SVM-based prediction of caspase substrate cleavage sites

DiCleave: a deep learning model for predicting human Dicer cleavage sites

BACKGROUND

MicroRNAs (miRNAs) are a class of non-coding RNAs that play a pivotal role as gene expression regulators. These miRNAs are typically approximately 20 to 25 nucleotides long. The maturation of miRNAs requires Dicer cleavage at specific sites within the precursor miRNAs (pre-miRNAs). Recent advances in machine learning-based approaches for cleavage site prediction, such as PHDcleav and LBSizeCleav, have been reported. ReCGBM, a gradient boosting-based model, demonstrates superior performance compared with existing methods. Nonetheless, ReCGBM operates solely as a binary classifier despite the presence of two cleavage sites in a typical pre-miRNA. Previous approaches have focused on utilizing only a fraction of the structural information in pre-miRNAs, often overlooking comprehensive secondary structure information. There is a compelling need for the development of a novel model to address these limitations.

RESULTS

In this study, we developed a deep learning model for predicting the presence of a Dicer cleavage site within a pre-miRNA segment. This model was enhanced by an autoencoder that learned the secondary structure embeddings of pre-miRNA. Benchmarking experiments demonstrated that the performance of our model was comparable to that of ReCGBM in the binary classification tasks. In addition, our model excelled in multi-class classification tasks, making it a more versatile and practical solution than ReCGBM.

CONCLUSIONS

Our proposed model exhibited superior performance compared with the current state-of-the-art model, underscoring the effectiveness of a deep learning approach in predicting Dicer cleavage sites. Furthermore, our model could be trained using only sequence and secondary structure information. Its capacity to accommodate multi-class classification tasks has enhanced the practical utility of our model.

Cleavage-Mediated Regulation of Myd88 Signaling by Inflammasome-Activated Caspase-1

Coordination among multiple signaling pathways ensures an appropriate immune response, where a signaling pathway may impair or augment another signaling pathway. Here, we report a negative feedback regulation of signaling through the key innate immune mediator MyD88 by inflammasome-activated caspase-1. NLRP3 inflammasome activation impaired agonist- or infection-induced TLR signaling and cytokine production through the proteolytic cleavage of MyD88 by caspase-1. Site-specific mutagenesis was used to identify caspase-1 cleavage site within MyD88 intermediary segment. Different cleavage site location within MyD88 defined the functional consequences of MyD88 cleavage between mouse and human cells. LPS/monosodium urate–induced mouse inflammation model corroborated the physiological role of this mechanism of regulation, that could be reversed by chemical inhibition of NLRP3. While Toll/interleukin-1 receptor (TIR) domain released by MyD88 cleavage additionally contributed to the inhibition of signaling, Waldenström’s macroglobulinemia associated MyD88^L265P mutation is able to evade the caspase-1-mediated inhibition of MyD88 signaling through the ability of its TIR^L265P domain to recruit full length MyD88 and facilitate signaling. The characterization of this mechanism reveals an additional layer of innate immunity regulation.

In silico prediction of Severe Acute Respiratory Syndrome Coronavirus 2 main protease cleavage sites

One of the emerging subjects to combat the SARS-CoV-2 virus is to design accurate and efficient drug such as inhibitors against the viral protease to stop the viral spread. In addition to laboratory investigation of the viral protease, which is fundamental, the in silico research of viral protease such as the protease cleavage site prediction is critically important and urgent. However, this problem has yet to be addressed. This article has, for the first time, investigated this problem using the pattern recognition approaches. The article has shown that the pattern recognition approaches incorporating a specially tailored kernel function for dealing with amino acids has the outstanding performance in the accuracy of cleavage site prediction and the discovery of the prototype cleavage peptides.

ReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites

Background

Human dicer is an enzyme that cleaves pre-miRNAs into miRNAs. Several models have been developed to predict human dicer cleavage sites, including PHDCleav and LBSizeCleav. Given an input sequence, these models can predict whether the sequence contains a cleavage site. However, these models only consider each sequence independently and lack interpretability. Therefore, it is necessary to develop an accurate and explainable predictor, which employs relations between different sequences, to enhance the understanding of the mechanism by which human dicer cleaves pre-miRNA.

Results

In this study, we develop an accurate and explainable predictor for human dicer cleavage site – ReCGBM. We design relational features and class features as inputs to a lightGBM model. Computational experiments show that ReCGBM achieves the best performance compared to the existing methods. Further, we find that features in close proximity to the center of pre-miRNA are more important and make a significant contribution to the performance improvement of the developed method.

Conclusions

The results of this study show that ReCGBM is an interpretable and accurate predictor. Besides, the analyses of feature importance show that it might be of particular interest to consider more informative features close to the center of the pre-miRNA in future predictors.

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.

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.

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 .

During Infection, Theiler's Virions Are Cleaved by Caspases and Disassembled into Pentamers

Infected macrophages in spinal cords of mice persistently infected with Theiler's murine encephalomyelitis virus (TMEV) undergo apoptosis, resulting in restricted virus yields, as do infected macrophages in culture. Apoptosis of murine macrophages in culture occurs via the intrinsic pathway later in infection (>10 h postinfection [p.i.]) after maximal virus titers (150 to 200 PFU/cell) have been reached, with loss of most infectious virus (<5 PFU/cell) by 20 to 24 h p.i. Here, we show that BeAn virus RNA replication, translation, polyprotein processing into final protein products, and assembly of protomers and pentamers in infected M1-D macrophages did not differ from those processes in TMEV-infected BHK-21 cells, which undergo necroptosis. However, the initial difference from BHK-21 cell infection was seen at 10 to 12 h p.i., where virions from the 160S peak in sucrose gradients had incompletely processed VP0 (compared to that in infected BHK-21 cells). Thereafter, there was a gradual loss of the 160S virion peak in sucrose gradients, with replacement by a 216S peak that was observed to contain pentamers among lipid debris in negatively stained grids by electron microscopy. After infection or incubation of purified virions with activated caspase-3 in vitro, 13- and 17-kDa capsid peptide fragments were observed and were predicted by algorithms to contain cleavage sites within proteins by cysteine-dependent aspartate-directed proteases. These findings suggest that caspase cleavage of sites in exposed capsid loops of assembled virions occurs contemporaneously with the onset and progression of apoptosis later in the infection.

