A Yongye

Austin B Yongye

D Dimova

GM Maggiora

J Pérez-Villanueva

Jaime Pérez-Villanueva

JL Medina-Franco

José L Medina-Franco

Karina Martínez-Mayorga

Richard A Houghten

Journal of Cheminformatics

English

PubMed

Springer - Publisher Connector

POSTER PRESENTATION Open Access
Activity-difference maps and consensus similarity
measure characterize structure-activity
relationships
José L Medina-Franco1*, Austin B Yongye1, Jaime Pérez-Villanueva2, Richard A Houghten1,
Karina Martínez-Mayorga1
From 7th German Conference on Chemoinformatics: 25 CIC-Workshop
Goslar, Germany. 6-8 November 2011
Dual and triple activity-difference (DAD/TAD) maps are
two- and three- dimensional representations of the pair-
wise activity differences of compound data sets, respec-
tively [1]. These maps are valuable tools for the systematic
characterization of structure-activity relationships (SAR)
of compounds data sets screened against two or three tar-
gets [2]. Adding pairwise structural similarity information
into the DAD/TAD maps readily reveals activity cliff [3]
regions in the SAR for one, two or the three targets. In
addition, pairs of compounds in the smooth regions of the
SAR and scaffold hops are also easily identified in these
maps. Herein, we describe DAD and TAD maps for the
systematic characterization of the SAR of data sets
screened against three molecular targets. Several 2D and
3D structure representations were used to characterize the
SAR in order to reduce the well-known dependence of the
activity landscape on the structural representation [4,5].
Systematic analysis of the DAD and TAD maps reveals
regions in the landscape with similar SAR for two or the
tree targets as well as regions with inverse SAR, i.e.,
changes in structure that increase activity for one target,
but decrease activity for the other target. Focusing the ana-
lysis on pairs of compounds with high structure similarity
revealed the presence of single-, dual- and triple-target
activity cliffs, i.e., small changes in structure with high
changes in potency for one, two or the three targets,
respectively. Triple-target scaffold hops are also discussed.
Author details
1Torrey Pines Institute for Molecular Studies, Port St. Lucie, Florida, 34987,
USA. 2Departament of Biological Systems, UAM-X, Mexico City, 04960,
Mexico.
Published: 1 May 2012
References
1. Pérez-Villanueva J, Santos R, Hernández-Campos A, Giulianotti MA,
Castillo R, Medina-Franco JL: Structure-Activity Relationships of
Benzimidazole Derivatives as Antiparasitic Agents: Dual Activity-
Difference (DAD) Maps. Med Chem Comm 2011, 2:44-49.
2. Dimova D, Wawer M, Wassermann AM, Bajorath J: Design of Multitarget
Activity Landscapes that Capture Hierarchical Activity Cliff Distributions.
J Chem Inf Model 2011, 51:258-266.
3. Maggiora GM: On Outliers and Activity Cliffs-Why QSAR Often
Disappoints. J Chem Inf Model 2006, 46:1535-1535.
4. Medina-Franco JL, Martínez-Mayorga K, Bender A, Marín RM, Giulianotti MA,
Pinilla C, Houghten RA: Characterization of Activity Landscapes Using 2D
and 3D Similarity Methods: Consensus Activity Cliffs. J Chem Inf Model
2009, 49:477-491.
5. Yongye A, Byler K, Santos R, Martínez-Mayorga K, Maggiora GM, Medina-
Franco JL: Consensus Models of Activity Landscapes with Multiple
Chemical, Conformer and Property Representations. J Chem Inf Model
2011, 51:1259-1270.
doi:10.1186/1758-2946-4-S1-P24
Cite this article as: Medina-Franco et al.: Activity-difference maps and
consensus similarity measure characterize structure-activity
relationships. Journal of Cheminformatics 2012 4(Suppl 1):P24.
* Correspondence: jmedina@tpims.org
1Torrey Pines Institute for Molecular Studies, Port St. Lucie, Florida, 34987,
USA
Full list of author information is available at the end of the article
Medina-Franco et al. Journal of Cheminformatics 2012, 4(Suppl 1):P24
http://www.jcheminf.com/content/4/S1/P24
© 2012 Medina-Franco et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.


Activity-difference maps and consensus similarity measure characterize structure-activity relationships

Crossref

Design of Multitarget Activity Landscapes that Capture Hierarchical Activity Cliff Distributions. J Chem Inf Model

Houghten RA: Characterization of Activity Landscapes Using 2D and 3D Similarity Methods: Consensus Activity Cliffs. J Chem Inf Model

Medina-Franco JL: Structure-Activity Relationships of Benzimidazole Derivatives as Antiparasitic Agents: Dual ActivityDifference (DAD) Maps. Med Chem Comm

On Outliers and Activity Cliffs-Why QSAR Often Disappoints.

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3341234

Activity-difference maps and consensus similarity measure characterize structure-activity relationships

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