NASSAM

NASSAM identifies three-dimensional spatial patterns and motifs of nucleic acid bases in PDB-formatted structures using graph-theoretical representations to analyze base-base spatial arrangements relevant to RNA function and structural stabilization.

Key Features:

• Graph Theoretical Representation: Represents nucleic acid bases as pseudo-atoms within a labeled graph where nodes are pseudo-atoms and edges encode inter-pseudo-atomic distances.
• PDB Format Compatibility: Accepts PDB-formatted 3D coordinates as input for analysis of experimentally determined structures.
• Sequence-Independent Analysis: Detects spatial arrangements independent of nucleotide sequence order, enabling motif detection based solely on geometry.
• Pattern Matching to Annotated Motifs: Searches query structures for specific 3D patterns and matches them to annotated patterns from the literature.

Scientific Applications:

• RNA structural motif identification: Detects recurring 3D base arrangements that contribute to RNA tertiary structure stabilization.
• Functional inference of RNA: Relates detected spatial motifs to potential functional roles of RNA elements.
• Structural comparison and annotation: Matches query structures to literature-annotated motifs for structural interpretation and annotation.
• Support for structural biology, genomics, and molecular medicine: Provides geometric motif information useful for studies in structural biology, genomics, and molecular medicine.

Methodology:

Converts PDB 3D coordinates into a labeled graph by representing bases as pseudo-atoms (nodes) and encoding inter-pseudo-atomic distances as edges, then performs graph-based pattern matching against annotated 3D motifs.