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Molecules. 2015 Jul 16;20(7):12841-62. doi: 10.3390/molecules200712841.

Three-dimensional compound comparison methods and their application in drug discovery.

Author information

1
Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA. shin183@purdue.edu.
2
School of Life Science, Anhui University, Hefei 230601, China. newxiaoleizhu@gmail.com.
3
Discovery Chemistry Research and Technologies, Eli Lilly and Company, Indianapolis, IN 46285, USA. bures_mark@lilly.com.
4
Department of Biological Science, Purdue University, West Lafayette, IN 47907, USA. dkihara@purdue.edu.
5
Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA. dkihara@purdue.edu.

Abstract

Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS) methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D). Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.

KEYWORDS:

3D Zernike descriptors; PL-PatchSurfer; Patch-Surfer; ROCS; USR; ligand-based virtual screening; molecular shape; molecular surface; three-dimensional similarity

PMID:
26193243
PMCID:
PMC5005041
DOI:
10.3390/molecules200712841
[Indexed for MEDLINE]
Free PMC Article

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