AIUPred: combining energy estimation with deep learning for the enhanced prediction of protein disorder.

Intrinsically disordered proteins and protein regions (IDPs/IDRs) carry out important biological functions without relying on a single well-defined conformation. As these proteins are a challenge to study experimentally, computational methods play important roles in their characterization. One of the commonly used tools is the IUPred web server which provides prediction of disordered regions and their binding sites. IUPred is rooted in a simple biophysical model and uses a limited number of parameters largely derived on globular protein structures only. This enabled an incredibly fast and robust prediction method, however, its limitations have also become apparent in light of recent breakthrough methods using deep learning techniques. Here, we present AIUPred, a novel version of IUPred which incorporates deep learning techniques into the energy estimation framework. It achieves improved performance while keeping the robustness of the original method. Based on the evaluation of recent benchmark datasets, AIUPred scored amongst the top three single sequence based methods. With a new web server we offer fast and reliable visual analysis for users as well as options to analyze whole genomes in mere seconds with the downloadable package. AIUPred is available at https://aiupred.elte.hu.

The Origin of Discrepancies between Predictions and Annotations in Intrinsically Disordered Proteins.

Disorder prediction methods that can discriminate between ordered and disordered regions have contributed fundamentally to our understanding of the properties and prevalence of intrinsically disordered proteins (IDPs) in proteomes as well as their functional roles. However, a recent large-scale assessment of the performance of these methods indicated that there is still room for further improvements, necessitating novel approaches to understand the strengths and weaknesses of individual methods. In this study, we compared two methods, IUPred and disorder prediction, based on the pLDDT scores derived from AlphaFold2 (AF2) models. We evaluated these methods using a dataset from the DisProt database, consisting of experimentally characterized disordered regions and subsets associated with diverse experimental methods and functions. IUPred and AF2 provided consistent predictions in 79% of cases for long disordered regions; however, for 15% of these cases, they both suggested order in disagreement with annotations. These discrepancies arose primarily due to weak experimental support, the presence of intermediate states, or context-dependent behavior, such as binding-induced transitions. Furthermore, AF2 tended to predict helical regions with high pLDDT scores within disordered segments, while IUPred had limitations in identifying linker regions. These results provide valuable insights into the inherent limitations and potential biases of disorder prediction methods.

Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins.

Intrinsic disorder is instrumental for a wide range of protein functions, and its analysis, using computational predictions from primary structures, complements secondary and tertiary structure-based approaches. In this Tutorial, we provide an overview and comparison of 23 publicly available computational tools with complementary parameters useful for intrinsic disorder prediction, partly relying on results from the Critical Assessment of protein Intrinsic Disorder prediction experiment. We consider factors such as accuracy, runtime, availability and the need for functional insights. The selected tools are available as web servers and downloadable programs, offer state-of-the-art predictions and can be used in a high-throughput manner. We provide examples and instructions for the selected tools to illustrate practical aspects related to the submission, collection and interpretation of predictions, as well as the timing and their limitations. We highlight two predictors for intrinsically disordered proteins, flDPnn as accurate and fast and IUPred as very fast and moderately accurate, while suggesting ANCHOR2 and MoRFchibi as two of the best-performing predictors for intrinsically disordered region binding. We link these tools to additional resources, including databases of predictions and web servers that integrate multiple predictive methods. Altogether, this Tutorial provides a hands-on guide to comparatively evaluating multiple predictors, submitting and collecting their own predictions, and reading and interpreting results. It is suitable for experimentalists and computational biologists interested in accurately and conveniently identifying intrinsic disorder, facilitating the functional characterization of the rapidly growing collections of protein sequences.

DisCanVis: Visualizing integrated structural and functional annotations to better understand the effect of cancer mutations located within disordered proteins.

Intrinsically disordered proteins (IDPs) play important roles in a wide range of biological processes and have been associated with various diseases, including cancer. In the last few years, cancer genome projects have systematically collected genetic variations underlying multiple cancer types. In parallel, the number and different types of disordered proteins characterized by experimental methods have also significantly increased. Nevertheless, the role of IDPs in various types of cancer is still not well understood. In this work, we present DisCanVis, a novel visualization tool for cancer mutations with a special focus on IDPs. In order to aid the interpretation of observed mutations, genome level information is combined with information about the structural and functional properties of proteins. The web server enables users to inspect individual proteins, collect examples with existing annotations of protein disorder and associated function or to discover currently uncharacterized examples with likely disease relevance. Through a REST API interface and precompiled tables the analysis can be extended to a group of proteins.

