GraBCas: a bioinformatics tool for score-based prediction of Caspase- and Granzyme B-cleavage sites in protein sequences

Prediction and design of protease enzyme specificity using a structure-aware graph convolutional network

Site-specific proteolysis by the enzymatic cleavage of small linear sequence motifs is a key posttranslational modification involved in physiology and disease. The ability to robustly and rapidly predict protease-substrate specificity would also enable targeted proteolytic cleavage by designed proteases. Current methods for predicting protease specificity are limited to sequence pattern recognition in experimentally derived cleavage data obtained for libraries of potential substrates and generated separately for each protease variant. We reasoned that a more semantically rich and robust model of protease specificity could be developed by incorporating the energetics of molecular interactions between protease and substrates into machine learning workflows. We present Protein Graph Convolutional Network (PGCN), which develops a physically grounded, structure-based molecular interaction graph representation that describes molecular topology and interaction energetics to predict enzyme specificity. We show that PGCN accurately predicts the specificity landscapes of several variants of two model proteases. Node and edge ablation tests identified key graph elements for specificity prediction, some of which are consistent with known biochemical constraints for protease:substrate recognition. We used a pretrained PGCN model to guide the design of protease libraries for cleaving two noncanonical substrates, and found good agreement with experimental cleavage results. Importantly, the model can accurately assess designs featuring diversity at positions not present in the training data. The described methodology should enable the structure-based prediction of specificity landscapes of a wide variety of proteases and the construction of tailor-made protease editors for site-selectively and irreversibly modifying chosen target proteins.

Predicting Structural Susceptibility of Proteins to Proteolytic Processing

The importance of 3D protein structure in proteolytic processing is well known. However, despite the plethora of existing methods for predicting proteolytic sites, only a few of them utilize the structural features of potential substrates as predictors. Moreover, to our knowledge, there is currently no method available for predicting the structural susceptibility of protein regions to proteolysis. We developed such a method using data from CutDB, a database that contains experimentally verified proteolytic events. For prediction, we utilized structural features that have been shown to influence proteolysis in earlier studies, such as solvent accessibility, secondary structure, and temperature factor. Additionally, we introduced new structural features, including length of protruded loops and flexibility of protein termini. To maximize the prediction quality of the method, we carefully curated the training set, selected an appropriate machine learning method, and sampled negative examples to determine the optimal positive-to-negative class size ratio. We demonstrated that combining our method with models of protease primary specificity can outperform existing bioinformatics methods for the prediction of proteolytic sites. We also discussed the possibility of utilizing this method for bioinformatics prediction of other post-translational modifications.

Independent Membrane Binding Properties of the Caspase Generated Fragments of the Beaded Filament Structural Protein 1 (BFSP1) Involves an Amphipathic Helix

BACKGROUND

BFSP1 (beaded filament structural protein 1) is a plasma membrane, Aquaporin 0 (AQP0/MIP)-associated intermediate filament protein expressed in the eye lens. BFSP1 is myristoylated, a post-translation modification that requires caspase cleavage at D433. Bioinformatic analyses suggested that the sequences 434-452 were α-helical and amphipathic.

METHODS AND RESULTS

By CD spectroscopy, we show that the addition of trifluoroethanol induced a switch from an intrinsically disordered to a more α-helical conformation for the residues 434-467. Recombinantly produced BFSP1 fragments containing this amphipathic helix bind to lens lipid bilayers as determined by surface plasmon resonance (SPR). Lastly, we demonstrate by transient transfection of non-lens MCF7 cells that these same BFSP1 C-terminal sequences localise to plasma membranes and to cytoplasmic vesicles. These can be co-labelled with the vital dye, lysotracker, but other cell compartments, such as the nuclear and mitochondrial membranes, were negative. The N-terminal myristoylation of the amphipathic helix appeared not to change either the lipid affinity or membrane localisation of the BFSP1 polypeptides or fragments we assessed by SPR and transient transfection, but it did appear to enhance its helical content.

CONCLUSIONS

These data support the conclusion that C-terminal sequences of human BFSP1 distal to the caspase site at G433 have independent membrane binding properties via an adjacent amphipathic helix.

Prediction and Design of Protease Enzyme Specificity Using a Structure-Aware Graph Convolutional Network

Site-specific proteolysis by the enzymatic cleavage of small linear sequence motifs is a key post-translational modification involved in physiology and disease. The ability to robustly and rapidly predict protease substrate specificity would also enable targeted proteolytic cleavage - editing - of a target protein by designed proteases. Current methods for predicting protease specificity are limited to sequence pattern recognition in experimentally-derived cleavage data obtained for libraries of potential substrates and generated separately for each protease variant. We reasoned that a more semantically rich and robust model of protease specificity could be developed by incorporating the three-dimensional structure and energetics of molecular interactions between protease and substrates into machine learning workflows. We present Protein Graph Convolutional Network (PGCN), which develops a physically-grounded, structure-based molecular interaction graph representation that describes molecular topology and interaction energetics to predict enzyme specificity. We show that PGCN accurately predicts the specificity landscapes of several variants of two model proteases: the NS3/4 protease from the Hepatitis C virus (HCV) and the Tobacco Etch Virus (TEV) proteases. Node and edge ablation tests identified key graph elements for specificity prediction, some of which are consistent with known biochemical constraints for protease:substrate recognition. We used a pre-trained PGCN model to guide the design of TEV protease libraries for cleaving two non-canonical substrates, and found good agreement with experimental cleavage results. Importantly, the model can accurately assess designs featuring diversity at positions not present in the training data. The described methodology should enable the structure-based prediction of specificity landscapes of a wide variety of proteases and the construction of tailor-made protease editors for site-selectively and irreversibly modifying chosen target proteins.

Characterization of Novel Pathogenic Variants Leading to Caspase-8 Cleavage-Resistant RIPK1-Induced Autoinflammatory Syndrome

Pathogenic RIPK1 variants have been described as the cause of two different inborn errors of immunity. Biallelic loss-of-function variants cause the recessively inherited RIPK1 deficiency, while monoallelic variants impairing the caspase-8-mediated RIPK1 cleavage provoke a novel autoinflammatory disease (AID) called cleavage-resistant RIPK1-induced autoinflammatory (CRIA) syndrome. The aim of this study was to characterize the pathogenicity of two novel RIPK1 variants located at the cleavage site of caspase-8 detected in patients with dominantly-inherited, early-onset undefined AID. RIPK1 genotyping was performed by Sanger and next-generation sequencing. Clinical and analytical data were collected from medical charts, and in silico and in vitro assays were performed to evaluate the functional consequences. Genetic analyses identified two novel heterozygous RIPK1 variants at the caspase-8 cleavage site (p.Leu321Arg and p.Asp324Gly), which displayed a perfect intrafamilial phenotype-genotype segregation following a dominant inheritance pattern. Structural analyses suggested that these variants disrupt the normal RIPK1 structure, probably making it less accessible to and/or less cleavable by caspase-8. In vitro experiments confirmed that the p.Leu321Arg and p.Asp324Gly RIPK1 variants were resistant to caspase-8-mediated cleavage and induced a constitutive activation of necroptotic pathway in a similar manner that previously characterized RIPK1 variants causing CRIA syndrome. All these results strongly supported the pathogenicity of the two novel RIPK1 variants and the diagnosis of CRIA syndrome in all enrolled patients. Moreover, the evidences here collected expand the phenotypic and genetic diversity of this recently described AID, and provide interesting data about effectiveness of treatments that may benefit future patients.

