ArticlePhytomedicine : international journal of phytotherapy and phytopharmacology2011
Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part II: Identification of enzyme inhibitors from Prasaplai, a Thai traditional medicine.
Article in Phytomedicine : international journal of phytotherapy and phytopharmacology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 15 citations in OpenAlex.
- An Evaluation of the Anti-Inflammatory Effects of a Thai Traditional Polyherbal Recipe TPDM6315 in LPS-Induced RAW264.7 Macrophages and TNF-α-Induced 3T3-L1 Adipocytes.Current issues in molecular biology · 2023Article
- Article
- The Efficacy of Thai Herbal Prasaplai Formula for Treatment of Primary Dysmenorrhea: A Short-Term Randomized Controlled Trial.Evidence-based complementary and alternative medicine : eCAM · 2016Article
- Discovery and resupply of pharmacologically active plant-derived natural products: A review.Biotechnology advances · 2015Review
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prasaplai is a medicinal plant mixture that is used in Thailand to treat primary dysmenorrhea, which is characterized by painful uterine contractility caused by a significant increase of prostaglandin release. Cyclooxygenase (COX) represents a key enzyme in the formation of prostaglandins. Former studies revealed that extracts of Prasaplai inhibit COX-1 and COX-2. In this study, a comprehensive literature survey for known constituents of Prasaplai was performed. A multiconformational 3D database was created comprising 683 molecules. Virtual parallel screening using six validated pharmacophore models for COX inhibitors was performed resulting in a hit list of 166 compounds. 46 Prasaplai components with already determined COX activity were used for the external validation of this set of COX pharmacophore models. 57% of these components were classified correctly by the pharmacophore models. These findings confirm that the virtual approach provides a helpful tool (i) to unravel which molecular compounds might be responsible for the COX-inhibitory activity of Prasaplai and (ii) for the fast identification of novel COX inhibitors.
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