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A method for localizing ligand binding pockets in protein structures.

Fabian Glaser1, Richard J Morris, Rafael J Najmanovich

  • 1European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom. fabian@ebi.ac.uk

Proteins
|November 24, 2005
PubMed
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We developed SURFNET-ConSurf, a new method to identify ligand binding pockets in proteins. This computational tool accurately predicts binding sites, aiding in protein function determination and drug discovery.

Area of Science:

  • Structural Biology
  • Computational Biology
  • Biochemistry

Background:

  • Accurate identification of ligand binding sites is crucial for understanding protein function.
  • Knowledge of binding sites facilitates in silico and experimental analyses for ligand and protein function determination.
  • Binding pocket shape analysis critically depends on precise ligand binding site localization.

Purpose of the Study:

  • To develop and validate SURFNET-ConSurf, a novel computational method for identifying potential ligand binding pockets in protein structures.
  • To assess the accuracy and efficiency of SURFNET-ConSurf in locating and defining the shape of binding pockets.
  • To evaluate the performance of SURFNET-ConSurf across different protein types, particularly enzymes.

Main Methods:

Related Experiment Videos

  • Developed SURFNET-ConSurf, a two-stage computational approach for identifying ligand binding pockets.
  • Stage 1: SURFNET program identifies surface clefts as potential binding sites.
  • Stage 2: ConSurf-HSSP database is used to trim clefts, retaining regions near conserved residues.

    • Main Results:

    • SURFNET-ConSurf successfully identified ligand binding pockets in 75% of 244 analyzed protein structures from the Protein Data Bank (PDB).
    • The trimming procedure reduced average cleft volumes by 30% while preserving 87% of the ligand volume.
    • The method demonstrated superior performance for enzymes compared to non-enzyme proteins.

    Conclusions:

    • SURFNET-ConSurf accurately identifies ligand binding pockets, especially those associated with large, conserved clefts.
    • The method provides pockets that better match ligand shape and location, enhancing predictions.
    • This computational approach is a valuable tool for protein function studies and drug design, particularly for enzymes.