Center for Bioscience Research and Education, Utsunomiya University, Japan.
Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Japan.
Methods Enzymol. 2024;706:161-192. doi: 10.1016/bs.mie.2024.07.026. Epub 2024 Sep 11.
In this chapter we survey prediction tools and computational methods for the prediction of amino acid sequence elements which target proteins to the mitochondria. We will primarily focus on the prediction of N-terminal mitochondrial targeting signals (MTSs) and their N-terminal cleavage sites by mitochondrial peptidases. We first give practical details useful for using and installing some prediction tools. Then we describe procedures for preparing datasets of MTS containing proteins for statistical analysis or development of new prediction methods. Following that we lightly survey some of the computational techniques used by prediction tools. Finally, after discussing some caveats regarding the reliability of such methods to predict the effects of mutations on MTS function; we close with a discussion of possible future directions of computer prediction methods related to mitochondrial proteins.
在本章中,我们调查了预测工具和计算方法,用于预测靶向蛋白质到线粒体的氨基酸序列元件。我们将主要关注线粒体靶向信号(MTS)的 N 端预测及其被线粒体肽酶切割的 N 端切割位点。我们首先提供了一些预测工具的实际使用和安装的有用细节。然后,我们描述了准备用于统计分析或开发新预测方法的包含 MTS 蛋白的数据集的过程。接下来,我们简要调查了预测工具使用的一些计算技术。最后,在讨论了这些方法在预测 MTS 功能突变影响的可靠性方面的一些注意事项之后,我们讨论了与线粒体蛋白相关的计算机预测方法的可能未来方向。