LSPpred Suite: Tools for Leaderless Secretory Protein Prediction in Plants.

ABSTRACT: Plant proteins that are secreted without a classical signal peptide leader sequence are termed leaderless secretory proteins (LSPs) and are implicated in both plant development and (a)biotic stress responses. In plant proteomics experimental workflows, identification of LSPs is hindered by the possibility of contamination from other subcellar compartments upon purification of the secretome. Applying machine learning algorithms to predict LSPs in plants is also challenging due to the rarity of experimentally validated examples for training purposes. This work attempts to address this issue by establishing criteria for identifying potential plant LSPs based on experimental observations and training random forest classifiers on the putative datasets. The resultant plant protein database LSPDB

SUBMITTER: Lonsdale A 

PROVIDER: S-EPMC10097205 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature