Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam, 13488, South Korea.
Institute of Basic Medical Sciences, School of Medicine, CHA University, Seongnam, 13488, South Korea.
BMC Med Genomics. 2023 Jan 30;16(1):17. doi: 10.1186/s12920-023-01444-8.
Drugs produce pharmaceutical and adverse effects that arise from the complex relationship between drug targets and signatures; by considering such relationships, we can begin to understand the cellular mechanisms of drugs. In this study, we selected 463 genes from the DSigDB database corresponding to targets and signatures for 382 FDA-approved drugs with both protein binding information for a drug-target score (KDTN, i.e., the degree to which the protein encoded by the gene binds to a number of drugs) and microarray signature information for a drug-sensitive score (KDSN, i.e., the degree to which gene expression is stimulated by the drug). Accordingly, we constructed two drug-gene bipartite network models, a drug-target network and drug-signature network, which were merged into a multidimensional model. Analysis revealed that the KDTN and KDSN were in mutually exclusive and reciprocal relationships in terms of their biological network structure and gene function. A symmetric balance between the KDTN and KDSN of genes facilitates the possibility of therapeutic drug effects in whole genome. These results provide new insights into the relationship between drugs and genes, specifically drug targets and drug signatures.
药物会产生药物作用和不良反应，这些作用和不良反应源于药物靶点和特征之间的复杂关系；通过考虑这些关系，我们可以开始了解药物的细胞机制。在这项研究中，我们从 DSigDB 数据库中选择了 463 个基因，这些基因对应着 382 种 FDA 批准药物的靶点和特征，这些药物具有药物-靶点评分（KDTN，即基因编码的蛋白质与多种药物结合的程度）的蛋白质结合信息和药物敏感评分（KDSN，即基因表达受药物刺激的程度）的微阵列特征信息。因此，我们构建了两个药物-基因二分网络模型，一个是药物-靶点网络，另一个是药物-特征网络，这两个网络被合并成一个多维模型。分析表明，KDTN 和 KDSN 在生物网络结构和基因功能方面是相互排斥和相互关联的。基因的 KDTN 和 KDSN 之间的对称平衡有助于在整个基因组中产生治疗药物效应的可能性。这些结果为药物和基因之间的关系，特别是药物靶点和药物特征之间的关系提供了新的见解。
