Kunze Markus
Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria.
Methods Mol Biol. 2023;2643:391-404. doi: 10.1007/978-1-0716-3048-8_28.
Most soluble proteins enclosed in peroxisomes encode either type-1 or type-2 peroxisomal targeting signals (PTS1 or PTS2), which act as postal codes and define the proteins' intracellular destination. Thus, various computational programs have been developed to evaluate the probability of specific peptide sequences for being a functional PTS or to scan the primary sequence of proteins for such signals. Among these prediction algorithms the PTS1-predictor ( https://mendel.imp.ac.at/pts1/ ) has been amply used, but the research logic of this and other PTS1 prediction tools is occasionally misjudged giving rise to characteristic pitfalls. Here, a proper utilization of the PTS1-predictor is introduced together with a framework of additional tests to increase the validity of the interpretation of results. Moreover, a list of possible causes for a mismatch between results of such predictions and experimental outcomes is provided. However, the foundational arguments apply to other prediction tools for PTS1 motifs as well.
大多数存在于过氧化物酶体中的可溶性蛋白质编码1型或2型过氧化物酶体靶向信号(PTS1或PTS2),这些信号就像邮政编码一样,决定了蛋白质在细胞内的定位。因此,已经开发了各种计算程序来评估特定肽序列成为功能性PTS的可能性,或者在蛋白质的一级序列中扫描此类信号。在这些预测算法中,PTS1预测器(https://mendel.imp.ac.at/pts1/ )得到了广泛应用,但该工具和其他PTS1预测工具的研究逻辑偶尔会被误解,从而导致一些典型的错误。本文介绍了PTS1预测器的正确使用方法以及一系列额外测试,以提高结果解释的有效性。此外,还列出了此类预测结果与实验结果不匹配的可能原因。不过,基本观点也适用于其他PTS1基序预测工具。