Abstract
We describe the 'Structure-Activity Relationship (SAR) Matrix' (SARM) methodology that is based upon a special two-step application of the matched molecular pair (MMP) formalism. The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets. It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces. The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.
Highlights
Growing numbers of active compounds provide a critically important knowledge base for medicinal chemistry and challenge Structure-Activity Relationship (SAR) analysis[1]
Because Structure-Activity Relationship Matrix (SARM) resemble R-group tables, they are readily accessible to medicinal chemists who can inspect individual compounds and their relationships to others
Primary reasons for discussing the different aspects and applications of SARMs in context have been to expose this approach to a wider drug development audience and provide an example for the data- and application-driven evolution of a computational medicinal chemistry method
Summary
The ‘SAR Matrix’ method and its extensions for applications in medicinal chemistry and chemogenomics [version 1; peer review: 2 approved].
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