Introducing protein intrinsic disorder

Current research status on the structure, physicochemical properties, bioactivities, and mechanism of soybean-derived bioactive peptide lunasin

Since the 21st century, chronic diseases have become a worldwide health problem due to their high morbidity and mortality. Soybean bioactive substances, especially soybean peptides, are considered to have health benefits beyond nutritional effects. As the most studied peptide in soybean, lunasin has been proven to exert beneficial effects on various chronic disorders. This review summarizes the content of lunasin in soybeans, soy derived foods, and other crops, as well as its structural characteristics and bioavailability. Moreover, we focused on the relationship between the physicochemical characteristics and structural composition of lunasin, and its significance for the bioactivities of lunasin. Ultimately, the therapeutic effects of lunasin on cancer, oxidative stress, inflammation, immune response, and hyperlipidemia were described, as well as the molecular mechanisms involved in these impacts. In conclusion, lunasin is a promising multifunctional bioactive peptide, yet further research is required to optimize and expedite its application in the food industry.

The C-terminal end of PLIN1 displays structural disorder

Lipid droplets (LDs) serve as crucial organelles for lipid storage and metabolism, with their proteome significantly influencing their regulation. Perilipins (PLINs), in particular PLIN1, play vital role in LD metabolism by orchestrating lipolysis. The C-terminal end of PLIN1 regulates lipolysis through interactions with coactivators such as the CGI-58 protein. Despite its importance, the structural characterization of this domain remains limited. Here, we present a comprehensive bioinformatic and biophysical analysis of the C-terminal end of mouse PLIN1 (mPLIN1C). Our findings suggest that mPLIN1C behaves as an intrinsically disordered region (IDR), exhibiting context-dependent properties of the coil-like or pre-molten globule type. Structural analysis reveals a predominance of disordered secondary structure, with circular dichroism spectroscopy indicating a high coil content. Interaction studies with SDS micelles suggest a conformational transition towards a pre-molten globule state. Furthermore, the analysis of molecular recognition features (MoRFs) identifies the EPESE sequence spanning residues 413-417 as a potential binding site for partner molecules. Overall, our findings shed light on the structural properties and potential interaction mechanisms of mPLIN1C, providing insight into its functional role in LD metabolism.

Decoding Order and Disorder in Proteins by NMR Spectroscopy

Proteins often have a complex architecture, consisting of both globular ordered domains and intrinsically disordered regions (IDRs). These multidomain proteins pose challenges for traditional structural biology techniques. One major difficulty arises from the dynamic and flexible nature of IDRs, which lack a stable three-dimensional structure. Indeed, this feature further complicates the application of traditional structural biology techniques. Characterizing these systems is typically simplified by isolating individual domains, which can provide valuable insights into the structure and function of specific regions. However, this approach overlooks the interactions and regulatory mechanisms that occur between domains. To capture the full functional and structural complexity of multidomain proteins, it is crucial to study larger constructs. In this study, we focused on the CREB binding protein (CBP), a pivotal protein involved in numerous cellular processes. CBP is characterized by its modular structure, featuring alternating globular domains and IDRs. We specifically examined the TAZ4 construct, encompassing the TAZ2 globular domain and the ID4 flexible linker region. To characterize this multidomain system, we designed NMR experiments that take advantage of the dynamic differences between the two domains to obtain 2D and 3D spectra enabling the selection of the signals based on their nuclear relaxation properties. These experiments allowed the sequence-specific assignment of the TAZ4 construct to be extended revealing a crosstalk between the disordered region and the globular domain.