IMPORTANCE

Theiler's murine encephalomyelitis virus (TMEV) infection in mice results in establishment of virus persistence in the central nervous system and chronic inflammatory demyelinating disease, providing an experimental animal model for multiple sclerosis. Virus persistence takes place primarily in macrophages recruited into the spinal cord that undergo apoptosis and in turn may facilitate viral spread via infected apoptotic blebs. Infection of murine macrophages in culture results in restricted virus yields late in infection. Here it is shown that the early steps of the virus life cycle in infected macrophages in vitro do not differ from these processes in TMEV-infected BHK-21 cells, which undergo necroptosis. However, the findings late in infection suggest that caspases cleave sites in exposed capsid loops and possibly internal sites of assembled virions occurring contemporaneously with onset and progression of apoptosis. Mechanistically, this would explain the dramatic loss in virus yields during TMEV-induced apoptosis and attenuate the virus, enabling persistence.

Unc93b Induces Apoptotic Cell Death and Is Cleaved by Host and Enteroviral Proteases

Unc93b is an endoplasmic reticulum (ER)-resident transmembrane protein that serves to bind and traffic toll-like receptors (TLRs) from the ER to their appropriate subcellular locations for ligand sensing. Because of its role in TLR trafficking, Unc93b is necessary for an effective innate immune response to coxsackievirus B3 (CVB), a positive-sense single stranded RNA virus belonging to the enterovirus family. Here, we show that Unc93b is cleaved by a CVB-encoded cysteine protease (3Cpro) during viral replication. Further, we define a role for Unc93b in the induction of apoptotic cell death and show that expression of wild-type Unc93b, but not a mutant incapable of binding TLRs or exiting the ER (H412R), induces apoptosis. Furthermore, we show that cellular caspases activated during apoptosis directly cleave Unc93b. Interestingly, we show that the 3Cpro- and caspase-mediated cleavage of Unc93b both occur within ten amino acids in the distal N-terminus of Unc93b. Mechanistically, neither caspase-mediated nor 3Cpro-mediated cleavage of Unc93b altered its trafficking function, inhibited its role in facilitating TLR3 or TLR8 signaling, or altered its apoptosis-inducing effects. Taken together, our studies show that Unc93b is targeted by both viral- and host cell-specific proteases and identify a function of Unc93b in the induction of apoptotic cell death.

Caspases shutdown nonsense-mediated mRNA decay during apoptosis

Nonsense-mediated mRNA decay (NMD) is an mRNA surveillance mechanism that plays integral roles in eliminating mRNAs with premature termination codons to prevent the synthesis of truncated proteins that could be pathogenic. One response to the accumulation of detrimental proteins is apoptosis, which involves the activation of enzymatic pathways leading to protein and nucleic acid cleavage and culminating in cell death. It is not clear whether NMD is required to ensure the accurate expression of apoptosis genes or is no longer necessary since cytotoxic proteins are not an issue during cell death. The present study shows that caspases cleave the two NMD factors UPF1 and UPF2 during apoptosis impairing NMD. Our results demonstrate a new regulatory pathway for NMD that occurs during apoptosis and provide evidence for role of the UPF cleaved fragments in apoptosis and NMD inhibition.

Caspase-8-mediated PAR-4 cleavage is required for TNFα-induced apoptosis

The tumor suppressor protein prostate apoptosis response-4 (PAR-4) is silenced in a subset of human cancers and its down-regulation serves as a mechanism for cancer cell survival following chemotherapy. PAR-4 re-expression selectively causes apoptosis in cancer cells but how its pro-apoptotic functions are controlled and executed precisely is currently unknown. We demonstrate here that UV-induced apoptosis results in a rapid caspase-dependent PAR-4 cleavage at EEPD131G, a sequence that was preferentially recognized by caspase-8. To investigate the effect on cell growth for this cleavage event we established stable cell lines that express wild-type-PAR-4 or the caspase cleavage resistant mutant PAR-4 D131G under the control of a doxycycline-inducible promoter. Induction of the wild-type protein but not the mutant interfered with cell proliferation, predominantly through induction of apoptosis. We further demonstrate that TNFα-induced apoptosis leads to caspase-8-dependent PAR-4-cleavage followed by nuclear accumulation of the C-terminal PAR-4 (132-340) fragment, which then induces apoptosis. Taken together, our results indicate that the mechanism by which PAR-4 orchestrates the apoptotic process requires cleavage by caspase-8.

Mutating RBF can enhance its pro-apoptotic activity and uncovers a new role in tissue homeostasis

The tumor suppressor retinoblastoma protein (pRb) is inactivated in a wide variety of cancers. While its role during cell cycle is well characterized, little is known about its properties on apoptosis regulation and apoptosis-induced cell responses. pRb shorter forms that can modulate pRB apoptotic properties, resulting from cleavages at caspase specific sites are observed in several cellular contexts. A bioinformatics analysis showed that a putative caspase cleavage site (TELD) is found in the Drosophila homologue of pRb(RBF) at a position similar to the site generating the p76Rb form in mammals. Thus, we generated a punctual mutant form of RBF in which the aspartate of the TELD site is replaced by an alanine. This mutant form, RBFD253A, conserved the JNK-dependent pro-apoptotic properties of RBF but gained the ability of inducing overgrowth phenotypes in adult wings. We show that this overgrowth is a consequence of an abnormal proliferation in wing imaginal discs, which depends on the JNK pathway activation but not on wingless (wg) ectopic expression. These results show for the first time that the TELD site of RBF could be important to control the function of RBF in tissue homeostasis in vivo.

