http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Ying Cui,Qinggang Chen,Yaxiao Li,Ling Tang 대한약학회 2017 Archives of Pharmacal Research Vol.40 No.2
Flavonoids exhibit a high affinity for the purifiedcytosolic NBD (C-terminal nucleotide-binding domain) ofP-glycoprotein (P-gp). To explore the affinity of flavonoidsfor P-gp, quantitative structure–activity relationship(QSAR) models were developed using support vectormachines (SVMs). A novel method coupling a modifiedparticle swarm optimization algorithm with randommutation strategy and a genetic algorithm coupled withSVM was proposed to simultaneously optimize the kernelparameters of SVM and determine the subset of optimizedfeatures for the first time. Using DRAGON descriptors torepresent compounds for QSAR, three subsets (training,prediction and external validation set) derived from thedataset were employed to investigate QSAR. Withexcluding of the outlier, the correlation coefficient (R2) ofthe whole training set (training and prediction) was 0.924,and the R2 of the external validation set was 0.941. Theroot-mean-square error (RMSE) of the whole training setwas 0.0588; the RMSE of the cross-validation of theexternal validation set was 0.0443. The mean Q2 value ofleave-many-out cross-validation was 0.824. With moreinformations from results of randomization analysis andapplicability domain, the proposed model is of good predictiveability, stability.