This bucket list paper draws comparisons between three commercially available pharmacophore generation programs. All three programs are extensively described. The programs are then compared on their ability to identify the target pharmacophore which was a known pharmacophore, from Relibase+ and the literature, for five different proteins that had a vast collection of crystallographic data. The pharmacophoric features that were of interest include hydrogen-bond acceptors and donors, positive and negatively charged groups and hydrophobic centres. Two separate evaluations were performed, the first was using a rigid search and the second a flexible search. It is difficult to evaluate how good each of this methods were at generating the target pharmacophores, therefore, two criteria were used to judge. Firstly, the RMSD between the found pharmacophores and the target pharmacophore was calculated. The second method was to identify the number of “misses” that occurred, either a feature was missing or a wrong functional group was assigned to the pharmacophore. The generate pharmacophores can then be scored and ranked according to these two criteria. For all five datasets each of the results generated by each method are discussed in detail. These results indicated that Catalyst and GASP outperformed DISCO for all five datasets. GASP ranked first in three out of five cases and Catalyst ranked first in the other two cases. Both of these methodologies identified the target pharmacophore quickly as they were found within the first ten solutions.
A comparison of the pharmacophore identification programs:
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