Enteropathogenic Escherichia coli dynamically regulates EGFR signaling in intestinal epithelial cells

The diarrheagenic pathogen enteropathogenic Escherichia coli (EPEC) dynamically modulates the survival of infected host intestinal epithelial cells. In the initial stages of infection, several prosurvival signaling events are activated in host cells. These include the phosphorylation of epidermal growth factor receptor (EGFR) and the consequent activation of the phosphatidylinositol-3 kinase/Akt pathway. While studying this pathway in infected epithelial cells, we observed EGFR depletion at later stages of infection, followed subsequently by a decrease in phospho-EGFR. EGFR loss was not dependent on receptor phosphorylation, or on canonical proteasome- and lysosome-dependent processes. Although a type III secretion mutant (ΔescN) stimulated EGFR phosphorylation, it failed to induce receptor degradation. To identify the specific EPEC effector molecule(s) that influenced EGFR stability, epithelial cells infected with isogenic mutant EPEC strains were examined. An EPEC ΔespF strain failed to induce EGFR degradation, whereas EPEC ΔespZ accentuated receptor loss in infected cells. Given the known and contrasting effects of EspF and EspZ on caspase activation, and the known role of proteases in cleaving EGFR, we explored the effect of caspase inhibitors on infection-dependent EGFR loss. The pan-caspase inhibitor Q-VD-OPh blocked EPEC-induced EGFR cleavage in a dose-dependent manner. Taken together, our data suggest that EPEC EspF stimulates caspase-dependent EGFR cleavage and loss, whereas EspZ inhibits this process. Whereas EGFR phosphorylation contributes to the survival of host cells early in infection, EspF-driven caspase activation and consequent EGFR loss likely induce a precipitous increase in host cell death later in the infectious process.

The chlamydial protease CPAF: important or not, important for what?

The protease CPAF is only found in Chlamydiales and in at least most bacteria that share with Chlamydia the biphasic life-style in a cytosolic inclusion. CPAF is intriguing: it appears to be secreted from the inclusion across the inclusion membrane into the cytosol. A bacterial protease ravaging in the cytosol of a human cell may cause a plethora of effects. Curiously, very few are known. The current discussion is bogged down by a focus on experimental artifact, while proposed functions of CPAF remain speculative. I here make the attempt to summarize what we know about CPAF.

XPO1 (CRM1) inhibition represses STAT3 activation to drive a survivin-dependent oncogenic switch in triple-negative breast cancer

Inhibition of XPO1 (CRM1)-mediated nuclear export of multiple tumor suppressor proteins has been proposed as a novel cancer therapeutic strategy to turn off oncogenic signals and enhance tumor suppression. Survivin is a multifunctional protein with oncogenic properties when expressed in the cytoplasm that requires the XPO1-RanGTP complex for its nuclear export. We investigated the antitumor mechanisms of the drug-like selective inhibitors of nuclear export (SINE) XPO1 antagonists KPT-185, KPT-251 KPT-276, and KPT-330 in estrogen receptor-positive and triple-negative breast cancer (TNBC) cell lines and xenograft models of human breast tumors. KPT compounds significantly inhibited breast cancer cell growth and induced tumor cell death, both in vitro and in vivo. These drugs initially promoted survivin accumulation within tumor cell nuclei. However, their major in vitro effect was to decrease survivin cytoplasmic protein levels, correlating with the onset of apoptosis. XPO1 inhibition repressed Survivin transcription by inhibiting CREB-binding protein-mediated STAT3 acetylation, and blocking STAT3 binding to the Survivin promoter. In addition, caspase-3 was activated to cleave survivin, rendering it unavailable to bind X-linked inhibitor of apoptosis protein and block the caspase cascade. Collectively, these data demonstrate that XPO1 inhibition by SINE compounds represses STAT3 transactivation to block the selective oncogenic properties of survivin and supports their clinical use in TNBC.

Caspase-like activity during aging and cell death in the toxic dinoflagellate Karenia brevis

The observation of caspase-like activity during cell death has provided a new framework for understanding the evolutionary and ecological contexts of programmed cell death in phytoplankton. However, additional roles for this caspase-like activity, the enzymes responsible, and the targets of this enzyme activity in phytoplankton remain largely undefined. In the present study, the role of caspase-like activity in aging and ROS-mediated cell death were investigated and death programs both dependent on and independent of caspase-like activity were observed in the toxic dinoflagellate, Karenia brevis. The dual use of in situ caspase 3/7 and TUNEL staining identified previously undescribed death-associated morphotypes in K. brevis. In silico motif analysis identified several enzymes with predicted caspase-like activity in the K. brevis transcriptome, although bona fide caspases are absent. Lastly, computational prediction of downstream caspase substrates, using sequence context and predicted secondary structure, identified proteins involved in a wide range of biological processes including regulation of protein turnover, cell cycle progression, lipid metabolism, coenzyme metabolism, apoptotic and autophagic death. To confirm the computational predictions, a short peptide was designed around the predicated caspase cleavage site in a predicted novel K. brevis caspase 3/7-like target, S-adenosylmethionine synthetase (KbAdoMetS). Cleavage of the peptide substrate with recombinant caspase 3 enzyme was determined by MALDI-TOF MS, confirming that KbAdoMetS is indeed a bona fide caspase substrate. These data identify the involvement of caspase-like activity in both aging and cell death in K. brevis and identify novel executioner enzymes and downstream targets that may be important for bloom termination.

Alterations of Ca²⁺-responsive proteins within cholinergic neurons in aging and Alzheimer's disease

The molecular basis of selective neuronal vulnerability in Alzheimer's disease (AD) remains poorly understood. Using basal forebrain cholinergic neurons (BFCNs) as a model and immunohistochemistry, we have demonstrated significant age-related loss of the calcium-binding protein calbindin-D(28K) (CB) from BFCN, which was associated with tangle formation and degeneration in AD. Here, we determined alterations in RNA and protein for CB and the Ca(2+)-responsive proteins Ca(2+)/calmodulin-dependent protein kinase I (CaMKI), growth-associated protein-43 (GAP43), and calpain in the BF. We observed progressive downregulation of CB and CaMKI RNA in laser-captured BFCN in the normal-aged-AD continuum. We also detected progressive loss of CB, CaMKIδ, and GAP43 proteins in BF homogenates in aging and AD. Activated μ-calpain, a calcium-sensitive protease that degrades CaMKI and GAP43, was significantly increased in the normal aged BF and was 10 times higher in AD BF. Overactivation of μ-calpain was confirmed using proteolytic fragments of its substrate spectrin. Substantial age- and AD-related alterations in Ca(2+)-sensing proteins most likely contribute to selective vulnerability of BFCN to degeneration in AD.