The interaction between LC8 and LCA5 reveals a novel oligomerization function of LC8 in the ciliary-centrosome system.

Dynein light chain LC8 is a small dimeric hub protein that recognizes its partners through short linear motifs and is commonly assumed to drive their dimerization. It has more than 100 known binding partners involved in a wide range of cellular processes. Recent large-scale interaction studies suggested that LC8 could also play a role in the ciliary/centrosome system. However, the cellular function of LC8 in this system remains elusive. In this work, we characterized the interaction of LC8 with the centrosomal protein lebercilin (LCA5), which is associated with a specific form of ciliopathy. We showed that LCA5 binds LC8 through two linear motifs. In contrast to the commonly accepted model, LCA5 forms dimers through extensive coiled coil formation in a LC8-independent manner. However, LC8 enhances the oligomerization ability of LCA5 that requires a finely balanced interplay of coiled coil segments and both binding motifs. Based on our results, we propose that LC8 acts as an oligomerization engine that is responsible for the higher order oligomer formation of LCA5. As LCA5 shares several common features with other centrosomal proteins, the presented LC8 driven oligomerization could be widespread among centrosomal proteins, highlighting an important novel cellular function of LC8.

DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation.

The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.

IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation.

Intrinsically disordered proteins and protein regions (IDPs/IDRs) exist without a single well-defined conformation. They carry out important biological functions with multifaceted roles which is also reflected in their evolutionary behavior. Computational methods play important roles in the characterization of IDRs. One of the commonly used disorder prediction methods is IUPred, which relies on an energy estimation approach. The IUPred web server takes an amino acid sequence or a Uniprot ID/accession as an input and predicts the tendency for each amino acid to be in a disordered region with an option to also predict context-dependent disordered regions. In this new iteration of IUPred, we added multiple novel features to enhance the prediction capabilities of the server. First, learning from the latest evaluation of disorder prediction methods we introduced multiple new smoothing functions to the prediction that decreases noise and increases the performance of the predictions. We constructed a dataset consisting of experimentally verified ordered/disordered regions with unambiguous annotations which were added to the prediction. We also introduced a novel tool that enables the exploration of the evolutionary conservation of protein disorder coupled to sequence conservation in model organisms. The web server is freely available to users and accessible at https://iupred3.elte.hu.

The MemMoRF database for recognizing disordered protein regions interacting with cellular membranes.

Protein and lipid membrane interactions play fundamental roles in a large number of cellular processes (e.g. signalling, vesicle trafficking, or viral invasion). A growing number of examples indicate that such interactions can also rely on intrinsically disordered protein regions (IDRs), which can form specific reversible interactions not only with proteins but also with lipids. We named IDRs involved in such membrane lipid-induced disorder-to-order transition as MemMoRFs, in an analogy to IDRs exhibiting disorder-to-order transition upon interaction with protein partners termed Molecular Recognition Features (MoRFs). Currently, both the experimental detection and computational characterization of MemMoRFs are challenging, and information about these regions are scattered in the literature. To facilitate the related investigations we generated a comprehensive database of experimentally validated MemMoRFs based on manual curation of literature and structural data. To characterize the dynamics of MemMoRFs, secondary structure propensity and flexibility calculated from nuclear magnetic resonance chemical shifts were incorporated into the database. These data were supplemented by inclusion of sentences from papers, functional data and disease-related information. The MemMoRF database can be accessed via a user-friendly interface at https://memmorf.hegelab.org, potentially providing a central resource for the characterization of disordered regions in transmembrane and membrane-associated proteins.

Evolutionary Study of Disorder in Protein Sequences.

Intrinsically disordered proteins (IDPs) contain regions lacking intrinsic globular structure (intrinsically disordered regions, IDRs). IDPs are present across the tree of life, with great variability of IDR type and frequency even between closely related taxa. To investigate the function of IDRs, we evaluated and compared the distribution of disorder content in 10,695 reference proteomes, confirming its high variability and finding certain correlation along the Euteleostomi (bony vertebrates) lineage to number of cell types. We used the comparison of orthologs to study the function of disorder related to increase in cell types, observing that multiple interacting subunits of protein complexes might gain IDRs in evolution, thus stressing the function of IDRs in modulating protein-protein interactions, particularly in the cell nucleus. Interestingly, the conservation of local compositional biases of IDPs follows residue-type specific patterns, with E- and K-rich regions being evolutionarily stable and Q- and A-rich regions being more dynamic. We provide a framework for targeted evolutionary studies of the emergence of IDRs. We believe that, given the large variability of IDR distributions in different species, studies using this evolutionary perspective are required.

