Monash Centre for Data Science, Faculty of Information Technology.
Department of Biochemistry and Molecular Biology and Biomedicine Discovery Institute.
Bioinformatics. 2018 Feb 15;34(4):684-687. doi: 10.1093/bioinformatics/btx670.
Proteases are enzymes that specifically cleave the peptide backbone of their target proteins. As an important type of irreversible post-translational modification, protein cleavage underlies many key physiological processes. When dysregulated, proteases' actions are associated with numerous diseases. Many proteases are highly specific, cleaving only those target substrates that present certain particular amino acid sequence patterns. Therefore, tools that successfully identify potential target substrates for proteases may also identify previously unknown, physiologically relevant cleavage sites, thus providing insights into biological processes and guiding hypothesis-driven experiments aimed at verifying protease-substrate interaction. In this work, we present PROSPERous, a tool for rapid in silico prediction of protease-specific cleavage sites in substrate sequences. Our tool is based on logistic regression models and uses different scoring functions and their pairwise combinations to subsequently predict potential cleavage sites. PROSPERous represents a state-of-the-art tool that enables fast, accurate and high-throughput prediction of substrate cleavage sites for 90 proteases.
http://prosperous.erc.monash.edu/.
jiangning.song@monash.edu or geoff.webb@monash.edu or r.pike@latrobe.edu.au.
Supplementary data are available at Bioinformatics online.
蛋白酶是一种特异性切割靶蛋白肽骨架的酶。作为一种重要的不可逆翻译后修饰类型，蛋白质切割是许多关键生理过程的基础。当失调时，蛋白酶的作用与许多疾病有关。许多蛋白酶具有高度特异性，仅切割那些呈现特定氨基酸序列模式的靶底物。因此，成功识别蛋白酶潜在靶底物的工具也可以识别以前未知的、生理相关的切割位点，从而深入了解生物学过程，并指导基于假设的实验，以验证蛋白酶-底物相互作用。在这项工作中，我们提出了 PROSPERous，这是一种用于在底物序列中快速预测蛋白酶特异性切割位点的工具。我们的工具基于逻辑回归模型，并使用不同的评分函数及其两两组合来预测潜在的切割位点。PROSPERous 是一种最先进的工具，可用于快速、准确和高通量地预测 90 种蛋白酶的底物切割位点。
http://prosperous.erc.monash.edu/。
jiangning.song@monash.edu 或 geoff.webb@monash.edu 或 r.pike@latrobe.edu.au。
补充数据可在“Bioinformatics”在线获取。