Specificity of a protein-protein interface: local dynamics direct substrate recognition of effector caspases

Proteases are prototypes of multispecific protein–protein interfaces. Proteases recognize and cleave protein and peptide substrates at a well-defined position in a substrate binding groove and a plethora of experimental techniques provide insights into their substrate recognition. We investigate the caspase family of cysteine proteases playing a key role in programmed cell death and inflammation, turning caspases into interesting drug targets. Specific ligand binding to one particular caspase is difficult to achieve, as substrate specificities of caspase isoforms are highly similar. In an effort to rationalize substrate specificity of two closely related caspases, we investigate the substrate promiscuity of the effector Caspases 3 and 7 by data mining (cleavage entropy) and by molecular dynamics simulations. We find a strong correlation between binding site rigidity and substrate readout for individual caspase subpockets explaining more stringent substrate readout of Caspase 7 via its narrower conformational space. Caspase 3 subpockets S3 and S4 show elevated local flexibility explaining the more unspecific substrate readout of that isoform in comparison to Caspase 7. We show by in silico exchange mutations in the S3 pocket of the proteases that a proline residue in Caspase 7 contributes to the narrowed conformational space of the binding site. These findings explain the substrate specificities of caspases via a mechanism of conformational selection and highlight the crucial importance of binding site local dynamics in substrate recognition of proteases. Proteins 2014; 82:546–555.

The combination of a histogram-based clustering algorithm and support vector machine for the diagnosis of osteoporosis

Purpose

To prevent low bone mineral density (BMD), that is, osteoporosis, in postmenopausal women, it is essential to diagnose osteoporosis more precisely. This study presented an automatic approach utilizing a histogram-based automatic clustering (HAC) algorithm with a support vector machine (SVM) to analyse dental panoramic radiographs (DPRs) and thus improve diagnostic accuracy by identifying postmenopausal women with low BMD or osteoporosis.

Materials and Methods

We integrated our newly-proposed histogram-based automatic clustering (HAC) algorithm with our previously-designed computer-aided diagnosis system. The extracted moment-based features (mean, variance, skewness, and kurtosis) of the mandibular cortical width for the radial basis function (RBF) SVM classifier were employed. We also compared the diagnostic efficacy of the SVM model with the back propagation (BP) neural network model. In this study, DPRs and BMD measurements of 100 postmenopausal women patients (aged >50 years), with no previous record of osteoporosis, were randomly selected for inclusion.

Results

The accuracy, sensitivity, and specificity of the BMD measurements using our HAC-SVM model to identify women with low BMD were 93.0% (88.0%-98.0%), 95.8% (91.9%-99.7%) and 86.6% (79.9%-93.3%), respectively, at the lumbar spine; and 89.0% (82.9%-95.1%), 96.0% (92.2%-99.8%) and 84.0% (76.8%-91.2%), respectively, at the femoral neck.

Conclusion

Our experimental results predict that the proposed HAC-SVM model combination applied on DPRs could be useful to assist dentists in early diagnosis and help to reduce the morbidity and mortality associated with low BMD and osteoporosis.

SVM-based prediction of the calpain degradome using Bayes Feature Extraction

Calpains belong to a family of calcium-dependent cysteine proteases which are implicated in a myriad of pathologies such as cancer and neurodegeneration. Despite extensive experimental studies on these proteases, our knowledge of the calpain degradome is still limited. Using a dataset of 341 unique, experimentally verified calpain cleavage sites, we conducted extensive sequence analyses and discovered novel residue propensities in the region flanking the cleavage site which could be modeled for prediction using machine learning algorithms. We have developed a series of computational models incorporating support vector machines and Bayes Feature Extraction for the prediction of calpain cleavage sites. The best models achieved AROC and accuracy scores ranging from 0.79 to 0.93 and 71% to 86% respectively when tested on independent test sets. We predicted calpain cleavage sites on proteins from the receptor tyrosine kinase family and discovered potential sites of cleavage at critical regulatory domains. The results suggest a novel role of calpains as a direct regulator of receptor tyrosine kinase activity in cell survival and cell death pathways.

Serum markers in small cell lung cancer: opportunities for improvement

Lung cancer is one of the leading causes of death from malignancy worldwide. In particular small cell lung cancers, which comprise about 15-20% of all lung cancers, are extremely aggressive and cure rates are extremely low. Therefore, new treatment modalities are needed and detection at an early stage of disease, as well as adequate monitoring of treatment response is essential in order to improve outcome. In this respect, the use of non-invasive tools for screening and monitoring has gained increasing interest and the clinical applicability of reliable, tumor-related substances that can be detected as tumor markers in easily accessible body fluids is subject of intense investigation. Some of these indicators, such as high LDH levels in serum as a reflection of the disease, have been in use for a long time as a general tumor marker. To allow for improved monitoring of the efficacy of new therapeutic modalities and for accurate subtyping, there is a strong need for specific and sensitive markers that are more directly related to the biology and behavior of small cell lung cancer. In this review the current status of these potential markers, like CEA, NSE, ProGRP, CK-BB, SCC, CgA, NCAM and several cytokeratins will be critically analyzed with respect to their performance in blood based assays. Based on known cleavage sites for cytoplasmic and extracellular proteases, a prediction of stable fragments can be obtained and used for optimal test design. Furthermore, insight into the synthesis of specific splice variants and neo-epitopes resulting from protein modification and cleavage, offers further opportunities for improvement of tumor assays. Finally, we discuss the possibility that detection of SCLC related autoantibodies in paraneoplastic disease can be used as a very early indicator of SCLC.

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/.

