Posttranslational modifications that involve either reversible covalent modification of proteins or irreversible proteolysis are central to the regulation of key cellular mechanisms, including apoptosis, cell-cycle regulation and signal transduction. There is mounting evidence suggesting cross-talk between proteases and kinases. For instance: caspases, a class of proteases involved in programmed cell death-apoptosis, cleave a large set of various types of proteins. Simultaneously, kinases restrict caspase activity by phosphorylating their protein substrates in the vicinity of cleavage site. In addition, the caspase cleavage pattern in target proteins may be modified as a result of single nucleotide polymorphisms (SNPs) in the coding gene. This may either create a novel cleavage site, or increase/decrease the cleavage efficiency of a substrate. Such point mutations are often associated with the onset of disease. In this study, we predicted how phosphorylation and SNPs affect known human caspase proteolytic events collected in the CASBAH and Degrabase databases by applying Random Forest caspases' substrates prediction method, as implemented in the CaspDB, and the molecular dynamics free energy simulations approach. Our analysis confirms several experimental observations. Phosphorylation could have both positive or negative regulatory effects depending on its position with respect to the caspase cleavage site. For instance, we demonstrate that phosphorylation at P1' is the most detrimental for proteolytic efficiency of caspases. Phosphorylation at the P2 and P2' positions also negatively affect the cleavage events. In addition, we uncovered SNPs in 11 caspase substrates capable of completely abolishing the cleavage site due to polymorphism at the P1 position. The findings presented here may be useful for determining the link between aberrant proteolysis and disease.
Keywords: Apoptosis; Caspase substrates; Cross-talk between posttranslational modifications; Phosphorylation; Posttranslational modification of proteins; SNPs.