Emerging Canonical and Non-Canonical Roles of Granzyme B in Health and Disease

The Granzyme (Gzm) family has classically been recognized as a cytotoxic tool utilized by cytotoxic T lymphocytes (CTL) and natural killer (NK) cells to illicit cell death to infected and cancerous cells. Their importance is established based on evidence showing that deficiencies in these cell death executors result in defective immune responses. Recent findings have shown the importance of Granzyme B (GzmB) in regulatory immune cells, which may contribute to tumor growth and immune evasion during cancer development. Other studies have shown that members of the Gzm family are important for biological processes such as extracellular matrix remodeling, angiogenesis and organized vascular degradation. With this growing body of evidence, it is becoming more important to understand the broader function of Gzm's rather than a specific executor of cell death, and we should be aware of the many alternative roles that Gzm's play in physiological and pathological conditions. Therefore, we review the classical as well as novel non-canonical functions of GzmB and discuss approaches to utilize these new findings to address current gaps in our understanding of the immune system and tissue development.

Cell Death Related Proteins Beyond Apoptosis in the CNS

Cell death related (CDR) proteins are a diverse group of proteins whose original function was ascribed to apoptotic cell death signaling. Recently, descriptions of non-apoptotic functions for CDR proteins have increased. In this minireview, we comment on recent studies of CDR proteins outside the field of apoptosis in the CNS, encompassing areas such as the inflammasome and non-apoptotic cell death, cytoskeleton reorganization, synaptic plasticity, mitophagy, neurodegeneration and calcium signaling among others. Furthermore, we discuss the evolution of proteomic techniques used to predict caspase substrates that could potentially explain their non-apoptotic roles. Finally, we address new concepts in the field of non-apoptotic functions of CDR proteins that require further research such the effect of sexual dimorphism on non-apoptotic CDR protein function and the emergence of zymogen-specific caspase functions.

Integrated analysis of label-free quantitative proteomics and bioinformatics reveal insights into signaling pathways in male breast cancer

Male breast cancer (MBC) is a rare malignancy that accounts for about 1.8% of all breast cancer cases. In contrast to the high number of the “omics” studies in breast cancer in women, only recently molecular approaches have been performed in MBC research. High-throughput proteomics based methodologies are promisor strategies to characterize the MBC proteomic signatures and their association with clinico-pathological parameters. In this study, the label-free quantification-mass spectrometry and bioinformatics approaches were applied to analyze the proteomic profiling of a MBC case using the primary breast tumor and the corresponding axillary metastatic lymph nodes and adjacent non-tumor breast tissues. The differentially expressed proteins were identified in the signaling pathways of granzyme B, sirtuins, eIF2, actin cytoskeleton, eNOS, acute phase response and calcium and were connected to the upstream regulators MYC, PI3K SMARCA4 and cancer-related chemical drugs. An additional proteomic comparative analysis was performed with a primary breast tumor of a female patient and revealed an interesting set of proteins, which were mainly involved in cancer biology. Together, our data provide a relevant data source for the MBC research that can help the therapeutic strategies for its management.

Therapeutic peptides for the treatment of cystic fibrosis: Challenges and perspectives

Cystic fibrosis (CF) is the most common amongst rare genetic diseases, affecting more than 70.000 people worldwide. CF is characterized by a dysfunctional chloride channel, termed cystic fibrosis conductance regulator (CFTR), which leads to the production of a thick and viscous mucus layer that clogs the lungs of CF patients and traps pathogens, leading to chronic infections and inflammation and, ultimately, lung damage. In recent years, the use of peptides for the treatment of respiratory diseases, including CF, has gained growing interest. Therapeutic peptides for CF include antimicrobial peptides, inhibitors of proteases, and modulators of ion channels, among others. Peptides display unique features that make them appealing candidates for clinical translation, like specificity of action, high efficacy, and low toxicity. Nevertheless, the intrinsic properties of peptides, together with the need of delivering these compounds locally, e.g. by inhalation, raise a number of concerns in the development of peptide therapeutics for CF lung disease. In this review, we discuss the challenges related to the use of peptides for the treatment of CF lung disease through inhalation, which include retention within mucus, proteolysis, immunogenicity and aggregation. Strategies for overcoming major shortcomings of peptide therapeutics will be presented, together with recent developments in peptide design and optimization, including computational analysis and high-throughput screening.

iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites

Regulation of proteolysis plays a critical role in a myriad of important cellular processes. The key to better understanding the mechanisms that control this process is to identify the specific substrates that each protease targets. To address this, we have developed iProt-Sub, a powerful bioinformatics tool for the accurate prediction of protease-specific substrates and their cleavage sites. Importantly, iProt-Sub represents a significantly advanced version of its successful predecessor, PROSPER. It provides optimized cleavage site prediction models with better prediction performance and coverage for more species-specific proteases (4 major protease families and 38 different proteases). iProt-Sub integrates heterogeneous sequence and structural features and uses a two-step feature selection procedure to further remove redundant and irrelevant features in an effort to improve the cleavage site prediction accuracy. Features used by iProt-Sub are encoded by 11 different sequence encoding schemes, including local amino acid sequence profile, secondary structure, solvent accessibility and native disorder, which will allow a more accurate representation of the protease specificity of approximately 38 proteases and training of the prediction models. Benchmarking experiments using cross-validation and independent tests showed that iProt-Sub is able to achieve a better performance than several existing generic tools. We anticipate that iProt-Sub will be a powerful tool for proteome-wide prediction of protease-specific substrates and their cleavage sites, and will facilitate hypothesis-driven functional interrogation of protease-specific substrate cleavage and proteolytic events.

Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods

The roles of proteolytic cleavage have been intensively investigated and discussed during the past two decades. This irreversible chemical process has been frequently reported to influence a number of crucial biological processes (BPs), such as cell cycle, protein regulation and inflammation. A number of advanced studies have been published aiming at deciphering the mechanisms of proteolytic cleavage. Given its significance and the large number of functionally enriched substrates targeted by specific proteases, many computational approaches have been established for accurate prediction of protease-specific substrates and their cleavage sites. Consequently, there is an urgent need to systematically assess the state-of-the-art computational approaches for protease-specific cleavage site prediction to further advance the existing methodologies and to improve the prediction performance. With this goal in mind, in this article, we carefully evaluated a total of 19 computational methods (including 8 scoring function-based methods and 11 machine learning-based methods) in terms of their underlying algorithm, calculated features, performance evaluation and software usability. Then, extensive independent tests were performed to assess the robustness and scalability of the reviewed methods using our carefully prepared independent test data sets with 3641 cleavage sites (specific to 10 proteases). The comparative experimental results demonstrate that PROSPERous is the most accurate generic method for predicting eight protease-specific cleavage sites, while GPS-CCD and LabCaS outperformed other predictors for calpain-specific cleavage sites. Based on our review, we then outlined some potential ways to improve the prediction performance and ease the computational burden by applying ensemble learning, deep learning, positive unlabeled learning and parallel and distributed computing techniques. We anticipate that our study will serve as a practical and useful guide for interested readers to further advance next-generation bioinformatics tools for protease-specific cleavage site prediction.

