On the intrinsic disorder status of the major players in programmed cell death pathways

Not Only Systemin: Prosystemin Harbors Other Active Regions Able to Protect Tomato Plants

Prosystemin is a 200-amino acid precursor expressed in Solanaceae plants which releases at the C-terminal part a peptidic hormone called Systemin in response to wounding and herbivore attack. We recently showed that Prosystemin is not only a mere scaffold of Systemin but, even when deprived of Systemin, is biologically active. These results, combined with recent discoveries that Prosystemin is an intrinsically disordered protein containing disordered regions within its sequence, prompted us to investigate the N-terminal portions of the precursor, which contribute to the greatest disorder within the sequence. To this aim, PS1-70 and PS1-120 were designed, produced, and structurally and functionally characterized. Both the fragments, which maintained their intrinsic disorder, were able to induce defense-related genes and to protect tomato plants against Botrytis cinerea and Spodoptera littoralis larvae. Intriguingly, the biological activity of each of the two N-terminal fragments and of Systemin is similar but not quite the same and does not show any toxicity on experimental non-targets considered. These regions account for different anti-stress activities conferred to tomato plants by their overexpression. The two N-terminal fragments identified in this study may represent new promising tools for sustainable crop protection.

NLRP3 inflammasome activation and cell death

The NLRP3 inflammasome is a cytosolic multiprotein complex composed of the innate immune receptor protein NLRP3, adapter protein ASC, and inflammatory protease caspase-1 that responds to microbial infection, endogenous danger signals, and environmental stimuli. The assembled NLRP3 inflammasome can activate the protease caspase-1 to induce gasdermin D-dependent pyroptosis and facilitate the release of IL-1β and IL-18, which contribute to innate immune defense and homeostatic maintenance. However, aberrant activation of the NLRP3 inflammasome is associated with the pathogenesis of various inflammatory diseases, such as diabetes, cancer, and Alzheimer's disease. Recent studies have revealed that NLRP3 inflammasome activation contributes to not only pyroptosis but also other types of cell death, including apoptosis, necroptosis, and ferroptosis. In addition, various effectors of cell death have been reported to regulate NLRP3 inflammasome activation, suggesting that cell death is closely related to NLRP3 inflammasome activation. In this review, we summarize the inextricable link between NLRP3 inflammasome activation and cell death and discuss potential therapeutics that target cell death effectors in NLRP3 inflammasome-associated diseases.

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

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

DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server

Computational predictions of the intrinsic disorder and its functions are instrumental to facilitate annotation for the millions of unannotated proteins. However, access to these predictors is fragmented and requires substantial effort to find them and to collect and combine their results. The DEPICTER (DisorderEd PredictIon CenTER) server provides first-of-its-kind centralized access to 10 popular disorder and disorder function predictions that cover protein and nucleic acids binding, linkers, and moonlighting regions. It automates the prediction process, runs user-selected methods on the server side, visualizes the results, and outputs all predictions in a consistent and easy-to-parse format. DEPICTER also includes two accurate consensus predictors of disorder and disordered protein binding. Empirical tests on an independent (low similarity) benchmark dataset reveal that the computational tools included in DEPICTER generate accurate predictions that are significantly better than the results secured using sequence alignment. The DEPICTER server is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER/.

Sequence-Derived Markers of Drug Targets and Potentially Druggable Human Proteins

Recent research shows that majority of the druggable human proteome is yet to be annotated and explored. Accurate identification of these unexplored druggable proteins would facilitate development, screening, repurposing, and repositioning of drugs, as well as prediction of new drug–protein interactions. We contrast the current drug targets against the datasets of non-druggable and possibly druggable proteins to formulate markers that could be used to identify druggable proteins. We focus on the markers that can be extracted from protein sequences or names/identifiers to ensure that they can be applied across the entire human proteome. These markers quantify key features covered in the past works (topological features of PPIs, cellular functions, and subcellular locations) and several novel factors (intrinsic disorder, residue-level conservation, alternative splicing isoforms, domains, and sequence-derived solvent accessibility). We find that the possibly druggable proteins have significantly higher abundance of alternative splicing isoforms, relatively large number of domains, higher degree of centrality in the protein-protein interaction networks, and lower numbers of conserved and surface residues, when compared with the non-druggable proteins. We show that the current drug targets and possibly druggable proteins share involvement in the catalytic and signaling functions. However, unlike the drug targets, the possibly druggable proteins participate in the metabolic and biosynthesis processes, are enriched in the intrinsic disorder, interact with proteins and nucleic acids, and are localized across the cell. To sum up, we formulate several markers that can help with finding novel druggable human proteins and provide interesting insights into the cellular functions and subcellular locations of the current drug targets and potentially druggable proteins.

