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Drug design for neuropathic pain regulation from traditional Chinese medicine.


ABSTRACT: FAAH-like anandamide transporter (FLAT) regulates anandamide transport for hydrolysis and may be an attractive drug target for pain regulation. We aimed to discover potential FLAT antagonists from traditional Chinese medicine (TCM) using virtual screening, ligand-based drug design and molecular dynamics simulation (MD). Guineensine and Retrofractamide A exhibited high Dock Scores in FLAT. Consensus from multiple linear regression (MLR; R(2) = 08973) and support vector machine (SVM; R(2) = 0.7988) showed similar bioactivities for Guineensine and the FAAH-1 inhibitor (9Z)-1-(5-pyridin-2-yl-1,3,4-oxadiazol-2-yl)octadec-9-en-1-one. Contour of Guineensine to CoMFA and CoMSIA features also imply bioactivity. MD revealed shake or vibration in the secondary structure of FLAT complexed with Guineensine and (9Z)-1-(5-pyridin-2-yl-1,3,4-oxadiazol-2-yl)octadec-9-en-1-one. Ligand movement might contribute to protein changes leading to vibration patterns. Violent vibrations leading to an overall decrease in FLAT function could be the underlying mechanism for Guineensine. Here we suggest Guineensine as a drug-like compound with potential application in relieving neuropathic pain by inhibiting FLAT.

SUBMITTER: Tou WI 

PROVIDER: S-EPMC3558695 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Drug design for neuropathic pain regulation from traditional Chinese medicine.

Tou Weng Ieong WI   Chang Su-Sen SS   Lee Cheng-Chun CC   Chen Calvin Yu-Chian CY   Chen Calvin Yu-Chian CY  

Scientific reports 20130130


FAAH-like anandamide transporter (FLAT) regulates anandamide transport for hydrolysis and may be an attractive drug target for pain regulation. We aimed to discover potential FLAT antagonists from traditional Chinese medicine (TCM) using virtual screening, ligand-based drug design and molecular dynamics simulation (MD). Guineensine and Retrofractamide A exhibited high Dock Scores in FLAT. Consensus from multiple linear regression (MLR; R(2) = 08973) and support vector machine (SVM; R(2) = 0.7988  ...[more]

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