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Assessing How Well a Modeling Protocol Captures a Structure−Activity Landscape
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Abstract
We introduce the notion of structure−activity landscape index (SALI) curves as a way to assess a model and a modeling protocol, applied to structure−activity relationships. We start from our earlier work [J. Chem. Inf. Model., 2008, 48, 646−658], where we show how to study a structure−activity relationship pairwise, based on the notion of “activity cliffs”―pairs of molecules that are structurally similar but have large differences in activity. There, we also introduced the SALI parameter, which allows one to identify cliffs easily, and which allows one to represent a structure−activity relationship as a graph. This graph orders every pair of molecules by their activity. Here, we introduce the new idea of a SALI curve, which tallies how many of these orderings a model is able to predict. Empirically, testing these SALI curves against a variety of models, ranging over two-dimensional quantitative structure−activity relationship (2D-QSAR), three-dimensional quantitative structure−activity relationship (3D-QSAR), and structure-based design models, the utility of a model seems to correspond to characteristics of these curves. In particular, the integral of these curves, denoted as SCI and being a number ranging from −1.0 to 1.0, approaches a value of 1.0 for two literature models, which are both known to be prospectively useful.
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This article has been cited by 12 ACS Journal articles (5 most recent appear below).
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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 ...
Consensus Models of Activity Landscapes with Multiple Chemical, Conformer, and Property Representations
Austin B. Yongye, Kendall Byler, Radleigh Santos, Karina Martínez-Mayorga, Gerald M. Maggiora, and José L. Medina-FrancoJournal of Chemical Information and Modeling2011 Article ASAPConsensus Models of Activity Landscapes with Multiple Chemical, Conformer, and Property Representations
Austin B. Yongye, Kendall Byler, Radleigh Santos, Karina Martínez-Mayorga, Gerald M. Maggiora, and José L. Medina-FrancoJournal of Chemical Information and Modeling2011 Article ASAPWe report consensus Structure–Activity Similarity (SAS) maps that address the dependence of activity landscapes on molecular representation. As a case study, we characterized the activity landscape of 54 compounds with activities against human cathepsin B ...
Single R-Group Polymorphisms (SRPs) and R-Cliffs: An Intuitive Framework for Analyzing and Visualizing Activity Cliffs in a Single Analog Series
Dimitris K. Agrafiotis, John J. M. Wiener, Andrew Skalkin, and Jeremy KolpakJournal of Chemical Information and Modeling2011 51 (5), 1122-1131Single R-Group Polymorphisms (SRPs) and R-Cliffs: An Intuitive Framework for Analyzing and Visualizing Activity Cliffs in a Single Analog Series
Dimitris K. Agrafiotis, John J. M. Wiener, Andrew Skalkin, and Jeremy KolpakJournal of Chemical Information and Modeling2011 51 (5), 1122-1131We introduce Single R-Group Polymorphisms (SRPs, pronounced ‘sharps’), an intuitive framework for analyzing substituent effects and activity cliffs in a single congeneric series. A SRP is a pair of compounds that differ only in a single R-group position. ...
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History
- Published In Issue August 25, 2008
- Article ASAPAugust 08, 2008
- Received: April 23, 2008
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Why QSAR Often Disappoints