Accuracy of protein-level disorder predictions

Experimental annotations of intrinsic disorder are available for 0.1% of 147 000 000 of currently sequenced proteins. Over 60 sequence-based disorder predictors were developed to help bridge this gap. Current benchmarks of these methods assess predictive performance on datasets of proteins; however, predictions are often interpreted for individual proteins. We demonstrate that the protein-level predictive performance varies substantially from the dataset-level benchmarks. Thus, we perform first-of-its-kind protein-level assessment for 13 popular disorder predictors using 6200 disorder-annotated proteins. We show that the protein-level distributions are substantially skewed toward high predictive quality while having long tails of poor predictions. Consequently, between 57% and 75% proteins secure higher predictive performance than the currently used dataset-level assessment suggests, but as many as 30% of proteins that are located in the long tails suffer low predictive performance. These proteins typically have relatively high amounts of disorder, in contrast to the mostly structured proteins that are predicted accurately by all 13 methods. Interestingly, each predictor provides the most accurate results for some number of proteins, while the best-performing at the dataset-level method is in fact the best for only about 30% of proteins. Moreover, the majority of proteins are predicted more accurately than the dataset-level performance of the most accurate tool by at least four disorder predictors. While these results suggests that disorder predictors outperform their current benchmark performance for the majority of proteins and that they complement each other, novel tools that accurately identify the hard-to-predict proteins and that make accurate predictions for these proteins are needed.

Computational prediction of functions of intrinsically disordered regions

Intrinsically disorder regions (IDRs) are abundant in nature, particularly among Eukaryotes. While they facilitate a wide spectrum of cellular functions including signaling, molecular assembly and recognition, translation, transcription and regulation, only several hundred IDRs are annotated functionally. This annotation gap motivates the development of fast and accurate computational methods that predict IDR functions directly from protein sequences. We introduce and describe a comprehensive collection of 25 methods that provide accurate predictions of IDRs that interact with proteins and nucleic acids, that function as flexible linkers and that moonlight multiple functions. Virtually all of these predictors can be accessed online and many were developed in the last few years. They utilize a wide range of predictive architectures and take advantage of modern machine learning algorithms. Our empirical analysis shows that predictors that are available as webservers enjoy high rates of citations, attesting to their practical value and popularity. The most cited methods include DISOPRED3, ANCHOR, alpha-MoRFpred, MoRFpred, fMoRFpred and MoRFCHiBi. We present two case studies to demonstrate that predictions produced by these computational tools are relatively easy to interpret and that they deliver valuable functional clues. However, the current computational tools cover a relatively narrow range of disorder functions. Further development efforts that would cover a broader range of functions should be pursued. We demonstrate that a sufficient amount of functionally annotated IDRs that are associated with several other disorder functions is already available and can be used to design and validate novel predictors.

Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions

Molecular recognition features (MoRFs) are short protein-binding regions that undergo disorder-to-order transitions (induced folding) upon binding protein partners. These regions are abundant in nature and can be predicted from protein sequences based on their distinctive sequence signatures. This first-of-its-kind survey covers 14 MoRF predictors and six related methods for the prediction of short protein-binding linear motifs, disordered protein-binding regions and semi-disordered regions. We show that the development of MoRF predictors has accelerated in the recent years. These predictors depend on machine learning-derived models that were generated using training datasets where MoRFs are annotated using putative disorder. Our analysis reveals that they generate accurate predictions. We identified eight methods that offer area under the ROC curve (AUC) ≥ 0.7 on experimentally-validated test datasets. We show that modern MoRF predictors accurately find experimentally annotated MoRFs even though they were trained using the putative disorder annotations. They are relatively highly-cited, particularly the methods available as webservers that on average secure three times more citations than methods without this option. MoRF predictions contribute to the experimental discovery of protein-protein interactions, annotation of protein functions and computational analysis of a variety of proteomes, protein families, and pathways. We outline future development and application directions for these tools, stressing the importance to develop novel tools that would target interactions of disordered regions with other types of partners.

