Department of Information Technology, University of Turku, Turku, Finland.
BMC Bioinformatics. 2010 Jun 15;11:320. doi: 10.1186/1471-2105-11-320.
Caspases are a family of proteases that have central functions in programmed cell death (apoptosis) and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several methods developed to predict caspase cleavage sites from individual proteins, but currently none of them can be used to predict caspase cleavage sites from multiple proteins or entire proteomes, or to use several classifiers in combination. The possibility to create a database from predicted caspase cleavage products for the whole genome could significantly aid in identifying novel caspase targets from tandem mass spectrometry based proteomic experiments.
Three different pattern recognition classifiers were developed for predicting caspase cleavage sites from protein sequences. Evaluation of the classifiers with quality measures indicated that all of the three classifiers performed well in predicting caspase cleavage sites, and when combining different classifiers the accuracy increased further. A new tool, Pripper, was developed to utilize the classifiers and predict the caspase cut sites from an arbitrary number of input sequences. A database was constructed with the developed tool, and it was used to identify caspase target proteins from tandem mass spectrometry data from two different proteomic experiments. Both known caspase cleavage products as well as novel cleavage products were identified using the database demonstrating the usefulness of the tool. Pripper is not restricted to predicting only caspase cut sites, but it gives the possibility to scan protein sequences for any given motif(s) and predict cut sites once a suitable cut site prediction model for any other protease has been developed. Pripper is freely available and can be downloaded from http://users.utu.fi/mijopi/Pripper.
We have developed Pripper, a tool for reading an arbitrary number of proteins in FASTA format, predicting their caspase cleavage sites and outputting the cleaved sequences to a new FASTA format sequence file. We show that Pripper is a valuable tool in identifying novel caspase target proteins from modern proteomics experiments.
半胱天冬酶是一类在细胞程序性死亡(细胞凋亡)和炎症中具有核心功能的蛋白酶。半胱天冬酶通过其靶蛋白天冬氨酸特异性切割来发挥作用,目前已知近 400 种半胱天冬酶底物。已经开发了几种从单个蛋白质预测半胱天冬酶切割位点的方法,但目前没有一种方法可用于从多个蛋白质或整个蛋白质组预测半胱天冬酶切割位点,或组合使用几种分类器。从预测的半胱天冬酶切割产物创建整个基因组数据库的可能性,可以显著帮助从基于串联质谱的蛋白质组实验中识别新的半胱天冬酶靶标。
开发了三种不同的模式识别分类器,用于从蛋白质序列预测半胱天冬酶切割位点。使用质量度量标准评估分类器表明,所有三种分类器在预测半胱天冬酶切割位点方面都表现良好,并且当组合使用不同的分类器时,准确性进一步提高。开发了一种新工具 Pripper,用于利用分类器从任意数量的输入序列预测半胱天冬酶切割位点。使用开发的工具构建了一个数据库,并将其用于从两个不同蛋白质组实验的串联质谱数据中鉴定半胱天冬酶靶标蛋白。使用该数据库鉴定了已知的半胱天冬酶切割产物和新的切割产物,证明了该工具的有用性。Pripper不仅限于预测半胱天冬酶切割位点,还可以扫描蛋白质序列以寻找任何给定的基序,并在为任何其他蛋白酶开发出合适的切割位点预测模型后预测切割位点。Pripper 是免费的,可以从 http://users.utu.fi/mijopi/Pripper 下载。
我们开发了 Pripper,这是一种用于以 FASTA 格式读取任意数量蛋白质的工具,预测它们的半胱天冬酶切割位点,并将切割后的序列输出到新的 FASTA 格式序列文件中。我们表明,Pripper 是从现代蛋白质组学实验中鉴定新的半胱天冬酶靶蛋白的有价值的工具。