RaacFold

RaacFold analyzes protein sequences and structures using reduced amino acid alphabets (Raaa) to simplify sequence and structural complexity and identify functionally conserved regions and biophysical conservation.

Key Features:

• Reduced amino acid alphabets (Raaa): Uses Raaa to simplify protein sequence and structural representations for analysis.
• 687 Raac clusters: Provides a library of 687 reduced amino acid clusters (Raac) as the basis for analyses.
• 58 reduction methods: Raac clusters are derived from 58 distinct amino-acid reduction methods.
• Protein Analysis: Produces simplified sequence and structure representations based on physicochemical similarities and computational biology strategies.
• Align Analysis: Aligns sequences and structures using reduced representations to reveal conserved regions and functional motifs.
• Multi Analysis: Compares biophysical variations and conservation across proteins to detect nonhomologous functions among paralogs and evolutionary changes.
• 2D and 3D rendering: Generates 2D and 3D visualizations with adjustable parameters for sequences, structures, and annotations.

Scientific Applications:

• Identification of conserved regions: Detects functionally conserved regions within proteins by reducing amino acid complexity.
• Functional motif discovery: Reveals conserved motifs across aligned reduced representations of proteins.
• Evolutionary analysis: Assesses conservation and biophysical variation over evolutionary timescales to inform evolutionary relationships and functional roles.
• Paralog function differentiation: Identifies nonhomologous functions among paralogs through comparative reduced-representation analysis.
• Protein engineering support: Informs artificial protein design by highlighting conserved and variable biophysical features.

Methodology:

Applies reduced amino acid alphabets (Raaa) using 687 Raac clusters derived from 58 reduction methods, generates reduced sequence and structural representations based on physicochemical similarities, aligns sequences and structures in reduced representation space, explores biophysical variations and conservation across proteins, and renders 2D and 3D visualizations of sequences, structures, and annotations.