Cargando…
Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy
Target identification is a crucial process for advancing natural products and drug leads development, which is often the most challenging and time-consuming step. However, the putative biological targets of natural products obtained from traditional prediction studies are also informatively redundan...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657499/ https://www.ncbi.nlm.nih.gov/pubmed/34884711 http://dx.doi.org/10.3390/ijms222312908 |
_version_ | 1784612517973065728 |
---|---|
author | Wu, Xunxun Li, Xiaokun Yang, Chunxue Diao, Yong |
author_facet | Wu, Xunxun Li, Xiaokun Yang, Chunxue Diao, Yong |
author_sort | Wu, Xunxun |
collection | PubMed |
description | Target identification is a crucial process for advancing natural products and drug leads development, which is often the most challenging and time-consuming step. However, the putative biological targets of natural products obtained from traditional prediction studies are also informatively redundant. Thus, how to precisely identify the target of natural products is still one of the major challenges. Given the shortcomings of current target identification methodologies, herein, a novel in silico docking and DARTS prediction strategy was proposed. Concretely, the possible molecular weight was detected by DARTS method through examining the protected band in SDS-PAGE. Then, the potential targets were obtained from screening and identification through the PharmMapper Server and TargetHunter method. In addition, the candidate target Src was further validated by surface plasmon resonance assay, and the anti-apoptosis effects of kaempferol against myocardial infarction were further confirmed by in vitro and in vivo assays. Collectively, these results demonstrated that the integrated strategy could efficiently characterize the targets, which may shed a new light on target identification of natural products. |
format | Online Article Text |
id | pubmed-8657499 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86574992021-12-10 Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy Wu, Xunxun Li, Xiaokun Yang, Chunxue Diao, Yong Int J Mol Sci Article Target identification is a crucial process for advancing natural products and drug leads development, which is often the most challenging and time-consuming step. However, the putative biological targets of natural products obtained from traditional prediction studies are also informatively redundant. Thus, how to precisely identify the target of natural products is still one of the major challenges. Given the shortcomings of current target identification methodologies, herein, a novel in silico docking and DARTS prediction strategy was proposed. Concretely, the possible molecular weight was detected by DARTS method through examining the protected band in SDS-PAGE. Then, the potential targets were obtained from screening and identification through the PharmMapper Server and TargetHunter method. In addition, the candidate target Src was further validated by surface plasmon resonance assay, and the anti-apoptosis effects of kaempferol against myocardial infarction were further confirmed by in vitro and in vivo assays. Collectively, these results demonstrated that the integrated strategy could efficiently characterize the targets, which may shed a new light on target identification of natural products. MDPI 2021-11-29 /pmc/articles/PMC8657499/ /pubmed/34884711 http://dx.doi.org/10.3390/ijms222312908 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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/). |
spellingShingle | Article Wu, Xunxun Li, Xiaokun Yang, Chunxue Diao, Yong Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy |
title | Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy |
title_full | Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy |
title_fullStr | Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy |
title_full_unstemmed | Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy |
title_short | Target Characterization of Kaempferol against Myocardial Infarction Using Novel In Silico Docking and DARTS Prediction Strategy |
title_sort | target characterization of kaempferol against myocardial infarction using novel in silico docking and darts prediction strategy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657499/ https://www.ncbi.nlm.nih.gov/pubmed/34884711 http://dx.doi.org/10.3390/ijms222312908 |
work_keys_str_mv | AT wuxunxun targetcharacterizationofkaempferolagainstmyocardialinfarctionusingnovelinsilicodockinganddartspredictionstrategy AT lixiaokun targetcharacterizationofkaempferolagainstmyocardialinfarctionusingnovelinsilicodockinganddartspredictionstrategy AT yangchunxue targetcharacterizationofkaempferolagainstmyocardialinfarctionusingnovelinsilicodockinganddartspredictionstrategy AT diaoyong targetcharacterizationofkaempferolagainstmyocardialinfarctionusingnovelinsilicodockinganddartspredictionstrategy |