Analyzing Protein Disorder with IUPred2A.

IUPred2A is a combined prediction tool designed to discover intrinsically disordered or conditionally disordered proteins and protein regions. Intrinsically disordered regions exist without a well-defined three-dimensional structure in isolation but carry out important biological functions. Over the years, various prediction methods have been developed to characterize disordered regions. The existence of disordered segments can also be dependent on different factors such as binding partners or environmental traits like pH or redox potential, and recognizing such regions represents additional computational challenges. In this article, we present detailed instructions on how to use IUPred2A, one of the most widely used tools for the prediction of disordered regions/proteins or conditionally disordered segments, and provide examples of how the predictions can be interpreted in different contexts. © 2020 The Authors. Basic Protocol 1: Analyzing disorder propensity with IUPred2A online Basic Protocol 2: Analyzing disordered binding regions using ANCHOR2 Support Protocol 1: Interpretation of the results Basic Protocol 3: Analyzing redox-sensitive disordered regions Support Protocol 2: Download options Support Protocol 3: REST API for programmatic purposes Basic Protocol 4: Using IUPred2A locally.

PhaSePro: the database of proteins driving liquid-liquid phase separation.

Membraneless organelles (MOs) are dynamic liquid condensates that host a variety of specific cellular processes, such as ribosome biogenesis or RNA degradation. MOs form through liquid-liquid phase separation (LLPS), a process that relies on multivalent weak interactions of the constituent proteins and other macromolecules. Since the first discoveries of certain proteins being able to drive LLPS, it emerged as a general mechanism for the effective organization of cellular space that is exploited in all kingdoms of life. While numerous experimental studies report novel cases, the computational identification of LLPS drivers is lagging behind, and many open questions remain about the sequence determinants, composition, regulation and biological relevance of the resulting condensates. Our limited ability to overcome these issues is largely due to the lack of a dedicated LLPS database. Therefore, here we introduce PhaSePro (https://phasepro.elte.hu), an openly accessible, comprehensive, manually curated database of experimentally validated LLPS driver proteins/protein regions. It not only provides a wealth of information on such systems, but improves the standardization of data by introducing novel LLPS-specific controlled vocabularies. PhaSePro can be accessed through an appealing, user-friendly interface and thus has definite potential to become the central resource in this dynamically developing field.

Large-Scale Analysis of Redox-Sensitive Conditionally Disordered Protein Regions Reveals Their Widespread Nature and Key Roles in High-Level Eukaryotic Processes.

Recently developed quantitative redox proteomic studies enable the direct identification of redox-sensing cysteine residues that regulate the functional behavior of target proteins in response to changing levels of reactive oxygen species. At the molecular level, redox regulation can directly modify the active sites of enzymes, although a growing number of examples indicate the importance of an additional underlying mechanism that involves conditionally disordered proteins. These proteins alter their functional behavior by undergoing a disorder-to-order transition in response to changing redox conditions. However, the extent to which this mechanism is used in various proteomes is currently unknown. Here, a recently developed sequence-based prediction tool incorporated into the IUPred2A web server is used to estimate redox-sensitive conditionally disordered regions at a large scale. It is shown that redox-sensitive conditional disorder is fairly widespread in various proteomes and that its presence strongly correlates with the expansion of specific domains in multicellular organisms that largely rely on extra stability provided by disulfide bonds or zinc ion binding. The analyses of yeast redox proteomes and human disease data further underlie the significance of this phenomenon in the regulation of a wide range of biological processes, as well as its biomedical importance.

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

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

Novel linear motif filtering protocol reveals the role of the LC8 dynein light chain in the Hippo pathway.

Protein-protein interactions (PPIs) formed between short linear motifs and globular domains play important roles in many regulatory and signaling processes but are highly underrepresented in current protein-protein interaction databases. These types of interactions are usually characterized by a specific binding motif that captures the key amino acids shared among the interaction partners. However, the computational proteome-level identification of interaction partners based on the known motif is hindered by the huge number of randomly occurring matches from which biologically relevant motif hits need to be extracted. In this work, we established a novel bioinformatic filtering protocol to efficiently explore interaction network of a hub protein. We introduced a novel measure that enabled the optimization of the elements and parameter settings of the pipeline which was built from multiple sequence-based prediction methods. In addition, data collected from PPI databases and evolutionary analyses were also incorporated to further increase the biological relevance of the identified motif hits. The approach was applied to the dynein light chain LC8, a ubiquitous eukaryotic hub protein that has been suggested to be involved in motor-related functions as well as promoting the dimerization of various proteins by recognizing linear motifs in its partners. From the list of putative binding motifs collected by our protocol, several novel peptides were experimentally verified to bind LC8. Altogether 71 potential new motif instances were identified. The expanded list of LC8 binding partners revealed the evolutionary plasticity of binding partners despite the highly conserved binding interface. In addition, it also highlighted a novel, conserved function of LC8 in the upstream regulation of the Hippo signaling pathway. Beyond the LC8 system, our work also provides general guidelines that can be applied to explore the interaction network of other linear motif binding proteins or protein domains.