Granzyme B Cleaves Multiple Herpes Simplex Virus 1 and Varicella-Zoster Virus (VZV) Gene Products, and VZV ORF4 Inhibits Natural Killer Cell Cytotoxicity

Immune regulation of alphaherpesvirus latency and reactivation is critical for the control of virus pathogenesis. This is evident for herpes simplex virus 1 (HSV-1), where cytotoxic T lymphocytes (CTLs) prevent viral reactivation independent of apoptosis induction. This inhibition of HSV-1 reactivation has been attributed to granzyme B cleavage of HSV infected cell protein 4 (ICP4); however, it is unknown whether granzyme B cleavage of ICP4 can directly protect cells from CTL cytotoxicity. Varicella zoster virus (VZV) is closely related to HSV-1; however, it is unknown whether VZV proteins contain granzyme B cleavage sites. Natural killer (NK) cells play a central role in VZV and HSV-1 pathogenesis and, like CTLs, utilize granzyme B to kill virally infected target cells. However, whether alphaherpesvirus granzyme B cleavage sites could modulate NK cell-mediated cytotoxicity has yet to be established. This study aimed to identify novel HSV-1 and VZV gene products with granzyme B cleavage sites and assess whether they could protect cells from NK cell-mediated cytotoxicity. We have demonstrated that HSV ICP27, VZV open reading frame 62 (ORF62), and VZV ORF4 are cleaved by granzyme B. However, in an NK cell cytotoxicity assay, only VZV ORF4 conferred protection from NK cell-mediated cytotoxicity. The granzyme B cleavage site in ORF4 was identified via site-directed mutagenesis and, surprisingly, the mutation of this cleavage site did not alter the ability of ORF4 to modulate NK cell cytotoxicity, suggesting that ORF4 has a novel immunoevasive function that is independent from the granzyme B cleavage site.IMPORTANCE HSV-1 causes oral and genital herpes and establishes life-long latency in sensory ganglia. HSV-1 reactivates multiple times in a person's life and can cause life-threatening disease in immunocompromised patients. VZV is closely related to HSV-1, causes chickenpox during primary infection, and establishes life-long latency in ganglia, from where it can reactivate to cause herpes zoster (shingles). Unlike HSV-1, VZV only infects humans, and there are limited model systems; thus, little is known concerning how VZV maintains latency and why VZV reactivates. Through studying the link between immune cell cytotoxic functions, granzyme B, and viral gene products, an increased understanding of viral pathogenesis will be achieved.

Toward more accurate prediction of caspase cleavage sites: a comprehensive review of current methods, tools and features

As one of the few irreversible protein posttranslational modifications, proteolytic cleavage is involved in nearly all aspects of cellular activities, ranging from gene regulation to cell life-cycle regulation. Among the various protease-specific types of proteolytic cleavage, cleavages by casapses/granzyme B are considered as essential in the initiation and execution of programmed cell death and inflammation processes. Although a number of substrates for both types of proteolytic cleavage have been experimentally identified, the complete repertoire of caspases and granzyme B substrates remains to be fully characterized. To tackle this issue and complement experimental efforts for substrate identification, systematic bioinformatics studies of known cleavage sites provide important insights into caspase/granzyme B substrate specificity, and facilitate the discovery of novel substrates. In this article, we review and benchmark 12 state-of-the-art sequence-based bioinformatics approaches and tools for caspases/granzyme B cleavage prediction. We evaluate and compare these methods in terms of their input/output, algorithms used, prediction performance, validation methods and software availability and utility. In addition, we construct independent data sets consisting of caspases/granzyme B substrates from different species and accordingly assess the predictive power of these different predictors for the identification of cleavage sites. We find that the prediction results are highly variable among different predictors. Furthermore, we experimentally validate the predictions of a case study by performing caspase cleavage assay. We anticipate that this comprehensive review and survey analysis will provide an insightful resource for biologists and bioinformaticians who are interested in using and/or developing tools for caspase/granzyme B cleavage prediction.

PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy

Summary

Proteases are enzymes that specifically cleave the peptide backbone of their target proteins. As an important type of irreversible post-translational modification, protein cleavage underlies many key physiological processes. When dysregulated, proteases' actions are associated with numerous diseases. Many proteases are highly specific, cleaving only those target substrates that present certain particular amino acid sequence patterns. Therefore, tools that successfully identify potential target substrates for proteases may also identify previously unknown, physiologically relevant cleavage sites, thus providing insights into biological processes and guiding hypothesis-driven experiments aimed at verifying protease-substrate interaction. In this work, we present PROSPERous, a tool for rapid in silico prediction of protease-specific cleavage sites in substrate sequences. Our tool is based on logistic regression models and uses different scoring functions and their pairwise combinations to subsequently predict potential cleavage sites. PROSPERous represents a state-of-the-art tool that enables fast, accurate and high-throughput prediction of substrate cleavage sites for 90 proteases.

Availability and implementation

http://prosperous.erc.monash.edu/.

Contact

jiangning.song@monash.edu or geoff.webb@monash.edu or r.pike@latrobe.edu.au.

Supplementary information

Supplementary data are available at Bioinformatics online.

BFSP1 C-terminal domains released by post-translational processing events can alter significantly the calcium regulation of AQP0 water permeability

BFSP1 (beaded filament structural protein 1, filensin) is a cytoskeletal protein expressed in the eye lens. It binds AQP0 in vitro and its C-terminal sequences have been suggested to regulate the water channel activity of AQP0. A myristoylated fragment from the C-terminus of BFSP1 was found in AQP0 enriched fractions. Here we identify BFSP1 as a substrate for caspase-mediated cleavage at several C-terminal sites including D433. Cleavage at D433 exposes a cryptic myristoylation sequence (434–440). We confirm that this sequence is an excellent substrate for both NMT1 and 2 (N-myristoyl transferase). Thus caspase cleavage may promote formation of myristoylated fragments derived from the BFSP1 C-terminus (G434-S665). Myristoylation at G434 is not required for membrane association. Biochemical fractionation and immunogold labeling confirmed that C-terminal BFSP1 fragments containing the myristoylation sequence colocalized with AQP0 in the same plasma membrane compartments of lens fibre cells. To determine the functional significance of the association of BFSP1 G434-S665 sequences with AQP0, we measured AQP0 water permeability in Xenopus oocytes co-transfected with transcripts expressing both AQP0 and various C-terminal domain fragments of BFSP1 generated by caspase cleavage. We found that different fragments dramatically alter the response of AQP0 to different concentrations of Ca²⁺. The complete C-terminal fragment (G434-S665) eliminates calcium regulation altogether. Shorter fragments can enhance regulation by elevated calcium or reverse the response, indicative of the regulatory potential of BFSP1 with respect to AQP0. In particular, elimination of the myristoylation site by the mutation G434A reverses the order of water permeability sensitivity to different Ca²⁺ concentrations.

Orthohantaviruses belonging to three phylogroups all inhibit apoptosis in infected target cells

Orthohantaviruses, previously known as hantaviruses, are zoonotic viruses that can cause hantavirus pulmonary syndrome (HPS) and hemorrhagic fever with renal syndrome (HFRS) in humans. The HPS-causing Andes virus (ANDV) and the HFRS-causing Hantaan virus (HTNV) have anti-apoptotic effects. To investigate if this represents a general feature of orthohantaviruses, we analysed the capacity of six different orthohantaviruses – belonging to three distinct phylogroups and representing both pathogenic and non-pathogenic viruses – to inhibit apoptosis in infected cells. Primary human endothelial cells were infected with ANDV, HTNV, the HFRS-causing Puumala virus (PUUV) and Seoul virus, as well as the putative non-pathogenic Prospect Hill virus and Tula virus. Infected cells were then exposed to the apoptosis-inducing chemical staurosporine or to activated human NK cells exhibiting a high cytotoxic potential. Strikingly, all orthohantaviruses inhibited apoptosis in both settings. Moreover, we show that the nucleocapsid (N) protein from all examined orthohantaviruses are potential targets for caspase-3 and granzyme B. Recombinant N protein from ANDV, PUUV and the HFRS-causing Dobrava virus strongly inhibited granzyme B activity and also, to certain extent, caspase-3 activity. Taken together, this study demonstrates that six different orthohantaviruses inhibit apoptosis, suggesting this to be a general feature of orthohantaviruses likely serving as a mechanism of viral immune evasion.

