Discovery and development of TRPV1 antagonists as non-opioid analgesics for pain treatment is an area of intense research in modern medicinal chemistry.This study was aimed to find several common pharmacophore patterns shared by potent TRPV1 antagonists. A dataset formed by 201 compounds obtained from ChEMBL was clustered based on the distribution of pharmacophoric features. For each cluster several models were built and validated using 3 different sets of compounds: a customized decoy set, a set of drugs currently in clinical trials, as well as inactive TRPV1 ligands extracted from the literature. The best models obtained were used for virtual screening of the Life Chemicals Database. Most of the chemical scaffolds represented in the top 1% ranked compounds were also found to have high SHED similarity to the most active compounds of the training set. We acknowledge financial support provided by the Austrian Science Fund grant n�W1232.

Pharmacophore models of competitive TRPV1 antagonists based on open data

245th National Meeting (2013)

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