Identification of SVM-based classification model, synthesis and evaluation of prenylated flavonoids as vasorelaxant agents.
Support vector machine (SVM) was applied to predict vasorelaxation effect of different structural molecules. A good classification model had been established, and the accuracy in prediction for the training, test, and overall datasets was 93.0%, 82.6%, and 89.5%, respectively. Furthermore, the model was used to predict the activity of a series of prenylated flavonoids. According to the estimated result, eleven molecules 1-11 were selected and synthesized. Their vasodilatory activities were determined experimentally in rat aorta rings that were pretreated with phenylephrine (PE). Structure-activity relationship (SAR) analysis revealed that flavanone derivatives showed the most potent activities, while flavone and chalcone derivatives exhibited medium activities.
Dong
Xiaowu
X
ZJU-ENS Joint Laboratory of Medicinal Chemistry, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Liu
Yujie
Y
Yan
Jingying
J
Jiang
Chaoyi
C
Chen
Jing
J
Liu
Tao
T
Hu
Yongzhou
Y
D000465:Algorithms; D000818:Animals; D001013:Aorta, Thoracic / Q000187:drug effects* / Q000502:physiology; D003198:Computer Simulation; D016208:Databases, Factual; D004305:Dose-Response Relationship, Drug; D005419:Flavonoids / Q000138:chemical synthesis / Q000737:chemistry / Q000494:pharmacology*; D008297:Male; D008956:Models, Chemical; D015394:Molecular Structure; D009924:Organ Culture Techniques; D010656:Phenylephrine / Q000494:pharmacology; D011237:Predictive Value of Tests; D051381:Rats; D017207:Rats, Sprague-Dawley; D013237:Stereoisomerism; D013329:Structure-Activity Relationship; D014662:Vasoconstrictor Agents / Q000494:pharmacology; D014665:Vasodilator Agents / Q000138:chemical synthesis / Q000737:chemistry / Q000494:pharmacology*
D005419:Flavonoids; D014662:Vasoconstrictor Agents; D014665:Vasodilator Agents; D010656:Phenylephrine