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Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models

Screening of bioactive components is important for modernization and quality control of herbal medicines, while the traditional bioassay-guided phytochemical approach is time-consuming and laborious. The presented study proposes a strategy for rapid screening of active components from herbal medicin...

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Autores principales: Yuan, Xiao-Yan, Wang, Meng, Lei, Sheng, Yang, Qian-Xu, Liu, Yan-Qiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6151442/
https://www.ncbi.nlm.nih.gov/pubmed/29048399
http://dx.doi.org/10.3390/molecules22101767
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author Yuan, Xiao-Yan
Wang, Meng
Lei, Sheng
Yang, Qian-Xu
Liu, Yan-Qiu
author_facet Yuan, Xiao-Yan
Wang, Meng
Lei, Sheng
Yang, Qian-Xu
Liu, Yan-Qiu
author_sort Yuan, Xiao-Yan
collection PubMed
description Screening of bioactive components is important for modernization and quality control of herbal medicines, while the traditional bioassay-guided phytochemical approach is time-consuming and laborious. The presented study proposes a strategy for rapid screening of active components from herbal medicines. As a case study, the quantitative pattern–activity relationship (QPAR) between compounds and the osteoclastic inhibitory effect of Herba epimedii, a widely used herbal medicine in China, were investigated based on joint models. For model construction, standard mixtures data showed that the joint-action models are better than the partial least-squares (PLS) model. Then, the Good2bad value, which could reflect components’ importance based on Monte Carlo sampling, was coupled with the joint-action models for screening of active components. A compound (baohuoside I) and a component composed of compounds with retention times in the 6.9–7.9 min range were selected by our method. Their inhibition rates were higher than icariin, the key bioactive compound in Herba epimedii, which could inhibit osteoclast differentiation and bone resorption in a previous study. Meanwhile, the half-maximal effective concentration, namely, EC(50) value of the selected component was 7.54 μg/mL, much smaller than that of baohuoside I—77 μg/mL—which indicated that there is synergistic action between compounds in the selected component. The results clearly show our proposed method is simple and effective in screening the most-bioactive components and compounds, as well as drug-lead components, from herbal medicines.
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spelling pubmed-61514422018-11-13 Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models Yuan, Xiao-Yan Wang, Meng Lei, Sheng Yang, Qian-Xu Liu, Yan-Qiu Molecules Article Screening of bioactive components is important for modernization and quality control of herbal medicines, while the traditional bioassay-guided phytochemical approach is time-consuming and laborious. The presented study proposes a strategy for rapid screening of active components from herbal medicines. As a case study, the quantitative pattern–activity relationship (QPAR) between compounds and the osteoclastic inhibitory effect of Herba epimedii, a widely used herbal medicine in China, were investigated based on joint models. For model construction, standard mixtures data showed that the joint-action models are better than the partial least-squares (PLS) model. Then, the Good2bad value, which could reflect components’ importance based on Monte Carlo sampling, was coupled with the joint-action models for screening of active components. A compound (baohuoside I) and a component composed of compounds with retention times in the 6.9–7.9 min range were selected by our method. Their inhibition rates were higher than icariin, the key bioactive compound in Herba epimedii, which could inhibit osteoclast differentiation and bone resorption in a previous study. Meanwhile, the half-maximal effective concentration, namely, EC(50) value of the selected component was 7.54 μg/mL, much smaller than that of baohuoside I—77 μg/mL—which indicated that there is synergistic action between compounds in the selected component. The results clearly show our proposed method is simple and effective in screening the most-bioactive components and compounds, as well as drug-lead components, from herbal medicines. MDPI 2017-10-19 /pmc/articles/PMC6151442/ /pubmed/29048399 http://dx.doi.org/10.3390/molecules22101767 Text en © 2017 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yuan, Xiao-Yan
Wang, Meng
Lei, Sheng
Yang, Qian-Xu
Liu, Yan-Qiu
Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models
title Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models
title_full Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models
title_fullStr Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models
title_full_unstemmed Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models
title_short Rapid Screening of Active Components with an Osteoclastic Inhibitory Effect in Herba epimedii Using Quantitative Pattern–Activity Relationships Based on Joint-Action Models
title_sort rapid screening of active components with an osteoclastic inhibitory effect in herba epimedii using quantitative pattern–activity relationships based on joint-action models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6151442/
https://www.ncbi.nlm.nih.gov/pubmed/29048399
http://dx.doi.org/10.3390/molecules22101767
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