QSbio

QSbio annotates quaternary structure (QS) conservation across the Protein Data Bank (PDB) to identify biologically relevant oligomeric states and distinguish true protein interfaces from crystal-packing contacts.

Key Features:

• Alignment and comparison of QS: Aligns and compares QS states across homologous proteins and data repositories.
• Conservation-based prediction: Leverages strong conservation of QS among homologs to predict biological relevance.
• QSalign: Annotates homo-oligomers by identifying conserved QS.
• anti-QSalign: Targets monomeric proteins and distinguishes biologically relevant interfaces from crystal-packing contacts.
• Large-scale annotation: Systematically identifies and annotates QS states across the PDB with accuracy approaching manual curation.
• Extensive dataset: Predicts and catalogs over 100,000 QS states.
• Interface conservation analysis: Examines pairs of structurally conserved interfaces to reveal evolutionary plasticity where interaction geometries are maintained despite divergent chemical properties.

Scientific Applications:

• Identification of biologically relevant oligomers: Predicts and annotates functional oligomeric assemblies in PDB entries.
• PDB-scale structural annotation: Provides a comprehensive dataset of QS states for downstream structural and bioinformatics analyses.
• Protein evolution studies: Enables investigation of conservation and plasticity of protein–protein interfaces across homologs.
• Structural interpretation: Differentiates biological interfaces from crystal contacts to improve interpretation of X-ray structures.
• Functional and disease mechanism research: Supports studies linking quaternary assembly to protein function and disease mechanisms.

Methodology:

Aligning and comparing QS states across homologous proteins and repositories using two complementary methods, QSalign for annotating conserved homo-oligomers and anti-QSalign for distinguishing monomeric interfaces from crystal-packing contacts, and analysis of structurally conserved interface pairs within the predicted QS dataset.