Software-aided workflow for predicting protease-specific cleavage sites using physicochemical properties of the natural and unnatural amino acids in peptide-based drug discovery

Peptide drugs have been used in the treatment of multiple pathologies. During peptide discovery, it is crucially important to be able to map the potential sites of cleavages of the proteases. This knowledge is used to later chemically modify the peptide drug to adapt it for the therapeutic use, making peptide stable against individual proteases or in complex medias. In some other cases it needed to make it specifically unstable for some proteases, as peptides could be used as a system to target delivery drugs on specific tissues or cells. The information about proteases, their sites of cleavages and substrates are widely spread across publications and collected in databases such as MEROPS. Therefore, it is possible to develop models to improve the understanding of the potential peptide drug proteolysis. We propose a new workflow to derive protease specificity rules and predict the potential scissile bonds in peptides for individual proteases. WebMetabase stores the information from experimental or external sources in a chemically aware database where each peptide and site of cleavage is represented as a sequence of structural blocks connected by amide bonds and characterized by its physicochemical properties described by Volsurf descriptors. Thus, this methodology could be applied in the case of non-standard amino acid. A frequency analysis can be performed in WebMetabase to discover the most frequent cleavage sites. These results were used to train several models using logistic regression, support vector machine and ensemble tree classifiers to map cleavage sites for several human proteases from four different families (serine, cysteine, aspartic and matrix metalloproteases). Finally, we compared the predictive performance of the developed models with other available public tools PROSPERous and SitePrediction.

CalCleaveMKL: a Tool for Calpain Cleavage Prediction

Calpain, an intracellular Ca²⁺-dependent cysteine protease, is known to play a role in a wide range of metabolic pathways through limited proteolysis of its substrates. However, only a limited number of these substrates are currently known, with the exact mechanism of substrate recognition and cleavage by calpain still largely unknown.Current sequencing technologies have made it possible to compile large amounts of cleavage data and brought greater understanding of the underlying protein interactions. However, the practical impossibility of exhaustively retrieving substrate sequences through experimentation alone has created the need for efficient computational prediction methods. Such methods must be able to quickly mark substrate candidates and putative cleavage sites for further analysis. While many methods exist for both calpain and other types of proteolytic actions, the expected reliability of these methods depends heavily on the type and complexity of proteolytic action, as well as the availability of well-labeled experimental datasets, which both vary greatly across enzyme families.This chapter introduces CalCleaveMKL: a tool for calpain cleavage prediction based on multiple kernel learning, an extension to the classic support vector machine framework that is able to train complex models based on rich, heterogeneous feature sets, leading to significantly improved prediction quality. Along with its improved accuracy, the method used by CalCleaveMKL provided numerous insights on the respective importance of sequence-related features, such as solvent accessibility and secondary structure. It notably demonstrated there existed significant specificity differences across calpain subtypes, despite previous assumption to the contrary.An online implementation of this prediction tool is available at http://calpain.org .

Single-Fluorescent Protein Reporters Allow Parallel Quantification of Natural Killer Cell-Mediated Granzyme and Caspase Activities in Single Target Cells

Natural killer (NK) cells eliminate infected and tumorigenic cells through delivery of granzymes via perforin pores or by activation of caspases via death receptors. In order to understand how NK cells combine different cell death mechanisms, it is important to quantify target cell responses on a single cell level. However, currently existing reporters do not allow the measurement of several protease activities inside the same cell. Here, we present a strategy for the comparison of two different proteases at a time inside individual target cells upon engagement by NK cells. We developed single-fluorescent protein reporters containing the RIEAD or the VGPD cleavage site for the measurement of granzyme B activity. We show that these two granzyme B reporters can be applied in combination with caspase-8 or caspase-3 reporters. While we did not find that caspase-8 was activated by granzyme B, our method revealed that caspase-3 activity follows granzyme B activity with a delay of about 6 min. Finally, we illustrate the comparison of several different reporters for granzyme A, M, K, and H. The approach presented here is a valuable means for the investigation of the temporal evolution of cell death mediated by cytotoxic lymphocytes.

Global substrate specificity profiling of post-translational modifying enzymes

Enzymes that modify the proteome, referred to as post-translational modifying (PTM) enzymes, are central regulators of cellular signaling. Determining the substrate specificity of PTM enzymes is a critical step in unraveling their biological functions both in normal physiological processes and in disease states. Advances in peptide chemistry over the last century have enabled the rapid generation of peptide libraries for querying substrate recognition by PTM enzymes. In this article, we highlight various peptide-based approaches for analysis of PTM enzyme substrate specificity. We focus on the application of these technologies to proteases and also discuss specific examples in which they have been used to uncover the substrate specificity of other types of PTM enzymes, such as kinases. In particular, we highlight our multiplex substrate profiling by mass spectrometry (MSP-MS) assay, which uses a rationally designed, physicochemically diverse library of tetradecapeptides. We show how this method has been applied to PTM enzymes to uncover biological function, and guide substrate and inhibitor design. We also briefly discuss how this technique can be combined with other methods to gain a systems-level understanding of PTM enzyme regulation and function.

Interferon regulatory factor 8 regulates caspase-1 expression to facilitate Epstein-Barr virus reactivation in response to B cell receptor stimulation and chemical induction

Interferon regulatory factor 8 (IRF8), also known as interferon consensus sequence-binding protein (ICSBP), is a transcription factor of the IRF family. IRF8 plays a key role in normal B cell differentiation, a cellular process that is intrinsically associated with Epstein-Barr virus (EBV) reactivation. However, whether IRF8 regulates EBV lytic replication remains unknown. In this study, we utilized a CRISPR/Cas9 genomic editing approach to deplete IRF8 and found that IRF8 depletion dramatically inhibits the reactivation of EBV upon lytic induction. We demonstrated that IRF8 depletion suppresses the expression of a group of genes involved in apoptosis and thus inhibits apoptosis induction upon lytic induction by B cell receptor (BCR) stimulation or chemical induction. The protein levels of caspase-1, caspase-3 and caspase-8 all dramatically decreased in IRF8-depleted cells, which led to reduced caspase activation and the stabilization of KAP1, PAX5 and DNMT3A upon BCR stimulation. Interestingly, caspase inhibition blocked the degradation of KAP1, PAX5 and DNMT3A, suppressed EBV lytic gene expression and viral DNA replication upon lytic induction, suggesting that the reduced caspase expression in IRF8-depleted cells contributes to the suppression of EBV lytic replication. We further demonstrated that IRF8 directly regulates CASP1 (caspase-1) gene expression through targeting its gene promoter and knockdown of caspase-1 abrogates EBV reactivation upon lytic induction, partially through the stabilization of KAP1. Together our study suggested that, by modulating the activation of caspases and the subsequent cleavage of KAP1 upon lytic induction, IRF8 plays a critical role in EBV lytic reactivation.

Infection with Epstein-Barr virus (EBV) is closely associated with human cancers of both B cell and epithelial cell origin. The EBV life cycle is tightly regulated by both viral and cellular factors. Here, we demonstrate that interferon regulatory factor 8 (IRF8) is required for EBV lytic replication. Mechanistically, IRF8 directly regulates caspase-1 expression and hence caspase activation upon B cell receptor (BCR) stimulation and chemical induction, which leads to the cleavage and de-stabilization of several host factors suppressing lytic replication, including KAP1. Caspase-1 depletion blocks EBV reactivation while KAP1 depletion facilitates reactivation in caspase-1 depleted cells. These results together establish a IRF8/caspase-1/KAP1 axis important for EBV reactivation.

Knowledge-transfer learning for prediction of matrix metalloprotease substrate-cleavage sites

Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced proteomic technologies have identified type-specific target substrates; however, the complete repertoire of MMP substrates remains uncharacterized. Indeed, computational prediction of substrate-cleavage sites associated with MMPs is a challenging problem. This holds especially true when considering MMPs with few experimentally verified cleavage sites, such as for MMP-2, -3, -7, and -8. To fill this gap, we propose a new knowledge-transfer computational framework which effectively utilizes the hidden shared knowledge from some MMP types to enhance predictions of other, distinct target substrate-cleavage sites. Our computational framework uses support vector machines combined with transfer machine learning and feature selection. To demonstrate the value of the model, we extracted a variety of substrate sequence-derived features and compared the performance of our method using both 5-fold cross-validation and independent tests. The results show that our transfer-learning-based method provides a robust performance, which is at least comparable to traditional feature-selection methods for prediction of MMP-2, -3, -7, -8, -9 and -12 substrate-cleavage sites on independent tests. The results also demonstrate that our proposed computational framework provides a useful alternative for the characterization of sequence-level determinants of MMP-substrate specificity.

