Target-independent prediction of drug synergies using only drug lipophilicity.
Target-independent prediction of drug synergies using only drug lipophilicity.
复制标题
DOI：
10.1021/ci500276x
复制
发表时间：
2014-08-25
影响因子：
5.6
通讯作者：
Cokol M
中科院分区：
文献类型：
--
作者：
Yilancioglu K;Weinstein ZB;Meydan C;Akhmetov A;Toprak I;Durmaz A;Iossifov I;Kazan H;Roth FP;Cokol M
Physicochemical properties of compounds have been instrumental in selecting lead compounds with increased drug-likeness. However, the relationship between physicochemical properties of constituent drugs and the tendency to exhibit drug interaction has not been systematically studied. We assembled physicochemical descriptors for a set of antifungal compounds (“drugs”) previously examined for interaction. Analyzing the relationship between molecular weight, lipophilicity, H-bond donor, and H-bond acceptor values for drugs and their propensity to show pairwise antifungal drug synergy, we found that combinations of two lipophilic drugs had a greater tendency to show drug synergy. We developed a more refined decision tree model that successfully predicted drug synergy in stringent cross-validation tests based on only lipophilicity of drugs. Our predictions achieved a precision of 63% and allowed successful prediction for 58% of synergistic drug pairs, suggesting that this phenomenon can extend our understanding for a substantial fraction of synergistic drug interactions. We also generated and analyzed a large-scale synergistic human toxicity network, in which we observed that combinations of lipophilic compounds show a tendency for increased toxicity. Thus, lipophilicity, a simple and easily determined molecular descriptor, is a powerful predictor of drug synergy. It is well established that lipophilic compounds (i) are promiscuous, having many targets in the cell, and (ii) often penetrate into the cell via the cellular membrane by passive diffusion. We discuss the positive relationship between drug lipophilicity and drug synergy in the context of potential drug synergy mechanisms.
登录
查看更多内容
影响因子：
9.9
作者：
Nelander, Sven;Wang, Weiqing;Nilsson, Bjoern;She, Qing-Bai;Pratilas, Christine;Rosen, Neal;Gennemark, Peter;Sander, Chris
通讯作者：
Sander, Chris
ASDCD：抗真菌协同药物组合数据库
影响因子：
3.7
作者：
Chen X;Ren B;Chen M;Liu MX;Ren W;Wang QX;Zhang LX;Yan GY
通讯作者：
Yan GY
DOI：
10.1021/ci020048r
发表时间：
2003-01-01
期刊：
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
影响因子：
--
作者：
Poroikov, VV;Filimonov, DA;Nicklaus, MC
通讯作者：
Nicklaus, MC
影响因子：
0.8
作者：
Pignatello R;Musumeci T;Basile L;Carbone C;Puglisi G
通讯作者：
Puglisi G
影响因子：
9.9
作者：
Lehar, Joseph;Zimmermann, Grant R.;Keith, Curtis T.
通讯作者：
Keith, Curtis T.