eMatchSite

eMatchSite performs sequence order-independent structure alignments of ligand binding pockets to detect similar binding sites across proteins for drug-target identification and proteome-scale analyses.


Key Features:

  • Sequence Order-Independent Alignments: Constructs alignments of ligand binding pockets without relying on residue sequence order, enabling detection of functional similarities despite lack of global homology.
  • High Tolerance for Structural Distortions: Maintains alignment accuracy for structurally distorted or low-quality predicted protein models, supporting proteome-scale analyses of gene products.
  • Benchmarking Performance: Large-scale benchmarking on adenine-binding pockets showed eMatchSite aligns nearly three times more protein pairs than SOIPPA and incurs only a 4–9% reduction in accuracy compared with crystal structures for weakly homologous models.
  • Superiority Over Existing Algorithms: Outperforms SiteEngine by 6% on high-quality models and 13% on moderate-quality models in recognizing similar binding sites.

Scientific Applications:

  • Drug–protein interaction network analysis: Enables systematic investigation of drug–protein interaction networks across complete proteomes.
  • Polypharmacology: Supports systems-level polypharmacology studies by identifying shared or off-target binding sites.
  • Rational drug repositioning: Facilitates rational drug repositioning by revealing binding-site similarities between unrelated proteins.

Methodology:

Performs sequence order-independent alignment of ligand binding pockets and tolerates structural distortions to align predicted protein structure models without requiring high-quality experimental (crystal) structures; benchmarking used adenine-binding pockets.

Topics

Details

Tool Type:
command-line tool, web application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
C++
Added:
5/8/2018
Last Updated:
12/10/2018

Operations

Publications

Brylinski M. eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models. PLoS Computational Biology. 2014;10(9):e1003829. doi:10.1371/journal.pcbi.1003829. PMID:25232727. PMCID:PMC4168975.

Documentation