Phytochemicals in drug discovery-a confluence of tradition and innovation
File(s)
Published version
Author(s)
Chihomvu, Patience
Ganesan, A
Gibbons, Simon
Woollard, Kevin
Hayes, Martin A
Type
Journal Article
Abstract
Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products’ potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. An emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.
Date Issued
2024-08-02
Date Acceptance
2024-07-25
Citation
International Journal of Molecular Sciences, 2024, 25 (16)
ISSN
1661-6596
Publisher
MDPI AG
Journal / Book Title
International Journal of Molecular Sciences
Volume
25
Issue
16
Copyright Statement
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
License URL
Identifier
10.3390/ijms25168792
Subjects
Biochemistry & Molecular Biology
Chemistry
Chemistry, Multidisciplinary
COMBINATION
COVID-19
DIVERSITY
DOCKING
EFFICACY
IN-VITRO
Life Sciences & Biomedicine
natural products
NATURAL-PRODUCTS
Physical Sciences
phytochemicals
PHYTOCOMPOUNDS
Science & Technology
STRATEGIES
STRUCTURAL BIOLOGY
traditional medicine
Publication Status
Published
Article Number
8792
Date Publish Online
2024-08-13