Abstract
The past decade has seen a significant emergence in the availability and use of pathway analysis tools. The workflow that is supported by most of the pathway analysis tools is limited to either of the following:
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a.
a network of genes based on the input data set, or
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b.
the resultant network filtered down by a few criteria such as (but not limited to)
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i.
disease association of the genes in the network;
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ii.
targets known to be the target of one or more launched drugs;
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iii.
targets known to be the target of one or more compounds in clinical trials; and
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iv.
targets reasonably known to be potential candidate or clinical biomarkers.
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i.
Almost all the tools in use today are biased towards the biological side and contain little, if any, information on the chemical inhibitors associated with the components of a given biological network. The limitation resides as follows:
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The fact that the number of inhibitors that have been published or patented is probably several fold (probably greater than 10-fold) more than the number of published protein–protein interactions. Curation of such data is both expensive and time consuming and could impact ROI significantly.
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The non-standardization associated with protein and gene names makes mapping reasonably non-straightforward.
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The number of patented and published inhibitors across target classes increases by over a million per year. Therefore, keeping the databases current becomes a monumental problem.
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Modifications required in the product architectures to accommodate chemistry-related content.
GVK Bio has, over the past 7 years, curated the compound-target data that is necessary for the addition of such compound-centric workflows. This chapter focuses on identification, curation and utility of such data.
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Acknowledgements
The author would like to acknowledge the scientists and curators at GVK BioSciences. In addition, a special note of thanks for the expert advice of Dr JARP Sarma who heads the Informatics group and Nikhil Tamhankar, a key member of the Business Development group.
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© 2009 Humana Press, a part of Springer Science+Business Media, LLC
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Devidas, S. (2009). Curation of Inhibitor-Target Data: Process and Impact on Pathway Analysis. In: Nikolsky, Y., Bryant, J. (eds) Protein Networks and Pathway Analysis. Methods in Molecular Biology, vol 563. Humana Press. https://doi.org/10.1007/978-1-60761-175-2_3
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DOI: https://doi.org/10.1007/978-1-60761-175-2_3
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