VASE

VASE visualizes HSSP multiple sequence alignments and entropy/variability data on Protein Data Bank (PDB) 3D protein structures to support analysis of conserved and variable sites.


Key Features:

  • Protein structure retrieval: Accepts Protein Data Bank (PDB) identifiers to retrieve 3D structures and associate structural coordinates with alignment positions.
  • HSSP multiple sequence alignments: Uses HSSP (Homology-derived Secondary Structure of Proteins) multiple sequence alignments linked to target structures.
  • Entropy/variability metrics: Presents entropy and variability information for aligned sequences to indicate sequence conservation and diversity across homologs.
  • Secondary-structure and conservation mapping: Maps secondary-structure elements and conserved regions onto 3D models to correlate structural context with alignment-derived signals.

Scientific Applications:

  • Comparative and evolutionary analysis: Enables comparative analyses of protein families to interpret conserved and variable sites in an evolutionary context.
  • Functional and stability inference: Supports interpretation of the functional implications of conserved residues and variable sites for protein stability and function.
  • Structural genomics: Facilitates structural genomics studies by linking sequence conservation patterns to solved PDB structures.
  • Structure-guided drug design: Provides structural context for conserved and variable regions to inform drug design.

Methodology:

VASE retrieves HSSP alignments and structural information from the Protein Data Bank (PDB) and processes these data to generate visual representations that highlight secondary structures, conserved regions, and entropy/variability across homologous sequences.

Topics

Details

Programming Languages:
JavaScript
Added:
1/14/2020
Last Updated:
1/16/2021

Operations

Publications

Lange J, Baakman C, Pistorius A, Krieger E, Hooft R, Joosten RP, Vriend G. Facilities that make the PDB data collection more powerful. Protein Science. 2019;29(1):330-344. doi:10.1002/pro.3788. PMID:31724231. PMCID:PMC6933850.

Links