关键词: 药物-靶标相互作用, 多标记学习, 多信息融合, 药物-靶标相互作用网络, 药物相似性

Abstract: Drug-target association prediction is researched. PDML based on weak label learning and multi-information fusion is proposed to find new drug-target interactions from human enzymes, ion channels, GPCRs and nuclear receptors. The performance of the proposed method makes better than the methods provided by Yamanishi, RLSMDA, LapRLS and NetCBP in terms of sensitivity, specificity, AUC values and AUPR values except that the AUC values of the model slightly decrease in nuclear receptor dataset compared to LapRLS. The five drug-target interaction pairs with highest scores can be extracted and validated by available public database DrugBank, SuperTarget and KEGG.

Key words: drug-target interaction, multi-label learning, multi-information fusion, drug-target interaction network, drug similarity