictive performance across the structure- and disorder-annotated proteins for a representative collection of ten predictors. Majority of the structure-trained tools perform well on the structure-annotated proteins while doing relatively poorly on the disorder-annotated proteins, and vice versa. Several methods make accurate predictions for the structure-annotated proteins or the disorder-annotated proteins, but none performs highly accurately for both annotation types. Moreover, most predictors make excessive cross-predictions for the disorder-annotated proteins, where residues that interact with non-DNA ligand types are predicted as DBRs. Motivated by these results, we design, validate and deploy an innovative meta-model, hybridDBRpred, that uses deep transformer network to combine predictions generated by three best current predictors. HybridDBRpred provides accurate predictions and low levels of cross-predictions across the two annotation types, and is statistically more accurate than each of the ten tools and baseline meta-predictors that rely on averaging and logistic regression. We deploy hybridDBRpred as a convenient web server at http://biomine.cs.vcu.edu/servers/hybridDBRpred/ and provide the corresponding source code at https://github.com/jianzhang-xynu/hybridDBRpred.

Fine structures of intrinsically disordered proteins

We report simulation studies of 33 single intrinsically disordered proteins (IDPs) using coarse-grained bead-spring models where interactions among different amino acids are introduced through a hydropathy matrix and additional screened Coulomb interaction for the charged amino acid beads. Our simulation studies of two different hydropathy scales (HPS1, HPS2) [Dignon et al., PLoS Comput. Biol. 14, e1005941 (2018); Tesei et al. Proc. Natl. Acad. Sci. U. S. A. 118, e2111696118 (2021)] and the comparison with the existing experimental data indicate an optimal interaction parameter ϵ = 0.1 and 0.2 kcal/mol for the HPS1 and HPS2 hydropathy scales. We use these best-fit parameters to investigate both the universal aspects as well as the fine structures of the individual IDPs by introducing additional characteristics. (i) First, we investigate the polymer-specific scaling relations of the IDPs in comparison to the universal scaling relations [Bair et al., J. Chem. Phys. 158, 204902 (2023)] for the homopolymers. By studying the scaled end-to-end distances ⟨RN2⟩/(2Lℓp) and the scaled transverse fluctuations l̃⊥2=⟨l⊥2⟩/L, we demonstrate that IDPs are broadly characterized with a Flory exponent of ν ≃ 0.56 with the conclusion that conformations of the IDPs interpolate between Gaussian and self-avoiding random walk chains. Then, we introduce (ii) Wilson charge index (W) that captures the essential features of charge interactions and distribution in the sequence space and (iii) a skewness index (S) that captures the finer shape variation of the gyration radii distributions as a function of the net charge per residue and charge asymmetry parameter. Finally, our study of the (iv) variation of ⟨Rg⟩ as a function of salt concentration provides another important metric to bring out finer characteristics of the IDPs, which may carry relevant information for the origin of life.

Engineered aptamers for molecular imaging

Molecular imaging, including quantification and molecular interaction studies, plays a crucial role in visualizing and analysing molecular events occurring within cells or organisms, thus facilitating the understanding of biological processes. Moreover, molecular imaging offers promising applications for early disease diagnosis and therapeutic evaluation. Aptamers are oligonucleotides that can recognize targets with a high affinity and specificity by folding themselves into various three-dimensional structures, thus serving as ideal molecular recognition elements in molecular imaging. This review summarizes the commonly employed aptamers in molecular imaging and outlines the prevalent design approaches for their applications. Furthermore, it highlights the successful application of aptamers to a wide range of targets and imaging modalities. Finally, the review concludes with a forward-looking perspective on future advancements in aptamer-based molecular imaging.

Modulating hierarchical self-assembly in thermoresponsive intrinsically disordered proteins through high-temperature incubation time

The cornerstone of structural biology is the unique relationship between protein sequence and the 3D structure at equilibrium. Although intrinsically disordered proteins (IDPs) do not fold into a specific 3D structure, breaking this paradigm, some IDPs exhibit large-scale organization, such as liquid-liquid phase separation. In such cases, the structural plasticity has the potential to form numerous self-assembled structures out of thermal equilibrium. Here, we report that high-temperature incubation time is a defining parameter for micro and nanoscale self-assembly of resilin-like IDPs. Interestingly, high-resolution scanning electron microscopy micrographs reveal that an extended incubation time leads to the formation of micron-size rods and ellipsoids that depend on the amino acid sequence. More surprisingly, a prolonged incubation time also induces amino acid composition-dependent formation of short-range nanoscale order, such as periodic lamellar nanostructures. We, therefore, suggest that regulating the period of high-temperature incubation, in the one-phase regime, can serve as a unique method of controlling the hierarchical self-assembly mechanism of structurally disordered proteins.

