Detecting sequence signals in targeting peptides using deep learning.

Jose Juan Almagro Armenteros,Ole Winther,Arne Elofsson,Henrik Nielsen,Olof Emanuelsson,Marco Salvatore,Gunnar Von Heijne

doi:10.26508/lsa.201900429

Abstract

In bioinformatics, machine learning methods have been used to predict features embedded in the sequences. In contrast to what is generally assumed, machine learning approaches can also provide new insights into the underlying biology. Here, we demonstrate this by presenting TargetP 2.0, a novel state-of-the-art method to identify N-terminal sorting signals, which direct proteins to the secretory pathway, mitochondria, and chloroplasts or other plastids. By examining the strongest signals from the attention layer in the network, we find that the second residue in the protein, that is, the one following the initial methionine, has a strong influence on the classification. We observe that two-thirds of chloroplast and thylakoid transit peptides have an alanine in position 2, compared with 20% in other plant proteins. We also note that in fungi and single-celled eukaryotes, less than 30% of the targeting peptides have an amino acid that allows the removal of the N-terminal methionine compared with 60% for the proteins without targeting peptide. The importance of this feature for predictions has not been highlighted before.

Highlights

The localisation of proteins in the cell is a fundamental determinant of protein function
TargetP 2.0 improves identification of targeting peptides In Table S1, it can be seen that TargetP 2.0 is better than all the competitors at the identification of targeting peptides in accuracy and correlation coefficients
It can be noted that the identification of Signal peptides (SPs) is more reliable than the identification of transit peptides

Summary

Introduction

The localisation of proteins in the cell is a fundamental determinant of protein function. Specific sorting signals drive the subcellular localisation of proteins. These signals vary in structure, length, and position between the different subcellular compartments. One of the most common types of sorting signals are the N-terminal targeting peptides. These signals are responsible for sorting proteins to the secretory pathway, mitochondria, chloroplasts (or other plastids), and compartments inside the chloroplast such as thylakoids. Signal peptides (SPs) are responsible for transporting proteins to the endoplasmic reticulum to enter the secretory pathway. SPs are composed of three regions: a positively charged domain or n-region, a hydrophobic core or h-region, and a segment before the cleavage site (CS) or c-region (von Heijne, 1990)

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Results

Conclusion