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Predicting the points of interaction of small molecules in the NF-κB pathway.

Patel Y, Heyward CA, White MR, Kell DB - BMC Syst Biol (2011)

Bottom Line: Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis.The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway.The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.

ABSTRACT

Background: The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway.

Results: Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis.

Conclusions: The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis.

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Distribution of Compounds in a Representation of Chemical Space. The three principle components were calculated from 184 2D descriptors in MOE[21] and describe 51.1% of the variance. Type of interaction: orange = IKK inhibitors; pink = ROS interactions; blue = DNA interaction; green = inhibits translocation; yellow = increases IκB degradation & phosphorylation; yellow = decreases IκB degradation & phosphorylation; black = unknown. The compounds with unknown interactions in the area A all come from series of compounds based on Resveratrol[25] (bottom).
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Figure 3: Distribution of Compounds in a Representation of Chemical Space. The three principle components were calculated from 184 2D descriptors in MOE[21] and describe 51.1% of the variance. Type of interaction: orange = IKK inhibitors; pink = ROS interactions; blue = DNA interaction; green = inhibits translocation; yellow = increases IκB degradation & phosphorylation; yellow = decreases IκB degradation & phosphorylation; black = unknown. The compounds with unknown interactions in the area A all come from series of compounds based on Resveratrol[25] (bottom).

Mentions: A set of 460 small molecules that interact with the NF-κB pathway were obtained from the literature. This involved an extensive literature search with additional searches for chemical structures as many of the biological references only refer to compounds that interact with the NF-κB pathway by name (not necessarily the IUPAC name). Structures, SMILES and references for each compound can be found in Additional Files 1. Chiral information has been included where known, but this data was not available for all the compounds (and also the reason why only topological descriptors have been used). The compounds in the set vary greatly in terms of size and functional groups present. Figure 3 shows the distribution of the compounds in a representation of chemical space.


Predicting the points of interaction of small molecules in the NF-κB pathway.

Patel Y, Heyward CA, White MR, Kell DB - BMC Syst Biol (2011)

Distribution of Compounds in a Representation of Chemical Space. The three principle components were calculated from 184 2D descriptors in MOE[21] and describe 51.1% of the variance. Type of interaction: orange = IKK inhibitors; pink = ROS interactions; blue = DNA interaction; green = inhibits translocation; yellow = increases IκB degradation & phosphorylation; yellow = decreases IκB degradation & phosphorylation; black = unknown. The compounds with unknown interactions in the area A all come from series of compounds based on Resveratrol[25] (bottom).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3050742&req=5

Figure 3: Distribution of Compounds in a Representation of Chemical Space. The three principle components were calculated from 184 2D descriptors in MOE[21] and describe 51.1% of the variance. Type of interaction: orange = IKK inhibitors; pink = ROS interactions; blue = DNA interaction; green = inhibits translocation; yellow = increases IκB degradation & phosphorylation; yellow = decreases IκB degradation & phosphorylation; black = unknown. The compounds with unknown interactions in the area A all come from series of compounds based on Resveratrol[25] (bottom).
Mentions: A set of 460 small molecules that interact with the NF-κB pathway were obtained from the literature. This involved an extensive literature search with additional searches for chemical structures as many of the biological references only refer to compounds that interact with the NF-κB pathway by name (not necessarily the IUPAC name). Structures, SMILES and references for each compound can be found in Additional Files 1. Chiral information has been included where known, but this data was not available for all the compounds (and also the reason why only topological descriptors have been used). The compounds in the set vary greatly in terms of size and functional groups present. Figure 3 shows the distribution of the compounds in a representation of chemical space.

Bottom Line: Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis.The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway.The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.

ABSTRACT

Background: The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway.

Results: Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis.

Conclusions: The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis.

Show MeSH