MUSI

MUSI identifies multiple binding specificity patterns from peptide and nucleic-acid binding datasets to characterize peptide recognition domains and transcription factor binding preferences.

Key Features:

• High-Throughput Analysis: Leverages next-generation sequencing to increase the throughput of experimental techniques such as microarrays and phage display, enabling retrieval and analysis of thousands of distinct ligands.
• Detection of Multiple Specificity Patterns: Detects coexisting and previously unrecognized classes of binding specificities within large sequence datasets.
• Integrated Processing: Processes very large datasets generated by next-generation sequencing machines for efficient handling and analysis.
• Visualization: Produces multiple sequence logos that describe distinct binding preferences of proteins.

Scientific Applications:

• Protein–ligand interaction analysis: Analyzes interactions such as human SH3 domains using phage display data to reveal binding specificity classes.
• Transcription factor specificity profiling: Profiles transcription factor binding preferences from microarray data, exemplified by analyses of mouse transcription factors.

Methodology:

Starts from a set of sequences known to bind a specific target and automatically generates an optimal number of motifs that represent different specificity patterns present in the data.