DOI: http://dx.doi.org/10.18203/2319-2003.ijbcp20180657

Analgesic activity of Alpinia galanga extract in mice models and TNF-alpha receptor computational docking analysis on its leads with pharmacokinetics prediction

K. R. Subash, G. Francis Britto, Katari Sudheer Kumar, Amineni Umamaheshwari, Vijaya Chandra Reddy Konda, Bhanu Prakash G.

Abstract


Background: Alpinia galanga is an ayurvedic herb recognized and used across many traditional medicine systems for its analgesic and anti-inflammatory activity. The present study scientifically validates the potential anti nociceptive action of ethanolic extract of Alpinia galanga by chemical, neurogenic and inflammatory nociception model in mice followed by identification of potential lead compound by computational analysis.

Methods: The assessment of anti nociceptive action is evaluated by Acetic acid induced abdominal constrictions and Formalin assay on ethonolic extract of Alpinia galanga, followed by 20 compounds with known chemical structure of Alpinia galanga is subjected to computational analysis to predict possible lead compound with desirable pharmacokinetic and drug like features.

Results: The percentage inhibition rate of Aspirin (100mg/kg) was 82.15% compared to Alpinia galanga (100mg/kg) 19.63%, (200mg/kg) 33.02% and (400mg/kg) 57.13% by acetic acid induced abdominal constrictions antinociceptive mice model. Alpinia galanga 400mg/kg (71.70%) had comparable percentage inhibition of nociception to standard group indomethacin (88.71%) in formalin induced nociceptive mice model. Among 20 compounds screened for pharmacokinetic and drug like features, Galanal B had the binding free energy -56.664 when compared to control compound 2AZ5-56.000.

Conclusions: The Alpinia galanga extract had significant anti nociceptive activity and followed by computational analysis of 20 compounds with known chemical structure predicted Galanal B as lead compound with best insilico pharmacokinetic and drug like features.


Keywords


Alpinia galanga, Formalin assay, Insilico, Nociception, QSAR

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