Predicting Cyclooxygenase Inhibition by Three‐Dimensional Pharmacophoric Profiling. Part I: Model Generation, Validation and Applicability in Ethnopharmacology

Abstract

3D pharmacophore modeling has evolved as an established and state-of-the-art method for performing in-silico predictions of biological activity. Using one single model is limited to single binding modes, while the combination of several models bears a broader application scope. We demonstrate the generation of a complete and predictive 3D model set for cyclooxygenase 1 and 2 inhibitors, along with a selection and validation protocol optimized for parallel virtual screening. This model set was applied to explain the cyclooxygenase activity of an ethnopharmacologically known mixture of natural products, the Thai traditional medicine "Prasaplai". Results show that rationalizing natural product activity by modern in-silico approaches is promising and can be tremendously useful in the identification of the mechanisms of action for known biological effects of complex herbal remedies.

Pharmacophores in Drug Research

“…This, in fact, allows for rapid bio-activity profiling of compounds even before they are synthesized and also will drastically enhance the library design process. Several studies about pharmacophore-based ligand profiling [48][49][50][51] and target fishing [52][53][54] have been published so far. The results indicate that these methods can compete well with other approaches based on scalar descriptors or on molecular docking and scoring.…”

In Silico‐Guided Strategies for the Discovery and Rationalization of Bioactive Natural Products

“…Alternatively, a focused database of the isolated and already biologically tested compounds offers the possibility to rationalize NP activity or identify the mechanisms of action for known biological effects of complex remedies (retrospective application). Recently, Schuster et al (2010a) compiled the Prasaplai database, which was used to elucidate one mechanism of action of Prasaplai (Thai traditional medicine composed of 10 plants, sodium chloride, and camphor). The structural information on NPs from the plants present in Prasaplai was collected from literature.…”

“…The structural information on NPs from the plants present in Prasaplai was collected from literature. Virtual screening using five previously validated pharmacophore models for cyclooxygenase inhibitors (Schuster et al, 2010a) led to a list of Prasaplai constituents, which could act via this target and can thus be responsible for the anti-inflammatory and antiprostaglandin activities of this herbal remedy. Because 50% of the retrieved hits were already known cyclooxygenase inhibitors, it would be promising to explore the remaining, so far untested virtual hits for their biological activity (Waltenberger et al, 2011).…”

Redox and Non-Redox Mechanism ofIn VitroCyclooxygenase Inhibition by Natural Quinones

“…The pharmacophore models generated by Ligand-Scout were then optimized with datasets of known COX inhibi-tors to find as many active compounds as possible, while sorting out inactive decoy substances. For this optimization, a workflow published by Schuster et al was followed [20]. The interaction models were analyzed for their ability to recognize non-redox COX inhibitors from this study.…”