The linear ubiquitin chain assembly complex regulates TRAIL-induced gene activation and cell death

The linear ubiquitin chain assembly complex (LUBAC) is the only known E3 ubiquitin ligase which catalyses the generation of linear ubiquitin linkages de novo LUBAC is a crucial component of various immune receptor signalling pathways. Here, we show that LUBAC forms part of the TRAIL-R-associated complex I as well as of the cytoplasmic TRAIL-induced complex II In both of these complexes, HOIP limits caspase-8 activity and, consequently, apoptosis whilst being itself cleaved in a caspase-8-dependent manner. Yet, by limiting the formation of a RIPK1/RIPK3/MLKL-containing complex, LUBAC also restricts TRAIL-induced necroptosis. We identify RIPK1 and caspase-8 as linearly ubiquitinated targets of LUBAC following TRAIL stimulation. Contrary to its role in preventing TRAIL-induced RIPK1-independent apoptosis, HOIP presence, but not its activity, is required for preventing necroptosis. By promoting recruitment of the IKK complex to complex I, LUBAC also promotes TRAIL-induced activation of NF-κB and, consequently, the production of cytokines, downstream of FADD, caspase-8 and cIAP1/2. Hence, LUBAC controls the TRAIL signalling outcome from complex I and II, two platforms which both trigger cell death and gene activation.

Processing and secretion of guanylate binding protein-1 depend on inflammatory caspase activity

Human guanylate binding protein‐1 (GBP‐1) belongs to the family of large GTPases. The expression of GBP‐1 is inducible by inflammatory cytokines, and the protein is involved in inflammatory processes and host defence against cellular pathogens. GBP‐1 is the first GTPase which was described to be secreted by eukaryotic cells. Here, we report that precipitation of GBP‐1 with GMP‐agarose from cell culture supernatants co‐purified a 47‐kD fragment of GBP‐1 (p47‐GBP‐1) in addition to the 67‐kD full‐length form. MALDI‐TOF sequencing revealed that p47‐GBP‐1 corresponds to the C‐terminal helical part of GBP‐1 and lacks most of the globular GTPase domain. In silico analyses of protease target sites, together with cleavage experiments in vitro and in vivo, showed that p67‐GBP‐1 is cleaved by the inflammatory caspases 1 and 5, leading to the formation of p47‐GBP‐1. Furthermore, the secretion of p47‐GBP‐1 was found to occur via a non‐classical secretion pathway and to be dependent on caspase‐1 activity but independent of inflammasome activation. Finally, we showed that p47‐GBP‐1 represents the predominant form of secreted GBP‐1, both in cell culture supernatants and, in vivo, in the cerebrospinal fluid of patients with bacterial meningitis, indicating that it may represent the biologically active form of extracellular GBP‐1. These findings confirm the involvement of caspase‐1 in non‐classical secretion mechanisms and open novel perspectives for the extracellular function of secreted GBP‐1.

Macrophage activation and polarization modify P2X7 receptor secretome influencing the inflammatory process

The activation of P2X7 receptor (P2X7R) on M1 polarized macrophages induces the assembly of the NLRP3 inflammasome leading to the release of pro-inflammatory cytokines and the establishment of the inflammatory response. However, P2X7R signaling to the NLRP3 inflammasome is uncoupled on M2 macrophages without changes on receptor activation. In this study, we analyzed P2X7R secretome in wild-type and P2X7R-deficient macrophages polarized either to M1 or M2 and proved that proteins released after P2X7R stimulation goes beyond caspase-1 secretome. The characterization of P2X7R-secretome reveals a new function of this receptor through a fine-tuning of protein release. We found that P2X7R stimulation in macrophages is able to release potent anti-inflammatory proteins, such as Annexin A1, independently of their polarization state suggesting for first time a potential role for P2X7R during resolution of the inflammation and not linked to the release of pro-inflammatory cytokines. These results are of prime importance for the development of therapeutics targeting P2X7R.

Predictions of Cleavability of Calpain Proteolysis by Quantitative Structure-Activity Relationship Analysis Using Newly Determined Cleavage Sites and Catalytic Efficiencies of an Oligopeptide Array

Calpains are intracellular Ca²⁺-regulated cysteine proteases that are essential for various cellular functions. Mammalian conventional calpains (calpain-1 and calpain-2) modulate the structure and function of their substrates by limited proteolysis. Thus, it is critically important to determine the site(s) in proteins at which calpains cleave. However, the calpains' substrate specificity remains unclear, because the amino acid (aa) sequences around their cleavage sites are very diverse. To clarify calpains' substrate specificities, 84 20-mer oligopeptides, corresponding to P10-P10′ of reported cleavage site sequences, were proteolyzed by calpains, and the catalytic efficiencies (k_cat/K_m) were globally determined by LC/MS. This analysis revealed 483 cleavage site sequences, including 360 novel ones. The k_cat/K_ms for 119 sites ranged from 12.5–1,710 M⁻¹s⁻¹. Although most sites were cleaved by both calpain-1 and −2 with a similar k_cat/K_m, sequence comparisons revealed distinct aa preferences at P9-P7/P2/P5′. The aa compositions of the novel sites were not statistically different from those of previously reported sites as a whole, suggesting calpains have a strict implicit rule for sequence specificity, and that the limited proteolysis of intact substrates is because of substrates' higher-order structures. Cleavage position frequencies indicated that longer sequences N-terminal to the cleavage site (P-sites) were preferred for proteolysis over C-terminal (P′-sites). Quantitative structure-activity relationship (QSAR) analyses using partial least-squares regression and >1,300 aa descriptors achieved k_cat/K_m prediction with r = 0.834, and binary-QSAR modeling attained an 87.5% positive prediction value for 132 reported calpain cleavage sites independent of our model construction. These results outperformed previous calpain cleavage predictors, and revealed the importance of the P2, P3′, and P4′ sites, and P1-P2 cooperativity. Furthermore, using our binary-QSAR model, novel cleavage sites in myoglobin were identified, verifying our predictor. This study increases our understanding of calpain substrate specificities, and opens calpains to “next-generation,” i.e. activity-related quantitative and cooperativity-dependent analyses.

A combined cheminformatic and bioinformatic approach to address the proteolytic stability challenge in peptide-based drug discovery

We have created models to predict cleavage sites for several human proteases including caspase-1, caspase-3, caspase-6, caspase-7, cathepsin B, cathepsin D, cathepsin G, cathepsin K, cathepsin L, elastase-2, granzyme A, granzyme B, matrix metallopeptidase-2 (MMP2), MMP7, MMP9, thrombin, and trypsin-1. Rather than representing the sequence pattern around the potential cleavage site through a series of flags with each flag representing one of the 20 standard amino acids, we first represent each amino acid by its calculated properties. For these calculated properties, we use validated cheminformatic descriptors, such as molecular weight, logP, and polar surface area, of the individual amino acids. Finally, the cleavage site-specific descriptors are calculated through various combinations of the individual amino acid descriptors for the residues surrounding the cleavage site. Some of these combinations do not take into account the location of the residue, as long as it is in a prescribed neighborhood of the potential cleavage site, whereas others are sensitive to the precise order of the residues in the sequence. The key advantage of this approach is that it allows one to perform meaningful calculations with nonstandard amino acids for which little or no data exists. Finally, using both docking and molecular dynamics simulations, we examine the potential for and limitations of protease crystal structures to impact the design of proteolytically stable peptides.