Small Molecules Targeting the Structural Dynamics of AR-V7 Partially Disordered Proteins Using Deep Ensemble Docking

The extensive conformational dynamics of partially disordered proteins hinders the efficiency of traditional in-silico structure-based drug discovery approaches due to the challenge of screening large chemical spaces of compounds, albeit with an excessive number of transient binding sites, quickly making this problem intractable. In this study, using the monomer of the AR-V7 transcription factor splicing variant related to prostate cancer as a test case, we present a deep ensemble docking pipeline that accelerates the screening of small molecule binders targeting partially disordered proteins at functional regions. By swiftly identifying the conformational ensemble of AR-V7 and reducing the dimension of binding sites by a factor of 90, we identify functionally relevant binding sites along the AR-V7 structural ensemble at phase separation-prone regions that have been experimentally shown to contribute to enhanced transcription activity and the onset of tumor growth. Following this, we combine physics-based molecular docking and multiobjective classification machine learning models to speed up the screening for binders in a larger chemical space able to target these functional multiple binding sites of AR-V7. This step increases the multibinding site hit rate of small molecules by a factor of 17 compared to naive molecular docking. Finally, assessing in atomistic molecular dynamics the effect of a selected binder on AR-V7 dynamics, we find that in the presence of the ChEMBL22003 compound, AR-V7 exhibits less conformational entropy, smaller solvent exposure of phase separation-prone regions, and higher solvent exposure of other protein regions, promoting this compound as a potential AR-V7 phase separation modulator.

Accurate and Rapid Prediction of Protein pKa: Protein Language Models Reveal the Sequence-pKa Relationship

Protein pKa prediction is a key challenge in computational biology. In this study, we present pKALM, a novel deep learning-based method for high-throughput protein pKa prediction. pKALM uses a protein language model (PLM) to capture the complex sequence-structure relationships of proteins. While traditionally considered a structure-based problem, our results show that a PLM pretrained on large-scale protein sequence databases can effectively learn this relationship and achieve state-of-the-art performance. pKALM accurately predicts the pKa values of six residues (Asp, Glu, His, Lys, Cys, and Tyr) and two termini with high precision and efficiency. It performs well at predicting both exposed and buried residues, which often deviate from standard pKa values measured in the solvent. We demonstrate a novel finding that predicted protein isoelectric points (pI) can be used to improve the accuracy of pKa prediction. High-throughput pKa prediction of the human proteome using pKALM achieves a speed of 4,965 pKa predictions per second, which is several orders of magnitude faster than existing state-of-the-art methods. The case studies illustrate the efficacy of pKALM in estimating pKa values and the constraints of the method. pKALM will thus be a valuable tool for researchers in the fields of biochemistry, biophysics, and drug design.

Evidence of α-Synuclein/Glucocerebrosidase Dual Targeting by Iminosugar Derivatives

Intrinsically disordered proteins (IDPs) are highly flexible molecules often linked to the onset of incurable diseases. Despite their great therapeutic potential, IDPs are often considered as undruggable because they lack defined binding pockets, which constitute the basis of drug discovery approaches. However, small molecules that interact with the intrinsically disordered state of α-synuclein, the protein linked to Parkinson's disease (PD), were recently identified and shown to act as chemical chaperones. Glucocerebrosidase (GCase) is an enzyme crucially involved in PD, since mutations that code for GCase are among the most frequent genetic risk factors for PD. Following the "dual-target" approach, stating that one carefully designed molecule can, in principle, interfere with more than one target, we identified a pharmacological chaperone for GCase that interacts with the intrinsically disordered monomeric form of α-synuclein. This result opens novel avenues to be explored in the search for molecules that act on dual targets, in particular, with challenging targets such as IDPs.

Navigating the unstructured by evaluating alphafold's efficacy in predicting missing residues and structural disorder in proteins

