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Systematic identification and classification of three-dimensional activity cliffs.

Authors :
Hu Y
Furtmann N
Gütschow M
Bajorath J
Source :
Journal of chemical information and modeling [J Chem Inf Model] 2012 Jun 25; Vol. 52 (6), pp. 1490-8. Date of Electronic Publication: 2012 Jun 01.
Publication Year :
2012

Abstract

Activity cliffs were systematically extracted from public domain X-ray structures of targets for which complexes with multiple ligands were available, following the concept of three-dimensional (3D) cliffs. Binding modes of ligands with well-defined potency measurements were compared in a pairwise manner, and their 3D similarity was calculated using a previously reported property density function-based method taking conformational, positional, and chemical differences into account. Requiring the presence of at least 80% 3D similarity and a potency difference of at least 2 orders of magnitude as cliff criteria, a total of 216 well-defined 3D activity cliffs were detected in the Protein Data Bank (PDB). These 3D-cliffs involved a total of 269 ligands active against 38 different targets belonging to 17 protein families. For 255 of these compounds, binding modes were available at high crystallographic resolution. All 3D-cliffs were analyzed in detail and assigned to different categories on the basis of crystallographic interaction patterns. In many instances, differences in ligand-target interactions suggested plausible causes for origins of 3D-cliffs. In other cases, short-range interactions seen in X-ray structures were insufficient to deduce possible reasons for cliff formation. The 3D-cliffs described herein further advance the rationalization of activity cliffs at the level of ligand-target interactions and should also be useful for other applications such as the calibration of energy functions for structure-based design. The pool of identified activity cliffs is provided to enable subsequent structure-based analyses of cliffs.

Details

Language :
English
ISSN :
1549-960X
Volume :
52
Issue :
6
Database :
MEDLINE
Journal :
Journal of chemical information and modeling
Publication Type :
Academic Journal
Accession number :
22612566
Full Text :
https://doi.org/10.1021/ci300158v