Caspase-3 and caspase-6 cleave STAT1 in leukemic cells

Signal Transducer and Activator of Transcription-1 (STAT1) is phosphorylated upon interferon (IFN) stimulation, which can restrict cell proliferation and survival. Nevertheless, in some cancers STAT1 can act in an anti-apoptotic manner. Moreover, certain malignancies are characterized by the overexpression and constitutive activation of STAT1. Here, we demonstrate that the treatment of transformed hematopoietic cells with epigenetic drugs belonging to the class of histone deacetylase inhibitors (HDACi) leads to the cleavage of STAT1 at multiple sites by caspase-3 and caspase-6. This process does not occur in solid tumor cells, normal hematopoietic cells, and leukemic cells that underwent granulocytic or monocytic differentiation. STAT1 cleavage was studied under cell free conditions with purified STAT1 and a set of candidate caspases as well as with mass spectrometry. These assays indicate that unmodified STAT1 is cleaved at multiple sites by caspase-3 and caspase-6. Our study shows that STAT1 is targeted by caspases in malignant undifferentiated hematopoietic cells. This observation may provide an explanation for the selective toxicity of HDACi against rapidly proliferating leukemic cells.

Caspase cleavage sites in the human proteome: CaspDB, a database of predicted substrates

Caspases are enzymes belonging to a conserved family of cysteine-dependent aspartic-specific proteases that are involved in vital cellular processes and play a prominent role in apoptosis and inflammation. Determining all relevant protein substrates of caspases remains a challenging task. Over 1500 caspase substrates have been discovered in the human proteome according to published data and new substrates are discovered on a daily basis. To aid the discovery process we developed a caspase cleavage prediction method using the recently published curated MerCASBA database of experimentally determined caspase substrates and a Random Forest classification method. On both internal and external test sets, the ranking of predicted cleavage positions is superior to all previously developed prediction methods. The in silico predicted caspase cleavage positions in human proteins are available from a relational database: CaspDB. Our database provides information about potential cleavage sites in a verified set of all human proteins collected in Uniprot and their orthologs, allowing for tracing of cleavage motif conservation. It also provides information about the positions of disease-annotated single nucleotide polymorphisms, and posttranslational modifications that may modulate the caspase cleaving efficiency.

Hantaviruses: past, present and future

ABSTRACT: 

Hantaviruses productively infect endothelial cells in their rodent reservoirs and humans, but the infection only causes disease in humans – hantavirus pulmonary syndrome and hemorrhagic fever with renal syndrome. Despite the enormous progress that has been made in understanding the pathogenesis and immune responses of hantavirus infection, there is a large gap in our molecular-based knowledge of hantaviral proteins in their structures, functions and the mechanisms that facilitate their entry, replication and assembly. Importantly, we know little about the specific viral determinants and viral protein–host interactions that drive differences noted in immune responses between the reservoir and humans. This review discusses our current understanding and future work needed for unraveling the biology of these viruses in their reservoirs and in humans.

Sequence-derived structural features driving proteolytic processing

Proteolytic signaling, or regulated proteolysis, is an essential part of many important pathways such as Notch, Wnt, and Hedgehog. How the structure of the cleaved substrate regions influences the efficacy of proteolytic processing remains underexplored. Here, we analyzed the relative importance in proteolysis of various structural features derived from substrate sequences using a dataset of more than 5000 experimentally verified proteolytic events captured in CutDB. Accessibility to the solvent was recognized as an essential property of a proteolytically processed polypeptide chain. Proteolytic events were found nearly uniformly distributed among three types of secondary structure, although with some enrichment in loops. Cleavages in α-helices were found to be relatively abundant in regions apparently prone to unfolding, while cleavages in β-structures tended to be located at the periphery of β-sheets. Application of the same statistical procedures to proteolytic events divided into separate sets according to the catalytic classes of proteases proved consistency of the results and confirmed that the structural mechanisms of proteolysis are universal. The estimated prediction power of sequence-derived structural features, which turned out to be sufficiently high, presents a rationale for their use in bioinformatic prediction of proteolytic events.

Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets

MOTIVATION

Caspases and granzyme B (GrB) are important proteases involved in fundamental cellular processes and play essential roles in programmed cell death, necrosis and inflammation. Although a number of substrates for both types have been experimentally identified, the complete repertoire of caspases and granzyme B substrates remained to be fully characterized. Accordingly, systematic bioinformatics studies of known cleavage sites may provide important insights into their substrate specificity and facilitate the discovery of novel substrates.

RESULTS

We develop a new bioinformatics tool, termed Cascleave 2.0, which builds on previous success of the Cascleave tool for predicting generic caspase cleavage sites. It can be efficiently used to predict potential caspase-specific cleavage sites for the human caspase-1, 3, 6, 7, 8 and GrB. In particular, we integrate heterogeneous sequence and protein functional information from various sources to improve the prediction accuracy of Cascleave 2.0. During classification, we use both maximum relevance minimum redundancy and forward feature selection techniques to quantify the relative contribution of each feature to prediction and thus remove redundant as well as irrelevant features. A systematic evaluation of Cascleave 2.0 using the benchmark data and comparison with other state-of-the-art tools using independent test data indicate that Cascleave 2.0 outperforms other tools on protease-specific cleavage site prediction of caspase-1, 3, 6, 7 and GrB. Cascleave 2.0 is anticipated to be used as a powerful tool for identifying novel substrates and cleavage sites of caspases and GrB and help understand the functional roles of these important proteases in human proteolytic cascades.

AVAILABILITY AND IMPLEMENTATION

http://www.structbioinfor.org/cascleave2/.

Caspase-1 promotes Epstein-Barr virus replication by targeting the large tegument protein deneddylase to the nucleus of productively infected cells

The large tegument proteins of herpesviruses contain N-terminal cysteine proteases with potent ubiquitin and NEDD8-specific deconjugase activities, but the function of the enzymes during virus replication remains largely unknown. Using as model BPLF1, the homologue encoded by Epstein-Barr virus (EBV), we found that induction of the productive virus cycle does not affect the total level of ubiquitin-conjugation but is accompanied by a BPLF1-dependent decrease of NEDD8-adducts and accumulation of free NEDD8. Expression of BPLF1 promotes cullin degradation and the stabilization of cullin-RING ligases (CRLs) substrates in the nucleus, while cytoplasmic CRLs and their substrates are not affected. The inactivation of nuclear CRLs is reversed by the N-terminus of CAND1, which inhibits the binding of BPLF1 to cullins and prevents efficient viral DNA replication. Targeting of the deneddylase activity to the nucleus is dependent on processing of the catalytic N-terminus by caspase-1. Inhibition of caspase-1 severely impairs viral DNA synthesis and the release of infectious virus, pointing a previously unrecognized role of the cellular response to danger signals triggered by EBV reactivation in promoting virus replication.

Release of an ~55kDa fragment containing the actin-binding domain of β-spectrin by caspase-8 during FND-induced apoptosis depends on the presence of protein 4.1

Analyses of the status of the membrane spectrin-based skeleton during fludarabine/mitoxantrone/dexamethasone-induced (FND-induced) apoptosis revealed proteolytic degradation of β-spectrin, with the prevalent appearance of a specific fragment with a molecular weight of ~55kDa, containing the actin-binding domain (ABD). Appearance of this fragment was dependent on induction of apoptosis. In silico proteolysis of spectrin identified caspase-8 as a candidate protease responsible for the generation of this ~55kDa ABD-containing fragment. Analyses of spectrin and procaspase-8 localization during early apoptosis indicated temporary (<30-120min) submembranous colocalization of both proteins. Proteolytic release of the N-terminal ~55kDa fragment of purified spectrin by recombinant caspase-8 does not occur in normal cells, but does occur in isolated membrane, such as red blood cell ghosts, or in vitro in the presence of apoptotic cell extracts. Surprisingly, proteolysis of purified spectrin by recombinant caspase-8 resulted in the generation of the ~55kDa fragment only in the presence of purified protein 4.1. This suggests that only the appropriate spatial arrangement of the spectrin-based membrane skeleton or the appropriate conformational state of spectrin, which are both known to be induced by 4.1, can sensitize β-spectrin to cleavage by caspase-8 at the N-terminal ABD-containing region.

PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites

The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using machine learning techniques. It is freely available at http://lightning.med.monash.edu.au/PROSPER/.

Low prevalence of autoantibodies to CENP-H, -I, -K, -L, -M, -N, -T and -U in a Japanese cohort of anti-centromere positive samples

OBJECTIVE

The constituents of the centromere region, centromere protein (CENP)-A, -B, and -C, are mainly targeted by anticentromere antibodies (ACA). Many other proteins also assemble around CENP-A nucleosomes in interphase nuclei to form the interphase centromere complex (ICEN). CENP-H, -I, -K, -L, -M, -N, -T, and -U have been reported as the constitutive components of ICEN. In this study, we examined the reactivities of ACA to the 8 CENPs for the purpose of investigating their autoantigenicity.

METHODS

Sera from 95 patients with ACA were tested by western blotting (WB) and enzyme-linked immunosorbent assay (ELISA) with the recombinant C-terminal of CENP-B (Ct-CENP-B). Next, the sera were examined for autoantibodies against the 8 CENPs by WB with each recombinant protein. Furthermore, the coiled-coil motifs and granzyme B (GB) cleavage for various CENPs were analyzed with computer tools.

RESULTS

Out of 95 ACA-positive sera, 85 and 93 sera were positive for anti-Ct-CENP-B antibodies in WB and in ELISA, respectively. In WB using the 8 CENPs, no sera reacted to any other 7 CENPs, except 1 serum, which reacted weakly to CENP-T. We were unable to find any obvious relationships between the autoantigenicity of CENPs and coiled-coil-forming probabilities or potential substrates for GB.

CONCLUSION

This study demonstrates that ACA rarely target the 8 CENPs, in contrast to CENP-B. Protein structures might not contribute in a major way to the autoantigenicity of CENPs.

Cleavage of the Junin virus nucleoprotein serves a decoy function to inhibit the induction of apoptosis during infection

The regulation of apoptosis during infection is an important factor for host survival and, in some cases, also for the virus life cycle. At the same time, mechanisms to prevent the induction of apoptosis have been observed in numerous viral pathogens, but until now the role of apoptosis during arenavirus infection has not been investigated. Junin virus (JUNV) belongs to the New World arenavirus serogroup of the Arenaviridae and is the causative agent of Argentine hemorrhagic fever. We have demonstrated that infection with JUNV in cell culture does not induce apoptosis but leads to cleavage of the nucleoprotein (NP) into discrete products resembling caspase cleavage events. Similar specific NP degradation patterns were also observed in NP-transfected cell lines, and a closer examination of the sequence of NP showed several putative caspase cleavage motifs. Point mutations that abolished these cleavage motifs were consistent with the loss of certain cleavage products. Consistent with these data, further studies showed that treatment with a caspase inhibitor also reduced NP cleavage, indicating that the observed cleavage events were occurring as a result of caspase activity with NP as a substrate. Finally, we showed that expression of NP suppresses the cleavage of caspase 3 in cells treated with an apoptosis activator. Based on these findings, we propose that NP functions as a decoy substrate for caspase cleavage in order to inhibit the induction of apoptosis in JUNV-infected cells.

High resolution quantitative proteomics of HeLa cells protein species using stable isotope labeling with amino acids in cell culture(SILAC), two-dimensional gel electrophoresis(2DE) and nano-liquid chromatograpohy coupled to an LTQ-OrbitrapMass spectrometer

The proteomics field has shifted over recent years from two-dimensional gel electrophoresis (2-DE)-based approaches to SDS-PAGE or gel-free workflows because of the tremendous developments in isotopic labeling techniques, nano-liquid chromatography, and high-resolution mass spectrometry. However, 2-DE still offers the highest resolution in protein separation. Therefore, we combined stable isotope labeling with amino acids in cell culture of controls and apoptotic HeLa cells with 2-DE and the subsequent analysis of tryptic peptides via nano-liquid chromatography coupled to an LTQ-Orbitrap mass spectrometer to obtain quantitative data using the methods with the highest resolving power on all levels of the proteomics workflow. More than 1,200 proteins with more than 2,700 protein species were identified and quantified from 816 Coomassie Brilliant Blue G-250 stained 2-DE spots. About half of the proteins were identified and quantified only in single 2-DE spots. The majority of spots revealed one to five proteins; however, in one 2-DE spot, up to 23 proteins were identified. Only half of the 2-DE spots represented a dominant protein with more than 90% of the whole protein amount. Consequently, quantification based on staining intensities in 2-DE gels would in approximately half of the spots be imprecise, and minor components could not be quantified. These problems are circumvented by quantification using stable isotope labeling with amino acids in cell culture. Despite challenges, as shown in detail for lamin A/C and vimentin, the quantitative changes of protein species can be detected. The combination of 2-DE with high-resolution nano-liquid chromatography-mass spectrometry allowed us to identify proteomic changes in apoptotic cells that would be unobservable using any of the other previously employed proteomic workflows.

Prediction of protein cleavage site with feature selection by random forest

Proteinases play critical roles in both intra and extracellular processes by binding and cleaving their protein substrates. The cleavage can either be non-specific as part of degradation during protein catabolism or highly specific as part of proteolytic cascades and signal transduction events. Identification of these targets is extremely challenging. Current computational approaches for predicting cleavage sites are very limited since they mainly represent the amino acid sequences as patterns or frequency matrices. In this work, we developed a novel predictor based on Random Forest algorithm (RF) using maximum relevance minimum redundancy (mRMR) method followed by incremental feature selection (IFS). The features of physicochemical/biochemical properties, sequence conservation, residual disorder, amino acid occurrence frequency, secondary structure and solvent accessibility were utilized to represent the peptides concerned. Here, we compared existing prediction tools which are available for predicting possible cleavage sites in candidate substrates with ours. It is shown that our method makes much more reliable predictions in terms of the overall prediction accuracy. In addition, this predictor allows the use of a wide range of proteinases.

In silico prediction of the granzyme B degradome

BACKGROUND

Granzyme B is a serine protease which cleaves at unique tetrapeptide sequences. It is involved in several signaling cross-talks with caspases and functions as a pivotal mediator in a broad range of cellular processes such as apoptosis and inflammation. The granzyme B degradome constitutes proteins from a myriad of functional classes with many more expected to be discovered. However, the experimental discovery and validation of bona fide granzyme B substrates require time consuming and laborious efforts. As such, computational methods for the prediction of substrates would be immensely helpful.

RESULTS

We have compiled a dataset of 580 experimentally verified granzyme B cleavage sites and found distinctive patterns of residue conservation and position-specific residue propensities which could be useful for in silico prediction using machine learning algorithms. We trained a series of support vector machines (SVM) classifiers employing Bayes Feature Extraction to predict cleavage sites using sequence windows of diverse lengths and compositions. The SVM classifiers achieved accuracy and AROC scores between 71.00% to 86.50% and 0.78 to 0.94 respectively on independent test sets. We have applied our prediction method on the Chikungunya viral proteome and identified several regulatory domains of viral proteins to be potential sites of granzyme B cleavage, suggesting direct antiviral activity of granzyme B during host-viral innate immune responses.

