JOURNAL ARTICLE

IN VITRO ANTIOBESITY ACTIVITY OF SOME PLANTS THROUGH A MODIFIED LIPASE INHIBITION ASSAY.

  • Published In: Indian Drugs, 2024, v. 61, n. 4. P. 72 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Radheshyam; Basnal, Bhawna; Gauniya, Priyanka; Semalty, Mona; Semalty, Ajay 3 of 3

Abstract

The objective of the present study was to evaluate the antiobesity potential of various plant (leaves or seed) extracts through a modified in vitro lipase inhibitory activity assay. Dimethyl sulphoxide (DMSO, negative control or solvent) extracts as cold infusion of leaves and seeds of some plants were studied for lipase inhibitory potential using porcine pancreatic lipase enzyme, p-nitro phenyl acetate and orlistat (as positive control or standard inhibitor). Among the leaves, the Urtica dioica showed the best pancreatic lipase inhibition activity (52.0 %). On the other hand, among the seeds, Trachyspermum ammi showed the highest per cent lipase inhibition (91.68 %). Among six leaves' and seven seeds' extract, it was evident that the seeds showed better pancreatic lipase inhibition activity over the leaves in the study. The lipase inhibition was found to be in the range of 34.43 to 91.68 % for the plants in study. DMSO extract of the plants under the study showed significant pancreatic lipase inhibitory activity indicating strong antiobesity activity. Therefore, the plants can be further investigated for the identification and isolation of chief bioactive constituents for developing the lead molecules for obesity treatment. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Indian Drugs. 2024/04, Vol. 61, Issue 4, p72
  • Document Type:Article
  • Subject Area:Complementary and Alternative Medicine
  • Publication Date:2024
  • ISSN:0019-462X
  • DOI:10.53879/id.61.04.14175
  • Accession Number:177332973
  • Copyright Statement:Copyright of Indian Drugs is the property of Indian Drug Manufacturers' Association (IDMA) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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