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A survey of across-target bioactivity results of small molecules in PubChem.

Han L, Wang Y, Bryant SH - Bioinformatics (2009)

Bottom Line: This work provides an analysis of across-target bioactivity results in the screening data deposited in PubChem.This analysis also identifies compounds that are bioactive across unrelated targets.This work enables one to select target specific inhibitors, identify promiscuous compounds and better understand the biological mechanisms of target-small molecule interactions.

View Article: PubMed Central - PubMed

Affiliation: National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA.

ABSTRACT
This work provides an analysis of across-target bioactivity results in the screening data deposited in PubChem. Two alternative approaches for grouping-related targets are used to examine a compound's across-target bioactivity. This analysis identifies compounds that are selectively active against groups of protein targets that are identical or similar in sequence. This analysis also identifies compounds that are bioactive across unrelated targets. Statistical distributions of compound' across-target selectivity provide a survey to evaluate target specificity of compounds by deriving and analyzing bioactivity profile across a wide range of biological targets for tested small molecules in PubChem. This work enables one to select target specific inhibitors, identify promiscuous compounds and better understand the biological mechanisms of target-small molecule interactions.

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Distributions of compound activity among 116 target clusters.
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Figure 3: Distributions of compound activity among 116 target clusters.

Mentions: In this analysis, the 267 non-redundant targets were clustered based on their sequence similarity measured by the BLAST (Altschul et al., 1997) algorithm. As a result, 116 target clusters were derived, which include protein families such as kinase, phosphatase, protease and G protein-coupled receptor. Similar to the target identity-based analysis as described above, distributions of compound activity across the derived target clusters were obtained for two datasets as shown in Figure 3. This analysis shows that >50% of the compounds are active only against targets similar in sequences. It also shows that there is a substantial number of compounds revealing activity across non-related or distantly related protein targets. Comparison of the results given in Figures 1 and 3 suggests that the trends of the respective distributions of each dataset resembled each other. Compounds showing selectivity to a single target cluster should include those specific to a single target as well as those which are active to multiple members of the same target family, but otherwise inactive in other target clusters. One example of this would be a group of compounds showing activity across several members of one protease family including Complement factor C1s, Factor XIa, Factor XIIa, Thrombin, Kallikrein-related peptidase and Cathepsin G as shown in Figure 4.Fig. 3.


A survey of across-target bioactivity results of small molecules in PubChem.

Han L, Wang Y, Bryant SH - Bioinformatics (2009)

Distributions of compound activity among 116 target clusters.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2734317&req=5

Figure 3: Distributions of compound activity among 116 target clusters.
Mentions: In this analysis, the 267 non-redundant targets were clustered based on their sequence similarity measured by the BLAST (Altschul et al., 1997) algorithm. As a result, 116 target clusters were derived, which include protein families such as kinase, phosphatase, protease and G protein-coupled receptor. Similar to the target identity-based analysis as described above, distributions of compound activity across the derived target clusters were obtained for two datasets as shown in Figure 3. This analysis shows that >50% of the compounds are active only against targets similar in sequences. It also shows that there is a substantial number of compounds revealing activity across non-related or distantly related protein targets. Comparison of the results given in Figures 1 and 3 suggests that the trends of the respective distributions of each dataset resembled each other. Compounds showing selectivity to a single target cluster should include those specific to a single target as well as those which are active to multiple members of the same target family, but otherwise inactive in other target clusters. One example of this would be a group of compounds showing activity across several members of one protease family including Complement factor C1s, Factor XIa, Factor XIIa, Thrombin, Kallikrein-related peptidase and Cathepsin G as shown in Figure 4.Fig. 3.

Bottom Line: This work provides an analysis of across-target bioactivity results in the screening data deposited in PubChem.This analysis also identifies compounds that are bioactive across unrelated targets.This work enables one to select target specific inhibitors, identify promiscuous compounds and better understand the biological mechanisms of target-small molecule interactions.

View Article: PubMed Central - PubMed

Affiliation: National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA.

ABSTRACT
This work provides an analysis of across-target bioactivity results in the screening data deposited in PubChem. Two alternative approaches for grouping-related targets are used to examine a compound's across-target bioactivity. This analysis identifies compounds that are selectively active against groups of protein targets that are identical or similar in sequence. This analysis also identifies compounds that are bioactive across unrelated targets. Statistical distributions of compound' across-target selectivity provide a survey to evaluate target specificity of compounds by deriving and analyzing bioactivity profile across a wide range of biological targets for tested small molecules in PubChem. This work enables one to select target specific inhibitors, identify promiscuous compounds and better understand the biological mechanisms of target-small molecule interactions.

Show MeSH