Heterochromatin organization and phase separation

The eukaryotic nucleus displays a variety of membraneless compartments with distinct biomolecular composition and specific cellular activities. Emerging evidence indicates that protein-based liquid-liquid phase separation (LLPS) plays an essential role in the formation and dynamic regulation of heterochromatin compartmentalization. This feature is especially conspicuous at the pericentric heterochromatin domains. In this review, we will describe our understanding of heterochromatin organization and LLPS. In addition, we will highlight the increasing importance of multivalent weak homo- and heteromolecular interactions in LLPS-mediated heterochromatin compartmentalization in the complex environment inside living cells.

RNA-Binding Proteins: A Role in Neurotoxicity?

Despite sustained efforts to treat neurodegenerative diseases, little is known at the molecular level to understand and generate novel therapeutic approaches for these malignancies. Therefore, it is not surprising that neurogenerative diseases are among the leading causes of death in the aged population. Neurons require sophisticated cellular mechanisms to maintain proper protein homeostasis. These cells are generally sensitive to loss of gene expression control at the post-transcriptional level. Post-translational control responds to signals that can arise from intracellular processes or environmental factors that can be regulated through RNA-binding proteins. These proteins recognize RNA through one or more RNA-binding domains and form ribonucleoproteins that are critically involved in the regulation of post-transcriptional processes from splicing to the regulation of association of the translation machinery allowing a relatively rapid and precise modulation of the transcriptome. Neurotoxicity is the result of the biological, chemical, or physical interaction of agents with an adverse effect on the structure and function of the central nervous system. The disruption of the proper levels or function of RBPs in neurons and glial cells triggers neurotoxic events that are linked to neurodegenerative diseases such as spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS), fragile X syndrome (FXS), and frontotemporal dementia (FTD) among many others. The connection between RBPs and neurodegenerative diseases opens a new landscape for potentially novel therapeutic targets for the intervention of these neurodegenerative pathologies. In this contribution, a summary of the recent findings of the molecular mechanisms involved in the plausible role of RBPs in RNA processing in neurodegenerative disease is discussed.

Functional unfoldomics: Roles of intrinsic disorder in protein (multi)functionality

Intrinsically disordered proteins (IDPs), which are functional proteins without stable tertiary structure, and hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) constitute prominent parts of all proteomes collectively known as unfoldomes. IDPs/IDRs exist as highly dynamic structural ensembles of rapidly interconverting conformations and are characterized by the exceptional structural heterogeneity, where their different parts are (dis)ordered to different degree, and their overall structure represents a complex mosaic of foldons, inducible foldons, inducible morphing foldons, non-foldons, semifoldons, and even unfoldons. Despite their lack of unique 3D structures, IDPs/IDRs play crucial roles in the control of various biological processes and the regulation of different cellular pathways and are commonly involved in recognition and signaling, indicating that the disorder-based functional repertoire is complementary to the functions of ordered proteins. Furthermore, IDPs/IDRs are frequently multifunctional, and this multifunctionality is defined by their structural flexibility and heterogeneity. Intrinsic disorder phenomenon is at the roots of the structure-function continuum model, where the structure continuum is defined by the presence of differently (dis)ordered regions, and the function continuum arises from the ability of all these differently (dis)ordered parts to have different functions. In their everyday life, IDPs/IDRs utilize a broad spectrum of interaction mechanisms thereby acting as interaction specialists. They are crucial for the biogenesis of numerous proteinaceous membrane-less organelles driven by the liquid-liquid phase separation. This review introduces functional unfoldomics by representing some aspects of the intrinsic disorder-based functionality.

Charge Distribution Patterns of IA3 Impact Conformational Expansion and Hydration Diffusivity of the Disordered Ensemble

IA3 is a 68 amino acid natural peptide/protein inhibitor of yeast aspartic proteinase A (YPRA) that is intrinsically disordered in solution with induced N-terminal helicity when in the protein complex with YPRA. Based on the intrinsically disordered protein (IDP) parameters of fractional net charge (FNC), net charge density per residue (NCPR), and charge patterning (κ), the two domains of IA3 are defined to occupy different domains within conformationally based subclasses of IDPs, thus making IA3 a bimodal domain IDP. Site-directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy and low-field Overhauser dynamic nuclear polarization (ODNP) spectroscopy results show that these two domains possess different degrees of compaction and hydration diffusivity behavior. This work suggests that SDSL EPR line shapes, analyzed in terms of their local tumbling volume (VL), provide insights into the compaction of the unstructured IDP ensemble in solution and that protein sequence and net charge distribution patterns within a conformational subclass can impact bound water hydration dynamics, thus possibly offering an alternative thermodynamic property that can encode conformational binding and behavior of IDPs and liquid-liquid phase separations.

