PHEMTO

PHEMTO computes pH-dependent electric and dipole moments and analyzes protein electrostatic characteristics to assess molecular recognition and the effects of charge mutagenesis.


Key Features:

  • Electric and dipole moment computation: Computes electric and dipole moments from protein atomic coordinates.
  • Singular value decomposition of EP: Implements singular value decomposition (SVD) of electrostatic potential (EP) to account for reaction field influences.
  • pH-dependent properties: Evaluates global and local pH-dependent properties using mean field electrostatics and approaches from PHEI and the PHEPS server.
  • In silico charge mutagenesis: Performs in silico charge mutagenesis to predict impacts on protein electrostatic characteristics.
  • Non-polypeptide charge support: Allows inclusion of non-polypeptide charges in the electrostatic calculations.
  • PDB input: Accepts atomic coordinate files in Protein Data Bank (PDB) format.
  • Computational performance: Implements algorithms optimized for computational speed and efficiency.

Scientific Applications:

  • Protein–ligand interactions: Analyzes electrostatic contributions to protein–ligand binding and molecular recognition.
  • Enzyme catalysis: Assesses pH-dependent electrostatic effects relevant to enzyme catalytic mechanisms.
  • Structural biology: Provides electrostatic insights to support interpretation of structural data and experimental planning.
  • Drug design: Predicts how pH changes and charge mutations alter interaction surfaces relevant to drug design.

Methodology:

Uses mean field electrostatics and singular value decomposition of electrostatic potential (EP) to account for reaction field effects; requires atomic coordinate input in PDB format; algorithms are optimized for speed and efficiency.

Topics

Details

Tool Type:
web application
Added:
2/14/2017
Last Updated:
12/10/2018

Operations

Publications

Kantardjiev AA and Atanasov BP. PHEMTO: protein pH-dependent electric moment tools. Nucleic Acids Res. 2009; 37:W422-7. doi: 10.1093/nar/gkp336

PMID: 19420068