Kunze M. Computational Evaluation of Peroxisomal Targeting Signals in Metazoa.
Methods Mol Biol 2023;
2643:391-404. [PMID:
36952201 DOI:
10.1007/978-1-0716-3048-8_28]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
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.
Collapse