Effects of the gout-causing Q141K polymorphism and a CFTR ΔF508 mimicking mutation on the processing and stability of the ABCG2 protein.

ABCG2 is an important multidrug transporter involved also in urate transport, thus its mutations can lead to the development of gout and may also alter general drug absorption, distribution and excretion. The frequent ABCG2 polymorphism, Q141K, is associated with an elevated risk of gout and has been controversially reported to reduce the plasma membrane expression and/or the transport function of the protein. In the present work we examined the stability and cellular processing of the Q141K ABCG2 variant, as well as that of the ΔF142 ABCG2, corresponding to the ΔF508 mutation in the CFTR (ABCC7) protein, causing cystic fibrosis. The processing and localization of full length ABCG2 variants were investigated in mammalian cells, followed by Western blotting and confocal microscopy, respectively. Folding and stability were examined by limited proteolysis of Sf9 insect cell membranes expressing these ABCG2 constructs. Stability of isolated nucleotide binding domains, expressed in and purified from bacteria, was studied by CD spectroscopy. We find that the Q141K variant has a mild processing defect which can be rescued by low temperature, a slightly reduced activity, and a mild folding defect, especially affecting the NBD. In contrast, the ΔF142 mutant has major processing and folding defects, and no ATPase function. We suggest that although these mutations are both localized within the NBD, based on molecular modeling their contribution to the ABCG2 structure and function is different, thus rescue strategies may be devised accordingly.

Clinical outcomes of patients with severe aortic stenosis at increased surgical risk according to treatment modality.

OBJECTIVES: The aim of this study was to assess the role of transcatheter aortic valve implantation (TAVI) compared with medical treatment (MT) and surgical aortic valve replacement (SAVR) in patients with severe aortic stenosis (AS) at increased surgical risk. BACKGROUND: Elderly patients with comorbidities are at considerable risk for SAVR. METHODS: Since July 2007, 442 patients with severe AS (age: 81.7 ± 6.0 years, mean logistic European System for Cardiac Operative Risk Evaluation: 22.3 ± 14.6%) underwent treatment allocation to MT (n = 78), SAVR (n = 107), or TAVI (n = 257) on the basis of a comprehensive evaluation protocol as part of a prospective registry. RESULTS: Baseline clinical characteristics were similar among patients allocated to MT and TAVI, whereas patients allocated to SAVR were younger (p < 0.001) and had a lower predicted peri-operative risk (p < 0.001). Unadjusted rates of all-cause mortality at 30 months were lower for SAVR (22.4%) and TAVI (22.6%) compared with MT (61.5%, p < 0.001). Adjusted hazard ratios for death were 0.51 (95% confidence interval: 0.30 to 0.87) for SAVR compared with MT and 0.38 (95% confidence interval: 0.25 to 0.58) for TAVI compared with MT. Medical treatment (<0.001), older age (>80 years, p = 0.01), peripheral vascular disease (<0.001), and atrial fibrillation (p = 0.04) were significantly associated with all-cause mortality at 30 months in the multivariate analysis. At 1 year, more patients undergoing SAVR (92.3%) or TAVI (93.2%) had New York Heart Association functional class I/II as compared with patients with MT (70.8%, p = 0.003). CONCLUSIONS: Among patients with severe AS with increased surgical risk, SAVR and TAVI improve survival and symptoms compared with MT. Clinical outcomes of TAVI and SAVR seem similar among carefully selected patients with severe symptomatic AS at increased risk.

