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The 'SAR Matrix' method and its extensions for applications in medicinal chemistry and chemogenomics.

Gupta-Ostermann D, Bajorath J - F1000Res (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, D-53113, Germany.

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.

No MeSH data available.


SAR matrix generation.Three model series with three compounds each (A–C,D–F, andG–I) are shown with pKi values (red). In the first step, all compounds are fragmented at a single bond (purple dotted line) producing compound MMPs that yield a common core (key) and a compound specific substituents (values). In the second step, the cores resulting from the first step are further fragmented to obtain core MMPs. The SARM is then generated by combining series with structurally analogous cores that represent individual rows. In addition, columns represent substituents. In each cell, the combination of a core and a substituent defines a unique compound. Compounds present in the data set are indicated by filled cells that are color-coded according to potency using a continuous spectrum from red (low potency) over yellow to green (high). In addition, empty cells indicate virtual compounds. Substructures distinguishing the core fragments are highlighted in red.
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f1: SAR matrix generation.Three model series with three compounds each (A–C,D–F, andG–I) are shown with pKi values (red). In the first step, all compounds are fragmented at a single bond (purple dotted line) producing compound MMPs that yield a common core (key) and a compound specific substituents (values). In the second step, the cores resulting from the first step are further fragmented to obtain core MMPs. The SARM is then generated by combining series with structurally analogous cores that represent individual rows. In addition, columns represent substituents. In each cell, the combination of a core and a substituent defines a unique compound. Compounds present in the data set are indicated by filled cells that are color-coded according to potency using a continuous spectrum from red (low potency) over yellow to green (high). In addition, empty cells indicate virtual compounds. Substructures distinguishing the core fragments are highlighted in red.

Mentions: The most important aspect of SARM design has been the application of dual fragmentation scheme leading to MMP generation at two levels4, as outlined inFigure 1. In the first step, MMPs are generated from data set compounds yielding “compound MMPs”. In the second step, core fragments from compound MMPs are again subjected to fragmentation leading to the generation of “core MMPs”. As a consequence, this hierarchical two-step fragmentation scheme identifies all compound subsets that have structurally analogous cores, i.e., core structures that are only distinguished by a structural modification at a single site. Each subset represents a so-called “structurally analogous matching molecular series” (A_MMS)4. Thus, each A_MMS represents a set of compound series with structurally analogous cores. Individual compounds and/or subsets of compounds can belong to multiple A_MMS, hence providing a high-level structural organization of a compound collection that captures all possible (MMP-based) substructure relationships.


The 'SAR Matrix' method and its extensions for applications in medicinal chemistry and chemogenomics.

Gupta-Ostermann D, Bajorath J - F1000Res (2014)

SAR matrix generation.Three model series with three compounds each (A–C,D–F, andG–I) are shown with pKi values (red). In the first step, all compounds are fragmented at a single bond (purple dotted line) producing compound MMPs that yield a common core (key) and a compound specific substituents (values). In the second step, the cores resulting from the first step are further fragmented to obtain core MMPs. The SARM is then generated by combining series with structurally analogous cores that represent individual rows. In addition, columns represent substituents. In each cell, the combination of a core and a substituent defines a unique compound. Compounds present in the data set are indicated by filled cells that are color-coded according to potency using a continuous spectrum from red (low potency) over yellow to green (high). In addition, empty cells indicate virtual compounds. Substructures distinguishing the core fragments are highlighted in red.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4215758&req=5

f1: SAR matrix generation.Three model series with three compounds each (A–C,D–F, andG–I) are shown with pKi values (red). In the first step, all compounds are fragmented at a single bond (purple dotted line) producing compound MMPs that yield a common core (key) and a compound specific substituents (values). In the second step, the cores resulting from the first step are further fragmented to obtain core MMPs. The SARM is then generated by combining series with structurally analogous cores that represent individual rows. In addition, columns represent substituents. In each cell, the combination of a core and a substituent defines a unique compound. Compounds present in the data set are indicated by filled cells that are color-coded according to potency using a continuous spectrum from red (low potency) over yellow to green (high). In addition, empty cells indicate virtual compounds. Substructures distinguishing the core fragments are highlighted in red.
Mentions: The most important aspect of SARM design has been the application of dual fragmentation scheme leading to MMP generation at two levels4, as outlined inFigure 1. In the first step, MMPs are generated from data set compounds yielding “compound MMPs”. In the second step, core fragments from compound MMPs are again subjected to fragmentation leading to the generation of “core MMPs”. As a consequence, this hierarchical two-step fragmentation scheme identifies all compound subsets that have structurally analogous cores, i.e., core structures that are only distinguished by a structural modification at a single site. Each subset represents a so-called “structurally analogous matching molecular series” (A_MMS)4. Thus, each A_MMS represents a set of compound series with structurally analogous cores. Individual compounds and/or subsets of compounds can belong to multiple A_MMS, hence providing a high-level structural organization of a compound collection that captures all possible (MMP-based) substructure relationships.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, D-53113, Germany.

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.

No MeSH data available.