Abstract
BackgroundCaspases 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.ResultsIn 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.ConclusionAs 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.
Highlights
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
Based on our analysis on a dataset of 176 experimentally verified caspase substrates, we found that 80% of substrates contain at least one other identical caspase cleavage site sequence which is not reported as a true cleavage site in the literature
When CASVM [25,26] and GraBCas [27] were integrated into the model, prediction results were shown to achieve greater positive predictive values compared to CASVM or GraBCas alone
Summary
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. Much work had been done on the prediction of the substrates of caspases - a unique class of cysteine proteases which function as critical effectors of apoptosis, inflammation and other important cellular processes [2,3,4]. Most of the current approaches for caspase substrates prediction are primarily based on the detection of cleavage sites on proteins using information encoded within the tetrapeptide motifs (reviewed in [8]). While the identification of the specific cleavage site on the primary sequence of a protein is necessary for substrate prediction, it is intuitive that the final proteolytic cleavage of a protein in vivo is contingent on a multitude of other factors in addition to the presence of cleavage sites. It is suggested that the location of cleavage sites is critical for substrate cleavage - a potential cleavage site needs to be located at the surface of the substrate, rather than within the hydrophobic core of the protein, in order to be accessible to the protease active site [24]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
