title: Simple Ligand-Receptor Interaction Descriptor (SILIRID) for alignment-free binding site comparison.
abstract: We describe SILIRID (Simple Ligand-Receptor Interaction Descriptor), a novel fixed size descriptor characterizing protein-ligand interactions. SILIRID can be obtained from the binary interaction fingerprints (IFPs) by summing up the bits corresponding to identical amino acids. This results in a vector of 168 integer numbers corresponding to the product of the number of entries (20 amino acids and one cofactor) and 8 interaction types per amino acid (hydrophobic, aromatic face to face, aromatic edge to face, H-bond donated by the protein, H-bond donated by the ligand, ionic bond with protein cation and protein anion, and interaction with metal ion). Efficiency of SILIRID to distinguish different protein binding sites has been examined in similarity search in sc-PDB database, a druggable portion of the Protein Data Bank, using various protein-ligand complexes as queries. The performance of retrieval of structurally and evolutionary related classes of proteins was comparable to that of state-of-the-art approaches (ROC AUC ≈ 0.91). SILIRID can efficiently be used to visualize chemogenomic space covered by sc-PDB using Generative Topographic Mapping (GTM): sc-PDB SILIRID data form clusters corresponding to different protein types.
authors.affiliation: Laboratory of Chémoinformatics, UMR 7140, University of Strasbourg, France.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Chupakhin
authors.affiliation: Laboratory of Chémoinformatics, UMR 7140, University of Strasbourg, France.
authors.forename: Gilles
authors.initials: G
authors.lastname: Marcou
authors.affiliation: Laboratory of Chémoinformatics, UMR 7140, University of Strasbourg, France.
authors.forename: Helena
authors.initials: H
authors.lastname: Gaspar
authors.affiliation: Laboratory of Chémoinformatics, UMR 7140, University of Strasbourg, France.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Varnek
keywords: Chemogenomics; Generative Topographic Mapping; Interaction fingerprints; Protein classification; Protein similarity; Protein–ligand interactions