Abstract
The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.
Highlights
Ning et al devised a sequence search and alignment algorithm based on the Sequence Search and Alignment by Hashing Algorithm (SSAHA); this method performs three to four times faster than FASTP or BLAST, as it handles searches in databases of gigabyte range[11]
Both calpain-2 and caspase-3 proteases generate signature protein markers that would theoretically be indicative of different types of neural cell injury mechanisms[16,17,18]. These signature markers are fragment proteins or BDPs, resulting from proteases-associated cleavages. Since they are differentiated by their sequence and molecular weight (Mwt) specificity, they are considered unique to each protease with a definitive signature Mwt characterized by a well-defined amino acid sequence
Both calpain-2 and caspase-3 are activated in different modes of neural cell death and; it is essential to characterize their spatio-temporal activation as it is indicative of the injury mechanisms
Summary
Ning et al devised a sequence search and alignment algorithm based on the Sequence Search and Alignment by Hashing Algorithm (SSAHA); this method performs three to four times faster than FASTP or BLAST, as it handles searches in databases of gigabyte range[11]. Both calpain-2 and caspase-3 proteases generate signature protein markers that would theoretically be indicative of different types of neural cell injury mechanisms[16,17,18]. These signature markers are fragment proteins or BDPs, resulting from proteases-associated cleavages. A crucial gene in this context is the TLL1 which encodes a metalloprotease Upon activation, this metalloprotease truncates extracellular substrate proteins in the septum and the resulting BDPs represent putative markers of the disease[23]. The method is applied to calpain-2 and caspase-3 proteases which are associated with the execution phase of both the apoptotic and necrotic cell death, and where the distinction between the two dominated types of cell death is crucial to better reveal the injury mechanisms
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