HSMotifDiscover

HSMotifDiscover identifies motifs within sequences composed of non-single-letter elements to detect functional sub-strings that govern specificity of interactions between biopolymers and biomolecules, including sequences with chemical modifications in proteins, DNAs, RNAs, or polysaccharides.

Key Features:

• Conversion of Complex Elements: Converts modified sequence elements into representative single-letter codes to enable downstream motif analysis.
• Modified Gibbs-Sampling Algorithm: Uses a modified Gibbs-sampling algorithm to infer motifs and define position-specific scoring matrices (PSSMs).
• Application to Glycan Sequences: Implements motif discovery for heparan sulfate (HS) glycan sequences as a proof of principle.
• High-Throughput Data Integration: Applies motif discovery to high-throughput glycoprotein binding data, including microarrays with HS oligosaccharides.

Scientific Applications:

• Motif Discovery in Complex Sequences: Enables identification of functional motifs in sequences containing chemical modifications across biopolymers.
• Regulation of Protein-Protein Interactions: Facilitates analysis of heparan sulfate (HS) motifs that modulate protein–protein interactions.
• High-Throughput Binding Analysis: Supports analysis of large-scale glycoprotein binding datasets such as microarray screens with HS oligosaccharides.

Methodology:

Converts modified sequence elements to representative single-letter codes and applies a modified Gibbs-sampling algorithm to derive position-specific scoring matrices (PSSMs).