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Generation of truncated proteoforms in proteolytic networks : modeling and prediction in the protease web Fortelny, Nikolaus

Abstract

Primarily controlled by gene expression and fine-tuned by translation and degradation rates, protein activity is governed by a plethora of post-translation modifications such as phosphorylation and glycosylation, which generate a diversity of protein species and thereby control complex biological phenotypes. Protease processing by proteases is a particular modification leading to the irreversible generation of stable protein truncations. Well understood in examples such as signal- or propeptide removal, recent analyses consistently identify >50% of N-terminal peptides mapping inside the protein sequence as predicted by genomics, indicating an important regulatory role of proteases. All proteins undergo protease cleavage as part of processing or degradation, a second biological process controlled by proteases. Proteases are involved in numerous pathologies and commonly considered as drug targets. However, protease research and drug development is complicated, in part due to widespread crosstalk between proteases. Proteases regulate other proteases through direct cleavage or cleavage of protease inhibitors in a complex network of protease interactions, the protease web. Yet, a comprehensive analysis of the protease web has not been performed, hampering assignment of proteases to clear biological roles, their direct substrates, and protease inhibitor drug targeting. A second problem in the identification of protein processing is the potential confound between protein termini generated by protease processing, alternative splicing, and alternative translation. In this thesis, I computationally analyzed large and diverse datasets of protease interactions and protein truncations to gain insight into complex proteolytic processes and to guide biochemical follow- up experiments. Analyzing protease cleavage, alternative splicing and alternative translation data incorporated into our database TopFIND, I found that protease cleavage and alternative translation likely generate most protein truncations. Combining protease cleavage and inhibition data in a graph model of the protease web, I demonstrated extensive protease crosstalk and then predicted and validated a proteolytic pathway. Finally, investigating strategies for the prediction of protease inhibition, I predicted hundreds of protease-inhibitor interactions, and validated inhibition of kallikrein-5 by serpin B12. This work thus generated predictions for biochemical follow-up as well as important insights into the regulation of biological systems through proteases.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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