In Silico Identification of Potent PPAR- γ Agonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study
المؤلفون المشاركون
Chen, Calvin Yu-Chian
Chen, Kuan-Chung
المصدر
Evidence-Based Complementary and Alternative Medicine
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-19، 19ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-05-26
دولة النشر
مصر
عدد الصفحات
19
التخصصات الرئيسية
الملخص EN
The peroxisome proliferator-activated receptors (PPARs) related to regulation of lipid metabolism, inflammation, cell proliferation, differentiation, and glucose homeostasis by controlling the related ligand-dependent transcription of networks of genes.
They are used to be served as therapeutic targets against metabolic disorder, such as obesity, dyslipidemia, and diabetes; especially, PPAR- γ is the most extensively investigated isoform for the treatment of dyslipidemic type 2 diabetes.
In this study, we filter compounds of traditional Chinese medicine (TCM) using bioactivities predicted by three distinct prediction models before the virtual screening.
For the top candidates, the molecular dynamics (MD) simulations were also utilized to investigate the stability of interactions between ligand and PPAR- γ protein.
The top two TCM candidates, 5-hydroxy-L-tryptophan and abrine, have an indole ring and carboxyl group to form the H-bonds with the key residues of PPAR- γ protein, such as residues Ser289 and Lys367.
The secondary amine group of abrine also stabilized an H-bond with residue Ser289.
From the figures of root mean square fluctuations (RMSFs), the key residues were stabilized in protein complexes with 5-Hydroxy-L-tryptophan and abrine as control.
Hence, we propose 5-hydroxy-L-tryptophan and abrine as potential lead compounds for further study in drug development process with the PPAR- γ protein.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Kuan-Chung& Chen, Calvin Yu-Chian. 2014. In Silico Identification of Potent PPAR- γ Agonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study. Evidence-Based Complementary and Alternative Medicine،Vol. 2014, no. 2014, pp.1-19.
https://search.emarefa.net/detail/BIM-1018213
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Kuan-Chung& Chen, Calvin Yu-Chian. In Silico Identification of Potent PPAR- γ Agonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study. Evidence-Based Complementary and Alternative Medicine No. 2014 (2014), pp.1-19.
https://search.emarefa.net/detail/BIM-1018213
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Kuan-Chung& Chen, Calvin Yu-Chian. In Silico Identification of Potent PPAR- γ Agonists from Traditional Chinese Medicine: A Bioactivity Prediction, Virtual Screening, and Molecular Dynamics Study. Evidence-Based Complementary and Alternative Medicine. 2014. Vol. 2014, no. 2014, pp.1-19.
https://search.emarefa.net/detail/BIM-1018213
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1018213
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر