A quantitative screening strategy based on activity-content ratio for prioritizing bioactive compounds in medicinal plants
- 1Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, International Cooperative Laboratory of Traditional Chinese Medicine Modernization and Innovative Drug Development of Ministry of Education (MOE) of China, Jinan University, Guangzhou, 510632, China
- 2Corresponding author.
Abstract
Accurately evaluating the intrinsic bioactivity of individual constituents, independent of their abundance, remains a major challenge in natural product screening. To address this, we proposed the activity-content ratio (ACR) as a novel index for direct intrinsic inhibitory potency characterization of constituents. Utilizing an at-line nanofractionation platform, an ACR-based screening method for acetylcholinesterase inhibitors was established. The method was validated using both mixed standards and a complex extract of Corydalis rhizoma alkaloids. Results demonstrated a strong linear correlation ( R 2 > 0.93) between ACR% and IC 50 for 16 active constituents. High-ACR% compounds, such as berberine, palmatine, and dehydrocorydalin, exhibited significant inhibitory activities at nanomolar concentrations. The model's broad applicability was further confirmed by screening Citri reticulatae pericarpium flavonoids for α-glucosidase inhibitors, showing excellent linearity ( R 2 = 0.96) for the five identified active constituents. Notably, rutin displayed the highest ACR% and an IC 50 of 15.21 ± 1.23 μM. The consistent performance of the ACR model across two distinct enzymatic targets and chemical families (alkaloids and flavonoids) demonstrates its reliability and broad applicability. This study provides a reliable and efficient quantitative tool for bioactivity evaluation, which is expected to greatly accelerate the discovery and quality control of bioactive medicinal plants.
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BibTeX
@article{chen2026quantitative,
title = {{A quantitative screening strategy based on activity-content ratio for prioritizing bioactive compounds in medicinal plants}},
author = {Lin Chen and Xinxin Chen and Shengnan Pi and Ditong Huang and Manhuayun Zhai and Jincai Wang and Zhengjin Jiang and Tingting Zhang},
journal = {Journal of Pharmaceutical Analysis},
year = {2026},
month = sep,
doi = {10.1016/j.jpha.2026.101665},
url = {https://doi.org/10.1016/j.jpha.2026.101665},
note = {CC BY},
}
RIS
TY - JOUR
TI - A quantitative screening strategy based on activity-content ratio for prioritizing bioactive compounds in medicinal plants
AU - Lin Chen
AU - Xinxin Chen
AU - Shengnan Pi
AU - Ditong Huang
AU - Manhuayun Zhai
AU - Jincai Wang
AU - Zhengjin Jiang
AU - Tingting Zhang
PY - 2026
DA - 2026/09/01
JO - Journal of Pharmaceutical Analysis
DO - 10.1016/j.jpha.2026.101665
UR - https://doi.org/10.1016/j.jpha.2026.101665
AB - Accurately evaluating the intrinsic bioactivity of individual constituents, independent of their abundance, remains a major challenge in natural product screening. To address this, we proposed the activity-content ratio (ACR) as a novel index for direct intrinsic inhibitory potency characterization of constituents. Utilizing an at-line nanofractionation platform, an ACR-based screening method for acetylcholinesterase inhibitors was established. The method was validated using both mixed standards and a complex extract of Corydalis rhizoma alkaloids. Results demonstrated a strong linear correlation ( R 2 > 0.93) between ACR% and IC 50 for 16 active constituents. High-ACR% compounds, such as berberine, palmatine, and dehydrocorydalin, exhibited significant inhibitory activities at nanomolar concentrations. The model's broad applicability was further confirmed by screening Citri reticulatae pericarpium flavonoids for α-glucosidase inhibitors, showing excellent linearity ( R 2 = 0.96) for the five identified active constituents. Notably, rutin displayed the highest ACR% and an IC 50 of 15.21 ± 1.23 μM. The consistent performance of the ACR model across two distinct enzymatic targets and chemical families (alkaloids and flavonoids) demonstrates its reliability and broad applicability. This study provides a reliable and efficient quantitative tool for bioactivity evaluation, which is expected to greatly accelerate the discovery and quality control of bioactive medicinal plants.
SN - 2095-1779
SN - 2214-0883
ER -