JOURNAL ARTICLE

A comprehensive review of phytochemistry, pharmacology and quality control of plants from the genus Viola.

  • Published In: Journal of Pharmacy & Pharmacology, 2023, v. 75, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zhang, Qing; Wang Qing; Chen, Suiqing 3 of 3

Abstract

This article provides a comprehensive review of the genus *Viola* (family Violaceae), focusing on its phytochemistry, pharmacology, and quality control. Over 370 compounds have been identified from *Viola* species, including flavonoids, coumarins, alkaloids, lignans, sesquiterpenes, triterpenoids, sterols, fatty acids, phenolic acids, and notably cyclotides—cyclic peptides with diverse bioactivities. Pharmacological studies demonstrate that *Viola* plants exhibit antibacterial, antiviral, antioxidant, anti-inflammatory, antitumor, neuroprotective, hepatoprotective, and other effects, with some extracts and compounds showing activity against drug-resistant bacteria and viruses such as HIV and influenza. Quality control methods, primarily involving chromatographic and spectroscopic techniques, have been developed mainly for *Viola yedoensis* and *Viola tianshanica*, but are limited for other species. The review highlights the need for further research on toxicity, pharmacokinetics, polysaccharides, and quality control across more *Viola* species to support their safe and effective clinical use.

Additional Information

  • Source:Journal of Pharmacy & Pharmacology. 2023/01, Vol. 75, Issue 1, p1
  • Document Type:Article
  • Subject Area:Complementary and Alternative Medicine
  • Publication Date:2023
  • ISSN:0022-3573
  • DOI:10.1093/jpp/rgac041
  • Accession Number:162356457
  • Copyright Statement:Copyright of Journal of Pharmacy & Pharmacology is the property of Oxford University Press / USA 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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