CONCLUSIONS

We have compiled a comprehensive dataset of granzyme B cleavage sites and developed an accurate SVM-based prediction method utilizing Bayes Feature Extraction to identify novel substrates of granzyme B in silico. The prediction server is available online, together with reference datasets and supplementary materials.

Developing a powerful in silico tool for the discovery of novel caspase-3 substrates: a preliminary screening of the human proteome

Background

Caspases are a family of cysteinyl proteases that regulate apoptosis and other biological processes. Caspase-3 is considered the central executioner member of this family with a wide range of substrates. Identification of caspase-3 cellular targets is crucial to gain further insights into the cellular mechanisms that have been implicated in various diseases including: cancer, neurodegenerative, and immunodeficiency diseases. To date, over 200 caspase-3 substrates have been identified experimentally. However, many are still awaiting discovery.

Results

Here, we describe a powerful bioinformatics tool that can predict the presence of caspase-3 cleavage sites in a given protein sequence using a Position-Specific Scoring Matrix (PSSM) approach. The present tool, which we call CAT3, was built using 227 confirmed caspase-3 substrates that were carefully extracted from the literature. Assessing prediction accuracy using 10 fold cross validation, our method shows AUC (area under the ROC curve) of 0.94, sensitivity of 88.83%, and specificity of 89.50%. The ability of CAT3 in predicting the precise cleavage site was demonstrated in comparison to existing state-of-the-art tools. In contrast to other tools which were trained on cleavage sites of various caspases as well as other similar proteases, CAT3 showed a significant decrease in the false positive rate. This cost effective and powerful feature makes CAT3 an ideal tool for high-throughput screening to identify novel caspase-3 substrates.

The developed tool, CAT3, was used to screen 13,066 human proteins with assigned gene ontology terms. The analyses revealed the presence of many potential caspase-3 substrates that are not yet described. The majority of these proteins are involved in signal transduction, regulation of cell adhesion, cytoskeleton organization, integrity of the nucleus, and development of nerve cells.

Conclusions

CAT3 is a powerful tool that is a clear improvement over existing similar tools, especially in reducing the false positive rate. Human proteome screening, using CAT3, indicate the presence of a large number of possible caspase-3 substrates that exceed the anticipated figure. In addition to their involvement in various expected functions such as cytoskeleton organization, nuclear integrity and adhesion, a large number of the predicted substrates are remarkably associated with the development of nerve tissues.

Mass spectrometry-based proteomics strategies for protease cleavage site identification

Protease-catalyzed hydrolysis of peptide bonds is one of the most pivotal post-translational modifications fulfilling manifold functions in the regulation of cellular processes. Therefore, dysregulation of proteolytic reactions plays a central role in many pathophysiological events. For this reason, understanding the molecular mechanisms in proteolytic reactions, in particular the knowledge of proteases involved in complex processes, expression levels and activity of protease and knowledge of the targeted substrates are an indispensable prerequisite for targeted drug development. The present review focuses on mass spectrometry-based proteomic methods for the analysis of protease cleavage sites, including the identification of the hydrolyzed bonds as well as of the surrounding sequence. Peptide- and protein-centric approaches and bioinformatic tools for experimental data interpretation will be presented and the major advantages and drawbacks of the different approaches will be addressed. The recent applications of these approaches for the analysis of biological function of different protease classes and potential future directions will be discussed.

A review of statistical methods for prediction of proteolytic cleavage

A fundamental component of systems biology, proteolytic cleavage is involved in nearly all aspects of cellular activities: from gene regulation to cell lifecycle regulation. Current sequencing technologies have made it possible to compile large amount of cleavage data and brought greater understanding of the underlying protein interactions. However, the practical impossibility to exhaustively retrieve substrate sequences through experimentation alone has long highlighted the need for efficient computational prediction methods. Such methods must be able to quickly mark substrate candidates and putative cleavage sites for further analysis. Available methods and expected reliability depend heavily on the type and complexity of proteolytic action, as well as the availability of well-labelled experimental data sets: factors varying greatly across enzyme families. For this review, we chose to give a quick overview of the general issues and challenges in cleavage prediction methods followed by a more in-depth presentation of major techniques and implementations, with a focus on two particular families of cysteine proteases: caspases and calpains. Through their respective differences in proteolytic specificity (high for caspases, broader for calpains) and data availability (much lower for calpains), we aimed to illustrate the strengths and limitations of techniques ranging from position-based matrices and decision trees to more flexible machine-learning methods such as hidden Markov models and Support Vector Machines. In addition to a technical overview for each family of algorithms, we tried to provide elements of evaluation and performance comparison across methods.

ApoptoProteomics, an integrated database for analysis of proteomics data obtained from apoptotic cells

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no.

Caspase substrates and cellular remodeling

The caspases are unique proteases that mediate the major morphological changes of apoptosis and various other cellular remodeling processes. As we catalog and study the myriad proteins subject to cleavage by caspases, we are beginning to appreciate the full functional repertoire of these enzymes. Here, we examine current knowledge about caspase cleavages: what kinds of proteins are cut, in what contexts, and to what end. After reviewing basic caspase biology, we describe the technologies that enable high-throughput caspase substrate discovery and the datasets they have yielded. We discuss how caspases recognize their substrates and how cleavages are conserved among different metazoan organisms. Rather than comprehensively reviewing all known substrates, we use examples to highlight some functional impacts of caspase cuts during apoptosis and differentiation. Finally, we discuss the roles caspase substrates can play in medicine. Though great progress has been made in this field, many important areas still await exploration.

Calpains: an elaborate proteolytic system

Calpain is an intracellular Ca(2+)-dependent cysteine protease (EC 3.4.22.17; Clan CA, family C02). Recent expansion of sequence data across the species definitively shows that calpain has been present throughout evolution; calpains are found in almost all eukaryotes and some bacteria, but not in archaebacteria. Fifteen genes within the human genome encode a calpain-like protease domain. Interestingly, some human calpains, particularly those with non-classical domain structures, are very similar to calpain homologs identified in evolutionarily distant organisms. Three-dimensional structural analyses have helped to identify calpain's unique mechanism of activation; the calpain protease domain comprises two core domains that fuse to form a functional protease only when bound to Ca(2+)via well-conserved amino acids. This finding highlights the mechanistic characteristics shared by the numerous calpain homologs, despite the fact that they have divergent domain structures. In other words, calpains function through the same mechanism but are regulated independently. This article reviews the recent progress in calpain research, focusing on those studies that have helped to elucidate its mechanism of action. This article is part of a Special Issue entitled: Proteolysis 50 years after the discovery of lysosome.

Structural determinants of limited proteolysis

Limited or regulatory proteolysis plays a critical role in many important biological pathways like blood coagulation, cell proliferation, and apoptosis. A better understanding of mechanisms that control this process is required for discovering new proteolytic events and for developing inhibitors with potential therapeutic value. Two features that determine the susceptibility of peptide bonds to proteolysis are the sequence in the vicinity of the scissile bond and the structural context in which the bond is displayed. In this study, we assessed statistical significance and predictive power of individual structural descriptors and combination thereof for the identification of cleavage sites. The analysis was performed on a data set of >200 proteolytic events documented in CutDB for a variety of mammalian regulatory proteases and their physiological substrates with known 3D structures. The results confirmed the significance and provided a ranking within three main categories of structural features: exposure > flexibility > local interactions. Among secondary structure elements, the largest frequency of proteolytic cleavage was confirmed for loops and lower but significant frequency for helices. Limited proteolysis has lower albeit appreciable frequency of occurrence in certain types of β-strands, which is in contrast with some previous reports. Descriptors deduced directly from the amino acid sequence displayed only marginal predictive capabilities. Homology-based structural models showed a predictive performance comparable to protein substrates with experimentally established structures. Overall, this study provided a foundation for accurate automated prediction of segments of protein structure susceptible to proteolytic processing and, potentially, other post-translational modifications.