Anti-apoptotic role of caspase-cleaved GAB1 adaptor protein in hepatocyte growth factor/scatter factor-MET receptor protein signaling

The GRB2-associated binder 1 (GAB1) docking/scaffold protein is a key mediator of the MET-tyrosine kinase receptor activated by hepatocyte growth factor/scatter factor (HGF/SF). Activated MET promotes recruitment and tyrosine phosphorylation of GAB1, which in turn recruits multiple proteins and mediates MET signaling leading to cell survival, motility, and morphogenesis. We previously reported that, without its ligand, MET is a functional caspase target during apoptosis, allowing the generation of a p40-MET fragment that amplifies apoptosis. In this study we established that GAB1 is also a functional caspase target by evidencing a caspase-cleaved p35-GAB1 fragment that contains the MET binding domain. GAB1 is cleaved by caspases before MET, and the resulting p35-GAB1 fragment is phosphorylated by MET upon HGF/SF binding and can interact with a subset of GAB1 partners, PI3K, and GRB2 but not with SHP2. This p35-GAB1 fragment favors cell survival by maintaining HGF/SF-induced MET activation of AKT and by hindering p40-MET pro-apoptotic function. These data demonstrate an anti-apoptotic role of caspase-cleaved GAB1 in HGF/SF-MET signaling.

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.

Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system

Background

Early diagnosis of osteoporosis can potentially decrease the risk of fractures and improve the quality of life. Detection of thin inferior cortices of the mandible on dental panoramic radiographs could be useful for identifying postmenopausal women with low bone mineral density (BMD) or osteoporosis. The aim of our study was to assess the diagnostic efficacy of using kernel-based support vector machine (SVM) learning regarding the cortical width of the mandible on dental panoramic radiographs to identify postmenopausal women with low BMD.

Methods

We employed our newly adopted SVM method for continuous measurement of the cortical width of the mandible on dental panoramic radiographs to identify women with low BMD or osteoporosis. The original X-ray image was enhanced, cortical boundaries were determined, distances among the upper and lower boundaries were evaluated and discrimination was performed by a radial basis function. We evaluated the diagnostic efficacy of this newly developed method for identifying women with low BMD (BMD T-score of -1.0 or less) at the lumbar spine and femoral neck in 100 postmenopausal women (≥50 years old) with no previous diagnosis of osteoporosis. Sixty women were used for system training, and 40 were used in testing.

Results

The sensitivity and specificity using RBF kernel-SVM method for identifying women with low BMD were 90.9% [95% confidence interval (CI), 85.3-96.5] and 83.8% (95% CI, 76.6-91.0), respectively at the lumbar spine and 90.0% (95% CI, 84.1-95.9) and 69.1% (95% CI, 60.1-78.6), respectively at the femoral neck. The sensitivity and specificity for identifying women with low BMD at either the lumbar spine or femoral neck were 90.6% (95% CI, 92.0-100) and 80.9% (95% CI, 71.0-86.9), respectively.

Conclusion

Our results suggest that the newly developed system with the SVM method would be useful for identifying postmenopausal women with low skeletal BMD.

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.

Caspase-8-mediated cleavage inhibits IRF-3 protein by facilitating its proteasome-mediated degradation

Interferon regulatory factor 3 (IRF-3) plays a central role in inducing the expression of cellular antiviral genes, including the interferon-β gene, in response to Pattern Recognition Receptors. IRF-3 is targeted for proteasome-mediated degradation, which modulates the strength and duration of the innate immune responses that depend on it. We have found that caspase-8, which is activated by cytosolic RIG-I-dependent signaling, catalyzes an essential intermediate step in the ubiquitination and proteasome-mediated degradation of IRF-3. Mutation of a consensus cleavage site within IRF-3 generates a form that is not cleaved by caspase-8 and that is protected from ubiquitination and degradation. An in vitro assay confirms the direct action of caspase-8 cleavage on IRF-3. We also show that caspase-8-mediated cleavage of IRF-3 helps to modulate dsRNA-dependent gene induction.

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.

Bioinformatic approaches for predicting substrates of proteases

Proteases have central roles in "life and death" processes due to their important ability to catalytically hydrolyze protein substrates, usually altering the function and/or activity of the target in the process. Knowledge of the substrate specificity of a protease should, in theory, dramatically improve the ability to predict target protein substrates. However, experimental identification and characterization of protease substrates is often difficult and time-consuming. Thus solving the "substrate identification" problem is fundamental to both understanding protease biology and the development of therapeutics that target specific protease-regulated pathways. In this context, bioinformatic prediction of protease substrates may provide useful and experimentally testable information about novel potential cleavage sites in candidate substrates. In this article, we provide an overview of recent advances in developing bioinformatic approaches for predicting protease substrate cleavage sites and identifying novel putative substrates. We discuss the advantages and drawbacks of the current methods and detail how more accurate models can be built by deriving multiple sequence and structural features of substrates. We also provide some suggestions about how future studies might further improve the accuracy of protease substrate specificity prediction.

Prediction of regulatory interactions in Arabidopsis using gene-expression data and support vector machines

Identification of regulatory relationships between transcription factors (TFs) and their targets is a central problem in post-genomic biology. In this paper, we apply an approach based on the support vector machine (SVM) and gene-expression data to predict the regulatory interactions in Arabidopsis. A set of 125 experimentally validated TF-target interactions and 750 negative regulatory gene pairs are collected as the training data. Their expression profiles data at 79 experimental conditions are fed to the SVM to perform the prediction. Through the jackknife cross-validation test, we find that the overall prediction accuracy of our approach achieves 88.68%. Our approach could help to widen the understanding of Arabidopsis gene regulatory scheme and may offer a cost-effective alternative to construct the gene regulatory network.

