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The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets.

Karapetyan K, Batchelor C, Sharpe D, Tkachenko V, Williams AJ - J Cheminform (2015)

Bottom Line: There are presently hundreds of online databases hosting millions of chemical compounds and associated data.As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online.In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set.

View Article: PubMed Central - PubMed

Affiliation: Royal Society of Chemistry, US Office, 904 Tamaras Circle, Wake Forest, NC 27587 USA.

ABSTRACT

Background: There are presently hundreds of online databases hosting millions of chemical compounds and associated data. As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online. In order to help facilitate validation and standardization of chemical structure datasets from various sources we have delivered a freely available internet-based platform to the community for the processing of chemical compound datasets.

Results: The chemical validation and standardization platform (CVSP) both validates and standardizes chemical structure representations according to sets of systematic rules. The chemical validation algorithms detect issues with submitted molecular representations using pre-defined or user-defined dictionary-based molecular patterns that are chemically suspicious or potentially requiring manual review. Each identified issue is assigned one of three levels of severity - Information, Warning, and Error - in order to conveniently inform the user of the need to browse and review subsets of their data. The validation process includes validation of atoms and bonds (e.g., making aware of query atoms and bonds), valences, and stereo. The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file. This platform has been applied to the analysis of a large number of data sets prepared for deposition to our ChemSpider database and in preparation of data for the Open PHACTS project. In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set. CVSP web site is located at http://cvsp.chemspider.com/.

Conclusion: A platform for the validation and standardization of chemical structure representations of various formats has been developed and made available to the community to assist and encourage the processing of chemical structure files to produce more homogeneous compound representations for exchange and interchange between online databases. While the CVSP platform is designed with flexibility inherent to the rules that can be used for processing the data we have produced a recommended rule set based on our own experiences with the large data sets such as DrugBank, ChEMBL, and data sets from ChemSpider.

No MeSH data available.


A depiction of how a chemical structure can change between InChI generation and InChI conversion. The original structure on the left was the hypothetical structure input to the InChI algorithm to generation the InChI string shown at the top of the figure. The conversion of the InChI string back to a visual form of the structure using Accelrys Draw resulted in changes including disconnection of the metal, changing the bonds and the ionization state of the halogen
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Fig1: A depiction of how a chemical structure can change between InChI generation and InChI conversion. The original structure on the left was the hypothetical structure input to the InChI algorithm to generation the InChI string shown at the top of the figure. The conversion of the InChI string back to a visual form of the structure using Accelrys Draw resulted in changes including disconnection of the metal, changing the bonds and the ionization state of the halogen

Mentions: To help to solve the problem of proliferation of multiple non-interchangeable identifiers InChI was developed under the guidance of an IUPAC sanctioned committee as an open structure identifier. The generation of InChIs involves the normalization of the original structure, and its canonicalization and serialization [4]. Standard InChI normalization involves disconnecting metals, the removal/addition of protons, simple tautomer detection/canonicalization and the conversion of relative stereo to absolute, etc. Therefore, an InChI does not actually represent the original structure but its normalized version and an InChI string is not really intended for backward structure generation as it can lead to a molecule different from the one that was used for InChI generation (see Fig. 1). Often this is overlooked and thus there is a potential loss of information when using an InChI as the primary source of the structure rather than the original connection table in a molfile. An example of a hypothetical molecule that was converted to an InChI and then back to a structure using the Accelrys Draw [5] structure drawing application is presented on Fig. 1.Fig. 1


The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets.

Karapetyan K, Batchelor C, Sharpe D, Tkachenko V, Williams AJ - J Cheminform (2015)

A depiction of how a chemical structure can change between InChI generation and InChI conversion. The original structure on the left was the hypothetical structure input to the InChI algorithm to generation the InChI string shown at the top of the figure. The conversion of the InChI string back to a visual form of the structure using Accelrys Draw resulted in changes including disconnection of the metal, changing the bonds and the ionization state of the halogen
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4494041&req=5

Fig1: A depiction of how a chemical structure can change between InChI generation and InChI conversion. The original structure on the left was the hypothetical structure input to the InChI algorithm to generation the InChI string shown at the top of the figure. The conversion of the InChI string back to a visual form of the structure using Accelrys Draw resulted in changes including disconnection of the metal, changing the bonds and the ionization state of the halogen
Mentions: To help to solve the problem of proliferation of multiple non-interchangeable identifiers InChI was developed under the guidance of an IUPAC sanctioned committee as an open structure identifier. The generation of InChIs involves the normalization of the original structure, and its canonicalization and serialization [4]. Standard InChI normalization involves disconnecting metals, the removal/addition of protons, simple tautomer detection/canonicalization and the conversion of relative stereo to absolute, etc. Therefore, an InChI does not actually represent the original structure but its normalized version and an InChI string is not really intended for backward structure generation as it can lead to a molecule different from the one that was used for InChI generation (see Fig. 1). Often this is overlooked and thus there is a potential loss of information when using an InChI as the primary source of the structure rather than the original connection table in a molfile. An example of a hypothetical molecule that was converted to an InChI and then back to a structure using the Accelrys Draw [5] structure drawing application is presented on Fig. 1.Fig. 1

Bottom Line: There are presently hundreds of online databases hosting millions of chemical compounds and associated data.As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online.In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set.

View Article: PubMed Central - PubMed

Affiliation: Royal Society of Chemistry, US Office, 904 Tamaras Circle, Wake Forest, NC 27587 USA.

ABSTRACT

Background: There are presently hundreds of online databases hosting millions of chemical compounds and associated data. As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online. In order to help facilitate validation and standardization of chemical structure datasets from various sources we have delivered a freely available internet-based platform to the community for the processing of chemical compound datasets.

Results: The chemical validation and standardization platform (CVSP) both validates and standardizes chemical structure representations according to sets of systematic rules. The chemical validation algorithms detect issues with submitted molecular representations using pre-defined or user-defined dictionary-based molecular patterns that are chemically suspicious or potentially requiring manual review. Each identified issue is assigned one of three levels of severity - Information, Warning, and Error - in order to conveniently inform the user of the need to browse and review subsets of their data. The validation process includes validation of atoms and bonds (e.g., making aware of query atoms and bonds), valences, and stereo. The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file. This platform has been applied to the analysis of a large number of data sets prepared for deposition to our ChemSpider database and in preparation of data for the Open PHACTS project. In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set. CVSP web site is located at http://cvsp.chemspider.com/.

Conclusion: A platform for the validation and standardization of chemical structure representations of various formats has been developed and made available to the community to assist and encourage the processing of chemical structure files to produce more homogeneous compound representations for exchange and interchange between online databases. While the CVSP platform is designed with flexibility inherent to the rules that can be used for processing the data we have produced a recommended rule set based on our own experiences with the large data sets such as DrugBank, ChEMBL, and data sets from ChemSpider.

No MeSH data available.