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Linking the Resource Description Framework to cheminformatics and proteochemometrics.

Willighagen EL, Alvarsson J, Andersson A, Eklund M, Lampa S, Lapins M, Spjuth O, Wikberg JE - J Biomed Semantics (2011)

Bottom Line: Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet.Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility.The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

View Article: PubMed Central - HTML - PubMed

Affiliation: Uppsala University, Department of Pharmaceutical Biosciences, Box 591, SE-751 24 Uppsala, Sweden. egon.willighagen@farmbio.uu.se.

ABSTRACT

Background: Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF) and related methods show to be sufficiently versatile to change that situation.

Results: The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including cheminformatics, QSAR modeling and proteochemometrics. Applications are presented that link RDF technologies to methods from statistics and cheminformatics, including data aggregation, visualization, chemical identification, and property prediction. They demonstrate how this can be done using various existing RDF standards and cheminformatics libraries. For example, we show how IC50 and Ki values are modeled for a number of biological targets using data from the ChEMBL database.

Conclusions: We have shown that existing RDF standards can suitably be integrated into existing molecular chemometrics methods. Platforms that unite these technologies, like Bioclipse, makes this even simpler and more transparent. Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility. The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

No MeSH data available.


Related in: MedlinePlus

Correlation of measured interaction activity versus predicted interaction activity. The correlation is according to a 7-fold cross-validation of the ion channel inhibition model. Activity is expressed as negative logarithm of Ki or IC50.
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Figure 12: Correlation of measured interaction activity versus predicted interaction activity. The correlation is according to a 7-fold cross-validation of the ion channel inhibition model. Activity is expressed as negative logarithm of Ki or IC50.

Mentions: The predictive ability of the induced model was estimated by 7-fold cross-validation, the correlation coefficient between the predicted and experimentally determined values being 0.79 (see Figure 12). The model revealed the most important descriptors for explaining the activity of ion channel inhibitors to be MLOGP (Moriguchi octanol-water partition coefficient), MR (Ghose-Crippen molar refractivity), descriptors of atom centered fragments and functional groups (such as H-046, C-001, C-006, C-033, O-025, O-060, nCaR, nNO2Ph, nNHR, nCrHR; see [48] for explanation of fragment descriptors) and size-related descriptors (molecular weight and mean atomic van der Waals volume). The model also identified molecular properties delineating selective inhibitors of calcium channels from inhibitors of sodium channels.


Linking the Resource Description Framework to cheminformatics and proteochemometrics.

Willighagen EL, Alvarsson J, Andersson A, Eklund M, Lampa S, Lapins M, Spjuth O, Wikberg JE - J Biomed Semantics (2011)

Correlation of measured interaction activity versus predicted interaction activity. The correlation is according to a 7-fold cross-validation of the ion channel inhibition model. Activity is expressed as negative logarithm of Ki or IC50.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105498&req=5

Figure 12: Correlation of measured interaction activity versus predicted interaction activity. The correlation is according to a 7-fold cross-validation of the ion channel inhibition model. Activity is expressed as negative logarithm of Ki or IC50.
Mentions: The predictive ability of the induced model was estimated by 7-fold cross-validation, the correlation coefficient between the predicted and experimentally determined values being 0.79 (see Figure 12). The model revealed the most important descriptors for explaining the activity of ion channel inhibitors to be MLOGP (Moriguchi octanol-water partition coefficient), MR (Ghose-Crippen molar refractivity), descriptors of atom centered fragments and functional groups (such as H-046, C-001, C-006, C-033, O-025, O-060, nCaR, nNO2Ph, nNHR, nCrHR; see [48] for explanation of fragment descriptors) and size-related descriptors (molecular weight and mean atomic van der Waals volume). The model also identified molecular properties delineating selective inhibitors of calcium channels from inhibitors of sodium channels.

Bottom Line: Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet.Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility.The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

View Article: PubMed Central - HTML - PubMed

Affiliation: Uppsala University, Department of Pharmaceutical Biosciences, Box 591, SE-751 24 Uppsala, Sweden. egon.willighagen@farmbio.uu.se.

ABSTRACT

Background: Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF) and related methods show to be sufficiently versatile to change that situation.

Results: The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including cheminformatics, QSAR modeling and proteochemometrics. Applications are presented that link RDF technologies to methods from statistics and cheminformatics, including data aggregation, visualization, chemical identification, and property prediction. They demonstrate how this can be done using various existing RDF standards and cheminformatics libraries. For example, we show how IC50 and Ki values are modeled for a number of biological targets using data from the ChEMBL database.

Conclusions: We have shown that existing RDF standards can suitably be integrated into existing molecular chemometrics methods. Platforms that unite these technologies, like Bioclipse, makes this even simpler and more transparent. Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility. The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

No MeSH data available.


Related in: MedlinePlus