Modulation of Disordered Proteins with a Focus on Neurodegenerative Diseases and Other Pathologies

Intrinsically disordered proteins (IDPs) do not have rigid 3D structures, showing changes in their folding depending on the environment or ligands. Intrinsically disordered proteins are widely spread in eukaryotic genomes, and these proteins participate in many cell regulatory metabolism processes. Some IDPs, when aberrantly folded, can be the cause of some diseases such as Alzheimer′s, Parkinson′s, and prionic, among others. In these diseases, there are modifications in parts of the protein or in its entirety. A common conformational variation of these IDPs is misfolding and aggregation, forming, for instance, neurotoxic amyloid plaques. In this review, we discuss some IDPs that are involved in neurodegenerative diseases (such as beta amyloid, alpha synuclein, tau, and the “IDP-like” PrP), cancer (p53, c-Myc), and diabetes (amylin), focusing on the structural changes of these IDPs that are linked to such pathologies. We also present the IDP modulation mechanisms that can be explored in new strategies for drug design. Lastly, we show some candidate drugs that can be used in the future for the treatment of diseases caused by misfolded IDPs, considering that cancer therapy has more advanced research in comparison to other diseases, while also discussing recent and future developments in this area of research. Therefore, we aim to provide support to the study of IDPs and their modulation mechanisms as promising approaches to combat such severe diseases.

Biochemical, biophysical and molecular dynamics studies on the proteoglycan-like domain of carbonic anhydrase IX

Human carbonic anhydrase IX (hCA IX) is a tumour-associated enzyme present in a limited number of normal tissues, but overexpressed in several malignant human tumours. It is a transmembrane protein, where the extracellular region consists of a greatly investigated catalytic CA domain and a much less investigated proteoglycan-like (PG) domain. Considering its important role in tumour biology, here, we report for the first time the full characterization of the PG domain, providing insights into its structural and functional features. In particular, this domain has been produced at high yields in bacterial cells and characterized by means of biochemical, biophysical and molecular dynamics studies. Results show that it belongs to the family of intrinsically disordered proteins, being globally unfolded with only some local residual polyproline II secondary structure. The observed conformational flexibility may have several important roles in tumour progression, facilitating interactions of hCA IX with partner proteins assisting tumour spreading and progression.

The roles of intrinsic disorder-based liquid-liquid phase transitions in the "Dr. Jekyll-Mr. Hyde" behavior of proteins involved in amyotrophic lateral sclerosis and frontotemporal lobar degeneration

Pathological developments leading to amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) are associated with misbehavior of several key proteins, such as SOD1 (superoxide dismutase 1), TARDBP/TDP-43, FUS, C9orf72, and dipeptide repeat proteins generated as a result of the translation of the intronic hexanucleotide expansions in the C9orf72 gene, PFN1 (profilin 1), GLE1 (GLE1, RNA export mediator), PURA (purine rich element binding protein A), FLCN (folliculin), RBM45 (RNA binding motif protein 45), SS18L1/CREST, HNRNPA1 (heterogeneous nuclear ribonucleoprotein A1), HNRNPA2B1 (heterogeneous nuclear ribonucleoprotein A2/B1), ATXN2 (ataxin 2), MAPT (microtubule associated protein tau), and TIA1 (TIA1 cytotoxic granule associated RNA binding protein). Although these proteins are structurally and functionally different and have rather different pathological functions, they all possess some levels of intrinsic disorder and are either directly engaged in or are at least related to the physiological liquid-liquid phase transitions (LLPTs) leading to the formation of various proteinaceous membrane-less organelles (PMLOs), both normal and pathological. This review describes the normal and pathological functions of these ALS- and FTLD-related proteins, describes their major structural properties, glances at their intrinsic disorder status, and analyzes the involvement of these proteins in the formation of normal and pathological PMLOs, with the ultimate goal of better understanding the roles of LLPTs and intrinsic disorder in the "Dr. Jekyll-Mr. Hyde" behavior of those proteins.