Structure of Single-Chain Nanoparticles under Crowding Conditions: A Random Phase Approximation Approach

The conformation of poly(methyl methacrylate) (PMMA)-based single-chain nanoparticles (SCNPs) and their corresponding linear precursors in the presence of deuterated linear PMMA in deuterated dimethylformamide (DMF) solutions has been studied by small-angle neutron scattering (SANS). The SANS profiles were analyzed in terms of a three-component random phase approximation (RPA) model. The RPA approach described well the scattering profiles in dilute and crowded solutions. Considering all the contributions of the RPA leads to an accurate estimation of the single chain form factor parameters and the Flory-Huggins interaction parameter between PMMA and DMF. The value of the latter in the dilute regime indicates that the precursors and the SCNPs are in good solvent conditions, while in crowding conditions, the polymer becomes less soluble.

Identification of potential molecular mimicry in pathogen-host interactions

Pathogens have evolved sophisticated strategies to manipulate host signaling pathways, including the phenomenon of molecular mimicry, where pathogen-derived biomolecules imitate host biomolecules. In this study, we resurrected, updated, and optimized a sequence-based bioinformatics pipeline to identify potential molecular mimicry candidates between humans and 32 pathogenic species whose proteomes' 3D structure predictions were available at the start of this study. We observed considerable variation in the number of mimicry candidates across pathogenic species, with pathogenic bacteria exhibiting fewer candidates compared to fungi and protozoans. Further analysis revealed that the candidate mimicry regions were enriched in solvent-accessible regions, highlighting their potential functional relevance. We identified a total of 1,878 mimicked regions in 1,439 human proteins, and clustering analysis indicated diverse target proteins across pathogen species. The human proteins containing mimicked regions revealed significant associations between these proteins and various biological processes, with an emphasis on host extracellular matrix organization and cytoskeletal processes. However, immune-related proteins were underrepresented as targets of mimicry. Our findings provide insights into the broad range of host-pathogen interactions mediated by molecular mimicry and highlight potential targets for further investigation. This comprehensive analysis contributes to our understanding of the complex mechanisms employed by pathogens to subvert host defenses and we provide a resource to assist researchers in the development of novel therapeutic strategies.

CoMemMoRFPred: Sequence-based Prediction of MemMoRFs by Combining Predictors of Intrinsic Disorder, MoRFs and Disordered Lipid-binding Regions

Molecular recognition features (MoRFs) are a commonly occurring type of intrinsically disordered regions (IDRs) that undergo disorder-to-order transition upon binding to partner molecules. We focus on recently characterized and functionally important membrane-binding MoRFs (MemMoRFs). Motivated by the lack of computational tools that predict MemMoRFs, we use a dataset of experimentally annotated MemMoRFs to conceptualize, design, evaluate and release an accurate sequence-based predictor. We rely on state-of-the-art tools that predict residues that possess key characteristics of MemMoRFs, such as intrinsic disorder, disorder-to-order transition and lipid-binding. We identify and combine results from three tools that include flDPnn for the disorder prediction, DisoLipPred for the prediction of disordered lipid-binding regions, and MoRFCHiBiLight for the prediction of disorder-to-order transitioning protein binding regions. Our empirical analysis demonstrates that combining results produced by these three methods generates accurate predictions of MemMoRFs. We also show that use of a smoothing operator produces predictions that closely mimic the number and sizes of the native MemMoRF regions. The resulting CoMemMoRFPred method is available as an easy-to-use webserver at http://biomine.cs.vcu.edu/servers/CoMemMoRFPred. This tool will aid future studies of MemMoRFs in the context of exploring their abundance, cellular functions, and roles in pathologic phenomena.

IDP-LM: Prediction of protein intrinsic disorder and disorder functions based on language models

Intrinsically disordered proteins (IDPs) and regions (IDRs) are a class of functionally important proteins and regions that lack stable three-dimensional structures under the native physiologic conditions. They participate in critical biological processes and thus are associated with the pathogenesis of many severe human diseases. Identifying the IDPs/IDRs and their functions will be helpful for a comprehensive understanding of protein structures and functions, and inform studies of rational drug design. Over the past decades, the exponential growth in the number of proteins with sequence information has deepened the gap between uncharacterized and annotated disordered sequences. Protein language models have recently demonstrated their powerful abilities to capture complex structural and functional information from the enormous quantity of unlabelled protein sequences, providing opportunities to apply protein language models to uncover the intrinsic disorders and their biological properties from the amino acid sequences. In this study, we proposed a computational predictor called IDP-LM for predicting intrinsic disorder and disorder functions by leveraging the pre-trained protein language models. IDP-LM takes the embeddings extracted from three pre-trained protein language models as the exclusive inputs, including ProtBERT, ProtT5 and a disorder specific language model (IDP-BERT). The ablation analysis shown that the IDP-BERT provided fine-grained feature representations of disorder, and the combination of three language models is the key to the performance improvement of IDP-LM. The evaluation results on independent test datasets demonstrated that the IDP-LM provided high-quality prediction results for intrinsic disorder and four common disordered functions.