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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-Universit├Ąt, 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.


Multi-target compound series matrices.(a) shows a CSM containing 15 inhibitors of 10 carbonic anhydrase (CAR) isoforms. Target coverage of analogs is reflected by increasingly dark blue shading of cells. Substructures distinguishing the core fragments are highlighted in red. The matrix composition is summarized (top left) and the target profile reported (top right). (b) shows a CSM with 44 analogs active against 10 targets (including the hERG anti-target) belonging to three different families. The maximum common core structure (MCS) of the analog series is displayed. For clarity, compound structures are omitted. Target abbreviations: 5-HT; serotonin receptor, ST; serotonin transporter, D; dopamine receptor, hERG; hERG ion channel.
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f7: Multi-target compound series matrices.(a) shows a CSM containing 15 inhibitors of 10 carbonic anhydrase (CAR) isoforms. Target coverage of analogs is reflected by increasingly dark blue shading of cells. Substructures distinguishing the core fragments are highlighted in red. The matrix composition is summarized (top left) and the target profile reported (top right). (b) shows a CSM with 44 analogs active against 10 targets (including the hERG anti-target) belonging to three different families. The maximum common core structure (MCS) of the analog series is displayed. For clarity, compound structures are omitted. Target abbreviations: 5-HT; serotonin receptor, ST; serotonin transporter, D; dopamine receptor, hERG; hERG ion channel.

Mentions: SARMs have also been adapted for the navigation of multi-target activity spaces, which are populated by promiscuous compounds. In this context, promiscuity is defined as the ability of a compound to specifically interact with multiple targets (as opposed to non-specific binding effects)11. Here, the primary purpose of the matrix approach is not SAR analysis, but the systematic exploration of compound promiscuity patterns. Therefore, matrices capturing multi-target activities are generated. Such matrices have been designated as Compound Series Matrices (CSMs)6. CSMs are of interest for chemogenomics applications in which compound-target interactions are systematically explored12. InFigure 7, two exemplary CSMs of different composition and target coverage are shown that reveal different compound promiscuity patterns. In CSMs, data set compounds are color-coded according to the number of targets they are active against (instead of potency-based coloring). InFigure 7a, two structural analogs display very different degrees of promiscuity and inFigure 7b, a center of promiscuity is identified in a sparsely populated matrix. CSMs are designed to mine chemogenomics data sets and also offer immediate suggestions for the design of compounds with different multi-target activities. In addition, it is also readily possible to deconvolute CSMs into individual single-target SARMs, as illustrated inFigure 8. This makes it possible to compare SARMs across different targets and identify compounds that are attractive candidates for testing against additional targets.


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

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

Multi-target compound series matrices.(a) shows a CSM containing 15 inhibitors of 10 carbonic anhydrase (CAR) isoforms. Target coverage of analogs is reflected by increasingly dark blue shading of cells. Substructures distinguishing the core fragments are highlighted in red. The matrix composition is summarized (top left) and the target profile reported (top right). (b) shows a CSM with 44 analogs active against 10 targets (including the hERG anti-target) belonging to three different families. The maximum common core structure (MCS) of the analog series is displayed. For clarity, compound structures are omitted. Target abbreviations: 5-HT; serotonin receptor, ST; serotonin transporter, D; dopamine receptor, hERG; hERG ion channel.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f7: Multi-target compound series matrices.(a) shows a CSM containing 15 inhibitors of 10 carbonic anhydrase (CAR) isoforms. Target coverage of analogs is reflected by increasingly dark blue shading of cells. Substructures distinguishing the core fragments are highlighted in red. The matrix composition is summarized (top left) and the target profile reported (top right). (b) shows a CSM with 44 analogs active against 10 targets (including the hERG anti-target) belonging to three different families. The maximum common core structure (MCS) of the analog series is displayed. For clarity, compound structures are omitted. Target abbreviations: 5-HT; serotonin receptor, ST; serotonin transporter, D; dopamine receptor, hERG; hERG ion channel.
Mentions: SARMs have also been adapted for the navigation of multi-target activity spaces, which are populated by promiscuous compounds. In this context, promiscuity is defined as the ability of a compound to specifically interact with multiple targets (as opposed to non-specific binding effects)11. Here, the primary purpose of the matrix approach is not SAR analysis, but the systematic exploration of compound promiscuity patterns. Therefore, matrices capturing multi-target activities are generated. Such matrices have been designated as Compound Series Matrices (CSMs)6. CSMs are of interest for chemogenomics applications in which compound-target interactions are systematically explored12. InFigure 7, two exemplary CSMs of different composition and target coverage are shown that reveal different compound promiscuity patterns. In CSMs, data set compounds are color-coded according to the number of targets they are active against (instead of potency-based coloring). InFigure 7a, two structural analogs display very different degrees of promiscuity and inFigure 7b, a center of promiscuity is identified in a sparsely populated matrix. CSMs are designed to mine chemogenomics data sets and also offer immediate suggestions for the design of compounds with different multi-target activities. In addition, it is also readily possible to deconvolute CSMs into individual single-target SARMs, as illustrated inFigure 8. This makes it possible to compare SARMs across different targets and identify compounds that are attractive candidates for testing against additional targets.

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-Universit├Ąt, 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.