Clinical outcome and predictors for adverse events after transcatheter aortic valve implantation with the use of different devices and access routes.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) is a treatment option for high-risk patients with severe aortic stenosis. Previous reports focused on a single device or access site, whereas little is known of the combined use of different devices and access sites as selected by the heart team. The purpose of this study is to investigate clinical outcomes of TAVI using different devices and access sites. METHODS: A consecutive cohort of 200 patients underwent TAVI with the Medtronic CoreValve Revalving system (Medtronic Core Valve LLC, Irvine, CA; n = 130) or the Edwards SAPIEN valve (Edwards Lifesciences LLC, Irvine, CA; n = 70) implanted by either the transfemoral or transapical access route. RESULTS: Device success and procedure success were 99% and 95%, respectively, without differences between devices and access site. All-cause mortality was 7.5% at 30 days, with no differences between valve types or access sites. Using multivariable analysis, low body mass index (<20 kg/m(2)) (odds ratio [OR] 6.6, 95% CI 1.5-29.5) and previous stroke (OR 4.4, 95% CI 1.2-16.8) were independent risk factors for short-term mortality. The VARC-defined combined safety end point occurred in 18% of patients and was driven by major access site complications (8.0%), life-threatening bleeding (8.5%) or severe renal failure (4.5%). Transapical access emerged as independent predictor of adverse outcome for the Valve Academic Research Consortium-combined safety end point (OR 3.3, 95% CI 1.5-7.1). CONCLUSION: A heart team-based selection of devices and access site among patients undergoing TAVI resulted in high device and procedural success. Low body mass index and history of previous stroke were independent predictors of mortality. Transapical access emerged as a risk factor for the Valve Academic Research Consortium-combined safety end point.

Perioperative anaesthetic management of mediastinal mass in adults.

Mediastinal mass syndrome remains an anaesthetic challenge that cannot be underestimated. Depending on the localization and the size of the mediastinal tumour, the clinical presentation is variable ranging from a complete lack of symptoms to severe cardiorespiratory problems. The administration of general anaesthesia can be associated with acute intraoperative or postoperative cardiorespiratory decompensation that may result in death due to tumour-related compression syndromes. The role of the anaesthesiologist, as a part of the interdisciplinary treatment team, is to ensure a safe perioperative period. However, there is still no structured protocol available for perioperative anaesthesiological procedure. The aim of this article is to summarize the genesis of and the diagnostic options for mediastinal mass syndrome and to provide a solid detailed methodology for its safe perioperative management based on a review of the latest literature and our own clinical experiences. Proper anaesthetic management of patients with mediastinal mass syndrome begins with an assessment of the preoperative status, directed foremost at establishing the localization of the tumour and on the basis of the clinical and radiological findings, discerning whether any vital mediastinal structures are affected. We have found it helpful to assign 'severity grade' (using a three-grade clinical classification scale: 'safe', 'uncertain', 'unsafe'), whereby each stage triggers appropriate action in terms of staffing and apparatus, such as the provision of alternatives for airway management, cardiopulmonary bypass and additional specialists. During the preoperative period, we are guided by a 12-point plan that also takes into account the special features of transportation into the operating theatre and patient monitoring. Tumour compression on the airways or the great vessels may create a critical respiratory and/or haemodynamic situation, and therefore the standard of intraoperative management includes induction of anaesthesia in the operating theatre on an adjustable surgical table, the use of short-acting anaesthetics, avoidance of muscle relaxants and maintenance of spontaneous respiration. In the case of severe clinical symptoms and large mediastinal tumours, we consider it absolutely essential to cannulate the femoral vessels preoperatively under local anaesthesia and to provide for the availability of cardiopulmonary bypass in the operating theatre, should extracorporeal circulation become necessary. The benefits of establishing vascular access under local anaesthesia clearly outweigh any associated degree of patient discomfort. In the case of patients classified as 'safe' or 'uncertain', a preoperative consensus with the surgeons should be reached as to the anaesthetic approach and the management of possible complications.

Two-dimensional and three-dimensional oxygen mapping by 3He-MRI validation in a lung phantom.

The aim of this study was to validate oxygen-sensitive 3He-MRI in noninvasive determination of the regional, two- and three-dimensional distribution of oxygen partial pressure. In a gas-filled elastic silicon ventilation bag used as a lung phantom, oxygen sensitive two- and three-dimensional 3He-MRI measurements were performed at different oxygen concentrations which had been equilibrated in a range of normal and pathologic values. The oxygen partial pressure distribution was determined from 3He-MRI using newly developed software allowing for mapping of oxygen partial pressure. The reference bulk oxygen partial pressure inside the phantom was measured by conventional respiratory gas analysis. In two-dimensional measurements, image-based and gas-analysis results correlated with r=0.98; in three-dimensional measurements the between-methods correlation coefficient was r=0.89. The signal-to-noise ratio of three-dimensional measurements was about half of that of two-dimensional measurements and became critical (below 3) in some data sets. Oxygen-sensitive 3He-MRI allows for noninvasive determination of the two- and three-dimensional distribution of oxygen partial pressure in gas-filled airspaces.