期刊
JOURNAL OF COMPUTATIONAL BIOLOGY
卷 15, 期 7, 页码 737-754出版社
MARY ANN LIEBERT INC
DOI: 10.1089/cmb.2007.0130
关键词
computer-aided drug design (CADD); rational drug discovery; 3D molecular similarity; 3D molecular superposition
类别
资金
- Intramural NIH HHS [Z01 BC010442-06] Funding Source: Medline
- NCI NIH HHS [N01-CO-12400, N01CO12400] Funding Source: Medline
- NIAID NIH HHS [UC1 AI067231, 1UC1AI067231] Funding Source: Medline
We present a novel highly efficient method for the detection of a pharmacophore from a set of drug-like ligands that interact with a target receptor. A pharmacophore is a spatial arrangement of physico-chemical features in a ligand that is essential for the interaction with a specific receptor. In the absence of a known three-dimensional (3D) receptor structure, a pharmacophore can be identified from a multiple structural alignment of 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 set of standard default parameters, 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 databases of drug-like molecules. A user-friendly web interface is available at http://bioinfo3d.cs.tau.ac.il/pharma. Supplementary material can be found at http://bioinfo3d.cs.tau.ac.il/pharma/reduction/.
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