The study investigated regions with undefined structures, known as "missing" segments in X-ray crystallography and cryo-electron microscopy (Cryo-EM) data, by assessing their predicted structural confidence and disorder scores. Utilizing a comprehensive dataset from the Protein Data Bank (PDB), residues were categorized as "modeled", "hard missing" and "soft missing" based on their visibility in structural datasets. Key features were determined, including a confidence score predicted local distance difference test (pLDDT) from AlphaFold2, an advanced structural prediction tool, and a disorder score from IUPred, a traditional disorder prediction method. To enhance prediction performance for unstructured residues, we employed a Long Short-Term Memory (LSTM) model, integrating both scores with amino acid sequences. Notable patterns such as composition, region lengths and prediction scores were observed in unstructured residues and regions identified through structural experiments over our studied period. Our findings also indicate that "hard missing" residues often align with low confidence scores, whereas "soft missing" residues exhibit dynamic behavior that can complicate predictions. The incorporation of pLDDT, IUPred scores, and sequence data into the LSTM model has improved the differentiation between structured and unstructured residues, particularly for shorter unstructured regions. This research elucidates the relationship between established computational predictions and experimental structural data, enhancing our ability to target structurally significant areas for research and guiding experimental designs toward functionally relevant regions.

Conformationally adaptive therapeutic peptides for diseases caused by intrinsically disordered proteins (IDPs). New paradigm for drug discovery: Target the target, not the arrow

The traditional model of protein structure determined by the amino acid sequence is today seriously challenged by the fact that approximately half of the human proteome is made up of proteins that do not have a stable 3D structure, either partially or in totality. These proteins, called intrinsically disordered proteins (IDPs), are involved in numerous physiological functions and are associated with severe pathologies, e.g. Alzheimer, Parkinson, Creutzfeldt-Jakob, amyotrophic lateral sclerosis (ALS), and type 2 diabetes. Targeting these proteins is challenging for two reasons: i) we need to preserve their physiological functions, and ii) drug design by molecular docking is not possible due to the lack of reliable starting conditions. Faced with this challenge, the solutions proposed by artificial intelligence (AI) such as AlphaFold are clearly unsuitable. Instead, we suggest an innovative approach consisting of mimicking, in short synthetic peptides, the conformational flexibility of IDPs. These peptides, which we call adaptive peptides, are derived from the domains of IDPs that become structured after interacting with a ligand. Adaptive peptides are designed with the aim of selectively antagonizing the harmful effects of IDPs, without targeting them directly but through selected ligands, without affecting their physiological properties. This "target the target, not the arrow" strategy is promised to open a new route to drug discovery for currently undruggable proteins.

MIA40 circumvents the folding constraints imposed by TRIAP1 function

The MIA40 relay system mediates the import of small cysteine-rich proteins into the intermembrane mitochondrial space (IMS). MIA40 substrates are synthesized in the cytosol and assumed to be disordered in their reduced state in this compartment. As they cross the outer mitochondrial membrane, MIA40 promotes the oxidation of critical native disulfides to facilitate folding, trapping functional species in the IMS. Here, we study the redox-controled folding of TRIAP1, a small cysteine-rich protein with moonlighting function: regulating phospholipid trafficking between mitochondrial membranes in the IMS and preventing apoptosis in the cytosol. TRIAP1 dysregulation is connected to oncogenesis. Although TRIAP1 contains a canonical twin CX9C motif, its sequence characteristics and folding pathway deviate from typical MIA40 substrates. In its reduced state, TRIAP1 rapidly populates a hydrophobic collapsed, alpha-helical, and marginally stable molten globule. This intermediate biases oxidative folding towards a non-native Cys37-Cys47 kinetic trap, slowing the reaction. MIA40 accelerates TRIAP1 folding rate by 30-fold, bypassing the formation of this folding trap. MIA40 drives the oxidation of the inner disulfide bond Cys18-Cys37, and subsequently, it can catalyze the formation of the outer disulfide bond Cys8-Cys47 to attain the native two-disulfide-bridged structure. We demonstrate that, unlike most MIA40 substrates, TRIAP1's folding pathway is strongly constrained by the structural requirements for its function in phospholipid traffic at the IMS. The obligatory population of a reduced, alpha-helical, metastable molten globule in the cytoplasm may explain TRIAP1's connection to the p53-dependent cell survival pathway, constituting a remarkable example of a functional molten globule state.