Autophagy-related intrinsically disordered proteins in intra-nuclear compartments

Recent analyses indicated that autophagy can be regulated via some nuclear transcriptional networks and many important players in the autophagy and other forms of programmed cell death are known to be intrinsically disordered. To this end, we analyzed similarities and differences in the intrinsic disorder distribution of nuclear and non-nuclear proteins related to autophagy. We also looked at the peculiarities of the distribution of the intrinsically disordered autophagy-related proteins in various intra-nuclear organelles, such as the nucleolus, chromatin, Cajal bodies, nuclear speckles, promyelocytic leukemia (PML) nuclear bodies, nuclear lamina, nuclear pores, and perinucleolar compartment. This analysis revealed that the autophagy-related proteins constitute about 2.5% of the non-nuclear proteins and 3.3% of the nuclear proteins, which corresponds to a substantial enrichment by about 32% in the nucleus. Curiously, although, in general, the autophagy-related proteins share similar characteristics of disorder with a generic set of all non-nuclear proteins, chromatin and nuclear speckles are enriched in the intrinsically disordered autophagy proteins (29 and 37% of these proteins are disordered, respectively) and have high disorder content at 0.24 and 0.27, respectively. Therefore, our data suggest that some of the nuclear disordered proteins may play important roles in autophagy.

Intrinsically Disordered Proteins as Important Players during Desiccation Stress of Soybean Radicles

Intrinsically disordered proteins (IDPs) play a variety of important physiological roles in all living organisms. However, there is no comprehensive analysis of the abundance of IDPs associated with environmental stress in plants. Here, we show that a set of heat-stable proteins (i.e., proteins that do not denature after boiling at 100 °C for 10 min) was present in R0mm and R15mm radicles (i.e., before radicle emergence and 15 mm long radicles) of soybean (Glycine max) seeds. This set of 795 iTRAQ-quantified heat-stable proteins contained a high proportion of wholly or highly disordered proteins (15%), which was significantly higher than that estimated for the whole soybean proteome containing 55,787 proteins (9%). The heat-stable proteome of soybean radicles that contain many IDPs could protect lactate dehydrogenase (LDH) during freeze-thaw cycles. Comparison of the 795 heat-stable proteins in the R0mm and R15mm soybean radicles revealed that many of these proteins changed abundance during seedling growth with 170 and 89 proteins being more abundant in R0mm and R15mm, respectively. KEGG analysis identified 18 proteins from the cysteine and methionine metabolism pathways and nine proteins from the phenylpropanoid biosynthesis pathway. As an important type of IDP related to stress, 30 late embryogenesis abundant proteins were also found. Ten selected proteins with high levels of predicted intrinsic disorder were able to efficiently protect LDH from the freeze-thaw-induced inactivation, but the protective ability was not correlated with the disorder content of these proteins. These observations suggest that protection of the enzymes and other proteins in a stressed cell can be one of the biological functions of plant IDPs.

Caulobacter PopZ forms an intrinsically disordered hub in organizing bacterial cell poles

Despite their relative simplicity, bacteria have complex anatomy at the subcellular level. At the cell poles of Caulobacter crescentus, a 177-amino acid (aa) protein called PopZ self-assembles into 3D polymeric superstructures. Remarkably, we find that this assemblage interacts directly with at least eight different proteins, which are involved in cell cycle regulation and chromosome segregation. The binding determinants within PopZ include 24 aa at the N terminus, a 32-aa region near the C-terminal homo-oligomeric assembly domain, and portions of an intervening linker region. Together, the N-terminal 133 aa of PopZ are sufficient for interacting with all binding partners, even in the absence of homo-oligomeric assembly. Structural analysis of this region revealed that it is intrinsically disordered, similar to p53 and other hub proteins that organize complex signaling networks in eukaryotic cells. Through live-cell photobleaching, we find rapid binding kinetics between PopZ and its partners, suggesting many pole-localized proteins become concentrated at cell poles through rapid cycles of binding and unbinding within the PopZ scaffold. We conclude that some bacteria, similar to their eukaryotic counterparts, use intrinsically disordered hub proteins for network assembly and subcellular organization.

