Tertiary alphabet for the observable protein structural universe

Area of Science:

• Structural biology
• Computational biology
• Biophysics

Background:

• Protein structure is complex and vast, making comprehensive analysis challenging.
• Understanding the fundamental building blocks of protein structure is crucial for prediction and design.

Purpose of the Study:

• To systematically decompose the protein structural universe into basic elements called tertiary structural motifs (TERMs).
• To determine a universal set of TERMs sufficient for describing all known protein structures in the Protein Data Bank (PDB).
• To explore the utility of TERMs in mapping protein sequence to structure and predicting structural features.

Main Methods:

• Systematic decomposition of protein structures from the PDB into compact backbone fragments (TERMs).
• Statistical analysis to identify a minimal set of universal TERMs covering the PDB.
• Developing TERM-based statistical models to predict protein sequences from backbone structures.
• Investigating sequence signatures for predicting TERM locations within protein chains.

Main Results:

• A finite set of TERMs can describe the entire known protein structural universe with remarkable degeneracy.
• Approximately 600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution.
• TERM-based statistics accurately recapitulate native protein sequences from backbone structures and predict evolutionary variation.
• TERM locations in protein chains can be predicted from sequence alone, identifying non-contiguous fragments.

Conclusions:

• TERMs represent fundamental units of protein structure, offering a new paradigm for understanding protein architecture.
• The identified universal TERMs provide an effective bridge between protein sequence and structure.
• This decomposition facilitates improved protein structure prediction, design, and functional analysis.