Wregex

Wregex predicts amino acid motifs, focusing on leucine-rich nuclear export signals (NESs) that enable cargo proteins to bind the CRM1 receptor and regulate protein localization.

Key Features:

• Weighted regular expressions + PSSM: Integrates weighted regular expressions with a position-specific scoring matrix (PSSM) to detect and score motif matches.
• Scoring and prioritization: Assigns quantitative scores to candidate motifs to prioritize them for experimental validation.
• Flexibility: Adapts the motif-search methodology to detect various types of protein motifs beyond NESs.
• Efficiency: Executes searches rapidly to support large-scale genomic and proteomic analyses.
• Accuracy: Maintains a high true-positive identification rate while reducing the number of candidate sequences.

Scientific Applications:

• NES prediction: Identification and prediction of leucine-rich nuclear export signals (NESs) that mediate CRM1-dependent nuclear export.
• Motif discovery: Detection of other amino acid motifs in protein sequences using pattern-based searches and scoring.
• Experimental prioritization: Prioritizing candidate motifs for experimental validation to investigate protein localization and interactions.
• Large-scale screening: High-throughput screening of proteomes and genomic datasets for motif occurrences.

Methodology:

Applies weighted regular expressions combined with a position-specific scoring matrix (PSSM) to search protein sequences and assign scores for candidate ranking.