Calmodulin and STIM proteins: Two major calcium sensors in the cytoplasm and endoplasmic reticulum

The calcium (Ca(2+)) ion is a universal signalling messenger which plays vital physiological roles in all eukaryotes. To decode highly regulated intracellular Ca(2+) signals, cells have evolved a number of sensor proteins that are ideally adapted to respond to a specific range of Ca(2+) levels. Among many such proteins, calmodulin (CaM) is a multi-functional cytoplasmic Ca(2+) sensor with a remarkable ability to interact with and regulate a plethora of structurally diverse target proteins. CaM achieves this 'multi-talented' functionality through two EF-hand domains, each with an independent capacity to bind targets, and an adaptable flexible linker. By contrast, stromal interaction molecule-1 and -2 (STIMs) have evolved for a specific role in endoplasmic reticulum (ER) Ca(2+) sensing using EF-hand machinery analogous to CaM; however, whereas CaM structurally adjusts to dissimilar binding partners, STIMs use the EF-hand machinery to self-regulate the stability of the Ca(2+) sensing domain. The molecular mechanisms underlying the Ca(2+)-dependent signal transduction by CaM and STIMs have revealed a remarkable repertoire of actions and underscore the flexibility of nature in molecular evolution and adaption to discrete Ca(2+) levels. Recent genomic sequencing efforts have uncovered a number of disease-associated mutations in both CaM and STIM1. This article aims to highlight the most recent key structural and functional findings in the CaM and STIM fields, and discusses how these two Ca(2+) sensor proteins execute their biological functions.

Identifying Similar Patterns of Structural Flexibility in Proteins by Disorder Prediction and Dynamic Programming

Computational methods are prevailing in identifying protein intrinsic disorder. The results from predictors are often given as per-residue disorder scores. The scores describe the disorder propensity of amino acids of a protein and can be further represented as a disorder curve. Many proteins share similar patterns in their disorder curves. The similar patterns are often associated with similar functions and evolutionary origins. Therefore, finding and characterizing specific patterns of disorder curves provides a unique and attractive perspective of studying the function of intrinsically disordered proteins. In this study, we developed a new computational tool named IDalign using dynamic programming. This tool is able to identify similar patterns among disorder curves, as well as to present the distribution of intrinsic disorder in query proteins. The disorder-based information generated by IDalign is significantly different from the information retrieved from classical sequence alignments. This tool can also be used to infer functions of disordered regions and disordered proteins. The web server of IDalign is available at (http://labs.cas.usf.edu/bioinfo/service.html).

Myotubularin-related phosphatase 3 promotes growth of colorectal cancer cells

Due to changes in lifestyle, particularly changes in dietary habits, colorectal cancer (CRC) increased in recent years despite advances in treatment. Nearly one million new cases diagnosed worldwide and half a million deaths make CRC a leading cause of cancer mortality. In the present study, we aimed to investigate the role of myotubularin-related phosphatase 3 (MTMR3) in CRC cell growth via lentivirus-mediated small interfering RNA (siRNA) transduction in human colon cancer cell lines HCT116 and SW1116. The effect of MTMR3 knockdown on cell growth was evaluated by MTT, colony formation, and flow cytometry assays. The effect of MTMR3 knockdown on cell apoptosis was evaluated by flow cytometry with Annexin V/7-AAD double staining. The activation of apoptotic markers, Bad and PARP, was detected using Intracellular Signaling Array. Knockdown of MTMR3 resulted in a significant reduction in cell proliferation in both HCT116 and SW1116 cells. Moreover, knockdown of MTMR3 led to S phase cell cycle arrest. Furthermore, knockdown of MTMR3 induced cell apoptosis via phosphorylation of Bad and cleavage of PARP. These results indicate that MTMR3 may play an important role in the progression of CRC and suggest that siRNA mediated silencing of MTMR3 could be an effective tool in CRC treatment.