Induction of Ca²+-driven apoptosis in chronic lymphocytic leukemia cells by peptide-mediated disruption of Bcl-2-IP3 receptor interaction

Bcl-2 contributes to the pathophysiology and therapeutic resistance of chronic lymphocytic leukemia (CLL). Therefore, developing inhibitors of this protein based on a thorough understanding of its mechanism of action is an active and promising area of inquiry. One approach centers on agents (eg, ABT-737) that compete with proapoptotic members of the Bcl-2 protein family for binding in the hydrophobic groove formed by the BH1-BH3 domains of Bcl-2. Another region of Bcl-2, the BH4 domain, also contributes to the antiapoptotic activity of Bcl-2 by binding to the inositol 1,4,5-trisphosphate receptor (IP₃R) Ca²(+) channel, inhibiting IP(3)-dependent Ca²(+) release from the endoplasmic reticulum. We report that a novel synthetic peptide, modeled after the Bcl-2-interacting site on the IP₃R, binds to the BH4 domain of Bcl-2 and functions as a competitive inhibitor of the Bcl-2-IP₃R interaction. By disrupting the Bcl-2-IP₃R interaction, this peptide induces an IP₃R-dependent Ca²(+) elevation in lymphoma and leukemia cell lines and in primary CLL cells. The Ca²(+) elevation evoked by this peptide induces apoptosis in CLL cells, but not in normal peripheral blood lymphocytes, suggesting the involvement of the Bcl-2-IP₃R interaction in the molecular mechanism of CLL and indicating the potential merit of targeting this interaction therapeutically.

Cellular inhibitor of apoptosis 1 (cIAP-1) degradation by caspase 8 during TNF-related apoptosis-inducing ligand (TRAIL)-induced apoptosis

TNF-related apoptosis-inducing ligand (TRAIL) is a potential chemotherapeutic agent with high selectivity for malignant cells. Many tumors, however, are resistant to TRAIL cytotoxicity. Although cellular inhibitors of apoptosis 1 and 2 (cIAP-1 and -2) are often over-expressed in cancers, their role in mediating TRAIL resistance remains unclear. Here, we demonstrate that TRAIL-induced apoptosis of liver cancer cells is associated with degradation of cIAP-1 and X-linked IAP (XIAP), whereas cIAP-2 remains unchanged. Lower concentrations of TRAIL causing minimal or no apoptosis do not alter cIAP-1 or XIAP protein levels. Silencing of cIAP-1 expression, but not XIAP or cIAP-2, as well as co-treatment with a second mitochondrial activator of caspases (SMAC) mimetic (which results in rapid depletion of cIAP-1), sensitizes the cells to TRAIL. TRAIL-induced loss of cIAP-1 and XIAP requires caspase activity. In particular, caspase 8 knockdown stabilizes both cIAP-1 and XIAP, while caspase 9 knockdown prevents XIAP, but not cIAP-1 degradation. Cell-free experiments confirmed cIAP-1 is a substrate for caspase 8, with likely multiple cleavage sites. These results suggest that TRAIL-mediated apoptosis proceeds through caspase 8-dependent degradation of cIAP-1. Targeted depletion of cIAP-1 by SMAC mimetics in conjunction with TRAIL may be beneficial for the treatment of human hepatobiliary malignancies.

Ultraviolet B radiation regulates cysteine-rich protein 1 in human keratinocytes

BACKGROUND

Cysteine-rich protein 1 (CRP1) is a growth-inhibitory cytoskeletal protein that is induced by ultraviolet (UV) C radiation radiation in fibroblasts. Our aim was to investigate the effects of UV radiation on CRP1 in keratinocytes, the main cell type subjected to UV radiation in the human body.

METHODS

The effects of physiologically relevant doses of UVB radiation on CRP1 protein levels were studied in cultured primary keratinocytes and transformed cell lines (HaCaT, A-431) by immunoblotting. UVB-induced keratinocyte apoptosis was assessed by flow cytometry and monitoring caspase activity. Expression of CRP1 in human skin in vivo was studied by immunohistochemistry in samples of normal skin, actinic keratosis (AK) representing UV-damaged skin and squamous cell carcinoma (SCC), a UV-induced skin cancer.

RESULTS

CRP1 expression increased by UVB radiation in primary but not in immortalized keratinocytes. Upon high, apoptosis-inducing doses of UV radiation, CRP1 was cleaved in a caspase-dependent manner. In normal skin, CRP1 was expressed in smooth muscle cells, vasculature, sweat glands, sebaceous glands and hair root sheath, but very little CRP1 was present in keratinocytes. CRP1 expression was elevated in basal cells in AK but not in SCC.

CONCLUSION

CRP1 expression is regulated by UVB in human keratinocytes, suggesting a role for CRP1 in the phototoxic responses of human skin.

Classification of dengue fever patients based on gene expression data using support vector machines

Background

Symptomatic infection by dengue virus (DENV) can range from dengue fever (DF) to dengue haemorrhagic fever (DHF), however, the determinants of DF or DHF progression are not completely understood. It is hypothesised that host innate immune response factors are involved in modulating the disease outcome and the expression levels of genes involved in this response could be used as early prognostic markers for disease severity.

Methodology/Principal Findings

mRNA expression levels of genes involved in DENV innate immune responses were measured using quantitative real time PCR (qPCR). Here, we present a novel application of the support vector machines (SVM) algorithm to analyze the expression pattern of 12 genes in peripheral blood mononuclear cells (PBMCs) of 28 dengue patients (13 DHF and 15 DF) during acute viral infection. The SVM model was trained using gene expression data of these genes and achieved the highest accuracy of ∼85% with leave-one-out cross-validation. Through selective removal of gene expression data from the SVM model, we have identified seven genes (MYD88, TLR7, TLR3, MDA5, IRF3, IFN-α and CLEC5A) that may be central in differentiating DF patients from DHF, with MYD88 and TLR7 observed to be the most important. Though the individual removal of expression data of five other genes had no impact on the overall accuracy, a significant combined role was observed when the SVM model of the two main genes (MYD88 and TLR7) was re-trained to include the five genes, increasing the overall accuracy to ∼96%.

Conclusions/Significance

Here, we present a novel use of the SVM algorithm to classify DF and DHF patients, as well as to elucidate the significance of the various genes involved. It was observed that seven genes are critical in classifying DF and DHF patients: TLR3, MDA5, IRF3, IFN-α, CLEC5A, and the two most important MYD88 and TLR7. While these preliminary results are promising, further experimental investigation is necessary to validate their specific roles in dengue disease.

