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Figure 5 Workflow for removing duplicate compounds.
The last task in the pre-processing is the removal of duplicate compounds resulting from desalting and normalizing tautomers.
After normalization of the DrugBank database, we used ISIDA Duplicates to identify and remove duplicate compounds from the file [54].
After merging of Set1 and Set 2 compounds, the duplicate compounds are removed from the data and it resulted in 8292 compounds representing Set 3 data set.
Additionally, biochemical databases often contain numerous duplicate compounds [40] and these were identified by Standard InChIKey [41] comparison and removed for computational efficiency.
More recently, Isayev et al. [5] have demonstrated several errors in the AFLOW database including duplicate compounds and incorrect extraction of literature data.
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In general, data curation involves steps like the removal of duplicates, compounds with wrong Lewis structures, compounds for which descriptors could not be calculated, and in case of experimentally measured data the removal of compounds which suffer from errors caused by the measurement process.
After pooling supplier catalogues and filtering for duplicates, compounds that contained unwanted functionalities were removed.
Each experiment was carried out in duplicate and compounds were excluded if duplicates differed more than 10%.
Examples of concentration response curves for duplicate cytotoxic compounds in rat renal proximal tubule cells are shown in Figure 1.
Following duplicate screening, compounds inhibiting prokaryotic NAT enzymes specifically with an IC50 value of less than 10 μM were tested for inhibition of growth of mycobacteria and of Escherichia coli.
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