Molecular intricacies of intrinsically disordered proteins and drought stress in plants

Intrinsically Disordered Proteins (IDPs) and Intrinsically Disordered Regions (IDRs) are renowned for their dynamic structural characteristics and conformational adaptability, allowing them to assume diverse conformations in response to prevailing environmental conditions. This inherent flexibility facilitates their interactions with molecular targets, enabling them to engage in numerous cellular processes without any excessive energy consumption. This adaptability is instrumental in shaping cellular complexity and enhancing adaptability. Notably, most investigations into IDPs/IDRs have concentrated on non-plant organisms, while this comprehensive review explores their multifaceted functions with a perspective of plant resilience to drought stress. Furthermore, the impact of IDPs on plant stress is discussed, highlighting their involvement in diverse biological processes extending beyond mere stress adaptation. This review incorporates a broad spectrum of methodological approaches, ranging from computational tools to experimental techniques, employed for the systematic study of IDPs. We also discussed limitations, challenges, and future directions in this dynamic and evolving field, aiming to provide insights into the unexplored facets of IDPs/IDRs in the intricate landscape of plant responses to drought stress.

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.

ATP promotes protein coacervation through conformational compaction

Adenosine triphosphate (ATP) has been recognized as a hydrotrope in the phase separation process of intrinsically disordered proteins (IDPs). Surprisingly, when using the disordered Arg-Gly/Arg-Gly-Gly (RG/RGG) rich motif from the HNRNPG protein as a model system, we discover a biphasic relationship between the ATP concentration and IDP phase separation. We show that, at a relatively low ATP concentration, ATP dynamically interacts with the IDP, which neutralizes protein surface charges, promotes intermolecular interactions, and consequently promotes phase separation. We further demonstrate that ATP induces a compact conformation of the IDP, accounting for the reduced solvent exchange rate and lower compression ratio during phase separation. As ATP concentration increases, its hydrotropic properties emerge, leading to the dissolution of the phase-separated droplets. Our finding uncovers a complex mechanism by which ATP molecules modulate the structure, interaction, and phase separation of IDPs and accounts for the distinct phase separation behaviors of the charge-rich RGG motif and other low-complexity IDPs.

Ensemble docking for intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are implicated in many human diseases and are increasingly being pursued as drug targets. Conventional structure-based drug design methods that rely on well-defined binding sites are however, largely unsuitable for IDPs. Here, we present computationally efficient ensemble docking approaches to predict the relative affinities of small molecules to IDPs and characterize their dynamic, heterogenous binding mechanisms at atomic resolution. We demonstrate that these ensemble docking protocols accurately predict the relative binding affinities of small molecule α-synuclein ligands measured by NMR spectroscopy and generate conformational ensembles of ligand binding modes in remarkable agreement with experimentally validated long-timescale molecular dynamics simulations. Our results display the potential of ensemble docking approaches for predicting small molecule binding to IDPs and suggest that these methods may be valuable tools for IDP drug discovery campaigns.

The Pseudoenzyme β-Amylase9 From Arabidopsis Activates α-Amylase3: A Possible Mechanism to Promote Stress-Induced Starch Degradation

Starch accumulation in plants provides carbon for nighttime use, for regrowth after periods of dormancy, and for times of stress. Both ɑ- and β-amylases (AMYs and BAMs, respectively) catalyze starch hydrolysis, but their functional roles are unclear. Moreover, the presence of catalytically inactive amylases that show starch excess phenotypes when deleted presents questions on how starch degradation is regulated. Plants lacking one of these catalytically inactive β-amylases, BAM9, have enhanced starch accumulation when combined with mutations in BAM1 and BAM3, the primary starch degrading BAMs in response to stress and at night, respectively. BAM9 has been reported to be transcriptionally induced by stress although the mechanism for BAM9 function is unclear. From yeast two-hybrid experiments, we identified the plastid-localized AMY3 as a potential interaction partner for BAM9. We found that BAM9 interacted with AMY3 in vitro and that BAM9 enhances AMY3 activity about three-fold. Modeling of the AMY3-BAM9 complex predicted a previously undescribed alpha-alpha hairpin in AMY3 that could serve as a potential interaction site. Additionally, AMY3 lacking the alpha-alpha hairpin is unaffected by BAM9. Structural analysis of AMY3 showed that it can form a homodimer in solution and that BAM9 appears to replace one of the AMY3 monomers to form a heterodimer. The presence of both BAM9 and AMY3 in many vascular plant lineages, along with model-based evidence that they heterodimerize, suggests that the interaction is conserved. Collectively these data suggest that BAM9 is a pseudoamylase that activates AMY3 in response to cellular stress, possibly facilitating stress recovery.

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.

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.

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.

Evaluation of predictions of disordered binding regions in the CAID2 experiment

A large portion of the Intrinsically Disordered Regions (IDRs) in protein sequences interact with proteins, nucleic acids, and other types of ligands. Correspondingly, dozens of sequence-based predictors of binding IDRs were developed. A recently completed second community-based Critical Assessments of protein Intrinsic Disorder prediction (CAID2) evaluated 32 predictors of binding IDRs. However, CAID2 considered a rather narrow scenario by testing on 78 proteins with binding IDRs and not differentiating between different ligands, in spite that virtually all predictors target IDRs that interact with specific types of ligands. In that scenario, several intrinsic disorder predictors predict binding IDRs with accuracy equivalent to the best predictors of binding IDRs since large majority of IDRs in the 78 test proteins are binding. We substantially extended the CAID2's evaluation by using the entire CAID2 dataset of 348 proteins and considering several arguably more practical scenarios. We assessed whether predictors accurately differentiate binding IDRs from other types of IDRs and how they perform when predicting IDRs that interact with different ligand types. We found that intrinsic disorder predictors cannot accurately identify binding IDRs among other disordered regions, majority of the predictors of binding IDRs are ligand type agnostic (i.e., they cross predict binding in IDRs that interact with ligands that they do not cover), and only a handful of predictors of binding IDRs perform relatively well and generate reasonably low amounts of cross predictions. We also suggest a number of future research directions that would move this active field of research forward.

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.

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.

Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences

Computational prediction of nucleic acid-binding residues in protein sequences is an active field of research, with over 80 methods that were released in the past 2 decades. We identify and discuss 87 sequence-based predictors that include dozens of recently published methods that are surveyed for the first time. We overview historical progress and examine multiple practical issues that include availability and impact of predictors, key features of their predictive models, and important aspects related to their training and assessment. We observe that the past decade has brought increased use of deep neural networks and protein language models, which contributed to substantial gains in the predictive performance. We also highlight advancements in vital and challenging issues that include cross-predictions between deoxyribonucleic acid (DNA)-binding and ribonucleic acid (RNA)-binding residues and targeting the two distinct sources of binding annotations, structure-based versus intrinsic disorder-based. The methods trained on the structure-annotated interactions tend to perform poorly on the disorder-annotated binding and vice versa, with only a few methods that target and perform well across both annotation types. The cross-predictions are a significant problem, with some predictors of DNA-binding or RNA-binding residues indiscriminately predicting interactions with both nucleic acid types. Moreover, we show that methods with web servers are cited substantially more than tools without implementation or with no longer working implementations, motivating the development and long-term maintenance of the web servers. We close by discussing future research directions that aim to drive further progress in this area.

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.

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.

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.

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.

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.

Targeting MYC with protein drugs

After cardiovascular disease, cancer is our biggest killer. The "war on cancer" officially launched in 1971; despite decades of research and development, our arsenal of drugs against cancer still comprises mainly small molecules. Protein drugs, however, are poised to become the foundation for next-generation drugs that target MYC, a proto-oncogene that encodes the MYC transcription factor involved in the majority of human cancers. Such protein drugs work inside the cell in the nucleus, where they interact directly with the genome or can partner with MYC to blunt its detrimental activities. No small-molecule drug has been successful against MYC, but protein drug Omomyc has successfully inhibited solid tumors in human trials. Although MYC is a key regulator of normal cellular processes, we need to develop new tactics to contain MYC when it goes rogue.

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/.