MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition

TLDR

Functional annotation of unknown proteins relies heavily on predicting subcellular localization, yet existing methods typically target only one biological aspect or a limited set of compartments. The study aims to improve subcellular localization prediction accuracy and coverage by developing an SVM‑based method that integrates N‑terminal targeting sequences, amino‑acid composition, and sequence motifs. The method uses a support‑vector‑machine classifier trained on features derived from N‑terminal targeting sequences, overall amino‑acid composition, and conserved sequence motifs. TargetLoc outperforms existing N‑terminal‑based predictors and, as MultiLoc, achieves superior or comparable accuracy across all major eukaryotic compartments compared to specialized or organism‑specific methods. Contact information: [e-mail].

Abstract

Abstract Motivation: Functional annotation of unknown proteins is a major goal in proteomics. A key annotation is the prediction of a protein's subcellular localization. Numerous prediction techniques have been developed, typically focusing on a single underlying biological aspect or predicting a subset of all possible localizations. An important step is taken towards emulating the protein sorting process by capturing and bringing together biologically relevant information, and addressing the clear need to improve prediction accuracy and localization coverage. Results: Here we present a novel SVM-based approach for predicting subcellular localization, which integrates N-terminal targeting sequences, amino acid composition and protein sequence motifs. We show how this approach improves the prediction based on N-terminal targeting sequences, by comparing our method TargetLoc against existing methods. Furthermore, MultiLoc performs considerably better than comparable methods predicting all major eukaryotic subcellular localizations, and shows better or comparable results to methods that are specialized on fewer localizations or for one organism. Availability: Contact: [e-mail]