Pripper: prediction of caspase cleavage sites from whole proteomes

BACKGROUND

Caspases are a family of proteases that have central functions in programmed cell death (apoptosis) and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several methods developed to predict caspase cleavage sites from individual proteins, but currently none of them can be used to predict caspase cleavage sites from multiple proteins or entire proteomes, or to use several classifiers in combination. The possibility to create a database from predicted caspase cleavage products for the whole genome could significantly aid in identifying novel caspase targets from tandem mass spectrometry based proteomic experiments.

RESULTS

Three different pattern recognition classifiers were developed for predicting caspase cleavage sites from protein sequences. Evaluation of the classifiers with quality measures indicated that all of the three classifiers performed well in predicting caspase cleavage sites, and when combining different classifiers the accuracy increased further. A new tool, Pripper, was developed to utilize the classifiers and predict the caspase cut sites from an arbitrary number of input sequences. A database was constructed with the developed tool, and it was used to identify caspase target proteins from tandem mass spectrometry data from two different proteomic experiments. Both known caspase cleavage products as well as novel cleavage products were identified using the database demonstrating the usefulness of the tool. Pripper is not restricted to predicting only caspase cut sites, but it gives the possibility to scan protein sequences for any given motif(s) and predict cut sites once a suitable cut site prediction model for any other protease has been developed. Pripper is freely available and can be downloaded from http://users.utu.fi/mijopi/Pripper.

CONCLUSIONS

We have developed Pripper, a tool for reading an arbitrary number of proteins in FASTA format, predicting their caspase cleavage sites and outputting the cleaved sequences to a new FASTA format sequence file. We show that Pripper is a valuable tool in identifying novel caspase target proteins from modern proteomics experiments.

Prediction of protease substrates using sequence and structure features

MOTIVATION

Granzyme B (GrB) and caspases cleave specific protein substrates to induce apoptosis in virally infected and neoplastic cells. While substrates for both types of proteases have been determined experimentally, there are many more yet to be discovered in humans and other metazoans. Here, we present a bioinformatics method based on support vector machine (SVM) learning that identifies sequence and structural features important for protease recognition of substrate peptides and then uses these features to predict novel substrates. Our approach can act as a convenient hypothesis generator, guiding future experiments by high-confidence identification of peptide-protein partners.

RESULTS

The method is benchmarked on the known substrates of both protease types, including our literature-curated GrB substrate set (GrBah). On these benchmark sets, the method outperforms a number of other methods that consider sequence only, predicting at a 0.87 true positive rate (TPR) and a 0.13 false positive rate (FPR) for caspase substrates, and a 0.79 TPR and a 0.21 FPR for GrB substrates. The method is then applied to approximately 25 000 proteins in the human proteome to generate a ranked list of predicted substrates of each protease type. Two of these predictions, AIF-1 and SMN1, were selected for further experimental analysis, and each was validated as a GrB substrate.

AVAILABILITY

All predictions for both protease types are publically available at http://salilab.org/peptide. A web server is at the same site that allows a user to train new SVM models to make predictions for any protein that recognizes specific oligopeptide ligands.

Caspase-7 cleavage of Kaposi sarcoma-associated herpesvirus ORF57 confers a cellular function against viral lytic gene expression

Kaposi sarcoma-associated herpesvirus (KSHV) ORF57 is a viral early protein essential for KSHV multiplication. We found that B cells derived from cavity-based B cell lymphoma with lytic KSHV infection display activation of caspase-8 and cleavage of ORF57 in the cytoplasm by caspase-7 at the aspartate residue at position 33 from the N terminus. Caspase-7 cleavage of ORF57 is prevented by pan-caspase inhibitor z-VAD, caspase-3 and caspase-7 inhibitor z-DEVD, and caspase-7 small interfering RNAs. The caspase-7 cleavage site (30)DETD(33) in ORF57 is not cleavable by caspase-3, although both enzymes use DEXD as a common cleavage site. B cells with lytic KSHV infection and caspase-7 activation exhibited a greatly reduced level of ORF57. A majority of the cells expressing active caspase-7 appeared to have no detectable ORF57 and vice versa. Upon cleavage with caspase-7, ORF57 was deficient in promoting the expression of viral lytic genes. Inhibiting caspase-7 cleavage of ORF57 in KSHV(+) BCBL-1 cells by z-VAD, z-DEVD, or caspase-7 small interfering RNA led to increased expression of viral lytic genes and production of cell-free virus particles. Collectively, our data provide the first compelling evidence that caspase cleavage of ORF57 may represent a cellular function against lytic KSHV infection.

Cascleave: towards more accurate prediction of caspase substrate cleavage sites

MOTIVATION

The caspase family of cysteine proteases play essential roles in key biological processes such as programmed cell death, differentiation, proliferation, necrosis and inflammation. The complete repertoire of caspase substrates remains to be fully characterized. Accordingly, systematic computational screening studies of caspase substrate cleavage sites may provide insight into the substrate specificity of caspases and further facilitating the discovery of putative novel substrates.

RESULTS

In this article we develop an approach (termed Cascleave) to predict both classical (i.e. following a P(1) Asp) and non-typical caspase cleavage sites. When using local sequence-derived profiles, Cascleave successfully predicted 82.2% of the known substrate cleavage sites, with a Matthews correlation coefficient (MCC) of 0.667. We found that prediction performance could be further improved by incorporating information such as predicted solvent accessibility and whether a cleavage sequence lies in a region that is most likely natively unstructured. Novel bi-profile Bayesian signatures were found to significantly improve the prediction performance and yielded the best performance with an overall accuracy of 87.6% and a MCC of 0.747, which is higher accuracy than published methods that essentially rely on amino acid sequence alone. It is anticipated that Cascleave will be a powerful tool for predicting novel substrate cleavage sites of caspases and shedding new insights on the unknown caspase-substrate interactivity relationship.

AVAILABILITY

http://sunflower.kuicr.kyoto-u.ac.jp/ approximately sjn/Cascleave/

CONTACT

jiangning.song@med.monash.edu.au; takutsu@kuicr.kyoto-u.ac.jp; james; whisstock@med.monash.edu.au

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A multi-factor model for caspase degradome prediction

BACKGROUND

Caspases belong to a class of cysteine proteases which function as critical effectors in cellular processes such as apoptosis and inflammation by cleaving substrates immediately after unique tetrapeptide sites. With hundreds of reported substrates and many more expected to be discovered, the elucidation of the caspase degradome will be an important milestone in the study of these proteases in human health and disease. Several computational methods for predicting caspase cleavage sites have been developed recently for identifying potential substrates. However, as most of these methods are based primarily on the detection of the tetrapeptide cleavage sites - a factor necessary but not sufficient for predicting in vivo substrate cleavage - prediction outcomes will inevitably include many false positives.

RESULTS

In this paper, we show that structural factors such as the presence of disorder and solvent exposure in the vicinity of the cleavage site are important and can be used to enhance results from cleavage site prediction. We constructed a two-step model incorporating cleavage site prediction and these factors to predict caspase substrates. Sequences are first predicted for cleavage sites using CASVM or GraBCas. Predicted cleavage sites are then scored, ranked and filtered against a cut-off based on their propensities for locating in disordered and solvent exposed regions. Using an independent dataset of caspase substrates, the model was shown to achieve greater positive predictive values compared to CASVM or GraBCas alone, and was able to reduce the false positives pool by up to 13% and 53% respectively while retaining all true positives. We applied our prediction model on the family of receptor tyrosine kinases (RTKs) and highlighted several members as potential caspase targets. The results suggest that RTKs may be generally regulated by caspase cleavage and in some cases, promote the induction of apoptotic cell death - a function distinct from their role as transducers of survival and growth signals.

CONCLUSION

As a step towards the prediction of in vivo caspase substrates, we have developed an accurate method incorporating cleavage site prediction and structural factors. The multi-factor model augments existing methods and complements experimental efforts to define the caspase degradome on the systems-wide basis.

Caspase substrates: easily caught in deep waters?

Caspases are key players in various cellular processes, such as apoptosis, proliferation and differentiation, and in pathological conditions including cancer and inflammation. Although caspases preferentially cleave C-terminal of aspartic acid residues, their action is restricted generally to one or a few sites per protein substrate. Caspase-specific substrate recognition appears to be determined by the substrate sequences adjacent to the scissile bond. Knowledge of these substrates and the generated fragments is crucial for a thorough understanding of the functional implications of caspase-mediated proteolysis. In addition, insight into the cleavage specificity might assist in designing inhibitors that target disease-related caspase activities. Here, we critically review recently published procedures used to generate a proteome-wide view of caspase substrates.

Examining requirement for formation of functional Presenilin proteins and their processing events in vivo

Presenilin (Psn) is a multipass transmembrane protein that functions as the catalytic subunit of gamma-secretase for mediating intramembrane cleavage of type 1 transmembrane proteins. Normally active Psn is in the form of a heterodimer composed by its N-terminal and C-terminal fragments that are generated from a Presenilinase-mediated endoproteolytic cleavage within its large cytosolic loop during assembly of the protease complex. Using the Psn forms that either bypass or disable Presenilinase-mediated endoproteolysis, and a Psn form that has most of the large cytosolic loop deleted, we have established an in vivo system to enable investigations of Psn functional domains in Drosophila. We show that the Presenilinase-mediated endoproteolytic event is not essential for producing Psn activity during animal development, and is regulated by integrity of the large cytosolic loop of Psn in Drosophila. The Psn transgenic flies described here could be applied to a broad range of studies on Psn functioning and its related gamma-secretase activity at any developmental stage.

An in silico strategy identified the target gene candidates regulated by dehydration responsive element binding proteins (DREBs) in Arabidopsis genome

Identification of downstream target genes of stress-relating transcription factors (TFs) is desirable in understanding cellular responses to various environmental stimuli. However, this has long been a difficult work for both experimental and computational practices. In this research, we presented a novel computational strategy which combined the analysis of the transcription factor binding site (TFBS) contexts and machine learning approach. Using this strategy, we conducted a genome-wide investigation into novel direct target genes of dehydration responsive element binding proteins (DREBs), the members of AP2-EREBPs transcription factor super family which is reported to be responsive to various abiotic stresses in Arabidopsis. The genome-wide searching yielded in total 474 target gene candidates. With reference to the microarray data for abiotic stresses-inducible gene expression profile, 268 target gene candidates out of the total 474 genes predicted, were induced during the 24-h exposure to abiotic stresses. This takes about 57% of total predicted targets. Furthermore, GO annotations revealed that these target genes are likely involved in protein amino acid phosphorylation, protein binding and Endomembrane sorting system. The results suggested that the predicted target gene candidates were adequate to meet the essential biological principle of stress-resistance in plants.

Applications of diagonal chromatography for proteome-wide characterization of protein modifications and activity-based analyses

Numerous gel-free proteomics techniques have been reported over the past few years, introducing a move from proteins to peptides as bits of information in qualitative and quantitative proteome studies. Many shotgun proteomics techniques randomly sample thousands of peptides in a qualitative and quantitative manner but overlook the vast majority of protein modifications that are often crucial for proper protein structure and function. Peptide-based proteomic approaches have thus been developed to profile a diverse set of modifications including, but not at all limited, to phosphorylation, glycosylation and ubiquitination. Typical here is that each modification needs a specific, tailor-made analytical procedure. In this minireview, we discuss how one technique - diagonal reverse-phase chromatography - is applied to study two different types of protein modification: protein processing and protein N-glycosylation. Additionally, we discuss an activity-based proteome study in which purine-binding proteins were profiled by diagonal chromatography.

Establishing bioinformatics research in the Asia Pacific

In 1998, the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5^th annual conference of the Asia-Pacific Bioinformatics Network, on Dec. 18–20, 2006 in New Delhi, India, following a series of successful events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand) and Busan (South Korea). This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. It exemplifies a typical snapshot of the growing research excellence in bioinformatics of the region as we embark on a trajectory of establishing a solid bioinformatics research culture in the Asia Pacific that is able to contribute fully to the global bioinformatics community.