Deterministic pharmacophore detection via multiple flexible alignment of drug-like molecules

Yuval Inbar*, Dina Schneidman-Duhovny, Oranit Dror, Ruth Nussinov, Haim J. Wolfson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

We present a novel highly efficient method for the detection of a pharmacophore from a set of ligands/drugs that interact with a target receptor. A pharmacophore is a spatial arrangement of physicochemical features in a ligand that is responsible for the interaction with a specific receptor. In the absence of a known 3D receptor structure, a pharmacophore can be identified from a multiple structural alignment of the ligand molecules. The key advantages of the presented algorithm are: (a) its ability to multiply align flexible ligands in a deterministic manner, (b) its ability to focus on subsets of the input ligands, which may share a large common substructure, resulting in the detection of both outlier molecules and alternative binding modes, and (c) its computational efficiency, which allows to detect pharmacophores shared by a large number of molecules on a standard PC. The algorithm was extensively tested on a dataset of almost 80 ligands acting on 12 different receptors. The results, which were achieved using a standard default parameter set, were consistent with reference pharmacophores that were derived from the bound ligand-receptor complexes. The pharmacophores detected by the algorithm are expected to be a key component in the discovery of new leads by screening large drug-like molecule databases.

Original languageAmerican English
Title of host publicationResearch in Computational Molecular Biology - 11th Annual International Conference, RECOMB 2007, Proceedings
PublisherSpringer Verlag
Pages412-429
Number of pages18
ISBN (Print)3540716807, 9783540716808
DOIs
StatePublished - 2007
Externally publishedYes
Event11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007 - Oakland, CA, United States
Duration: 21 Apr 200725 Apr 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4453 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007
Country/TerritoryUnited States
CityOakland, CA
Period21/04/0725/04/07

Keywords

  • 3D molecular similarity
  • 3D molecular superposition
  • Computer-Aided Drug Design (CADD)
  • Rational drug discovery

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