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Structure−Activity Landscape Index: Identifying and Quantifying Activity Cliffs
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Abstract
A new method for analyzing a structure−activity relationship is proposed. By use of a simple quantitative index, one can readily identify “structure−activity cliffs”: pairs of molecules which are most similar but have the largest change in activity. We show how this provides a graphical representation of the entire SAR, in a way that allows the salient features of the SAR to be quickly grasped. In addition, the approach allows us view the SARs in a data set at different levels of detail. The method is tested on two data sets that highlight its ability to easily extract SAR information. Finally, we demonstrate that this method is robust using a variety of computational control experiments and discuss possible applications of this technique to QSAR model evaluation.
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This article has been cited by 19 ACS Journal articles (5 most recent appear below).
Exploring Activity Cliffs in Medicinal Chemistry
Dagmar Stumpfe and Jürgen BajorathJournal of Medicinal Chemistry2012 Article ASAPExploring Activity Cliffs in Medicinal Chemistry
Dagmar Stumpfe and Jürgen BajorathJournal of Medicinal Chemistry2012 Article ASAP
Exploration of the Topology of Chemical Spaces with Network Measures
Michael P. Krein and N. SukumarThe Journal of Physical Chemistry A2011 115 (45), 12905-12918Exploration of the Topology of Chemical Spaces with Network Measures
Michael P. Krein and N. SukumarThe Journal of Physical Chemistry A2011 115 (45), 12905-12918Discontinuous changes in molecular structure (resulting from continuous transformations of molecular coordinates) lead to changes in chemical properties and biological activities that chemists attempt to describe through structure–activity or structure–...
Multitarget Structure–Activity Relationships Characterized by Activity-Difference Maps and Consensus Similarity Measure
José L. Medina-Franco, Austin B. Yongye, Jaime Pérez-Villanueva, Richard A. Houghten, and Karina Martínez-MayorgaJournal of Chemical Information and Modeling2011 51 (9), 2427-2439Multitarget Structure–Activity Relationships Characterized by Activity-Difference Maps and Consensus Similarity Measure
José L. Medina-Franco, Austin B. Yongye, Jaime Pérez-Villanueva, Richard A. Houghten, and Karina Martínez-MayorgaJournal of Chemical Information and Modeling2011 51 (9), 2427-2439Dual and triple activity-difference (DAD/TAD) maps are tools for the systematic characterization of structure–activity relationships (SAR) of compound data sets screened against two or three targets. DAD and TAD maps are two- and three- dimensional ...
From Activity Cliffs to Activity Ridges: Informative Data Structures for SAR Analysis
Martin Vogt, Yun Huang, and Jürgen BajorathJournal of Chemical Information and Modeling2011 Article ASAPFrom Activity Cliffs to Activity Ridges: Informative Data Structures for SAR Analysis
Martin Vogt, Yun Huang, and Jürgen BajorathJournal of Chemical Information and Modeling2011 Article ASAPThe extraction of SAR information from structurally diverse compound data sets is a challenging task. One of the focal points of systematic SAR analysis is the search for activity cliffs, that is, structurally similar compounds having large potency ...
Extraction of Discontinuous Structure–Activity Relationships from Compound Data Sets through Particle Swarm Optimization
Vigneshwaran Namasivayam, Preeti Iyer, and Jürgen BajorathJournal of Chemical Information and Modeling2011 Article ASAPExtraction of Discontinuous Structure–Activity Relationships from Compound Data Sets through Particle Swarm Optimization
Vigneshwaran Namasivayam, Preeti Iyer, and Jürgen BajorathJournal of Chemical Information and Modeling2011 Article ASAPThe characterization of structure–activity relationship (SAR) features of large compound data sets has been a hot topic in recent years, and different methods for large-scale SAR analysis have been introduced. The exploration of local SAR components and ...
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History
- Published In Issue March 24, 2008
- Received November 8, 2007
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Why QSAR Often Disappoints
