Cheng Xiang, Zhao Shu-Guang, Xiao Xuan, Chou Kuo-Chen
College of Information Science and Technology, Donghua University, Shanghai 201620, China.
Computer Department, Jingdezhen Ceramic Institute, Jingdezhen 333001, China.
Oncotarget. 2017 Apr 11;8(35):58494-58503. doi: 10.18632/oncotarget.17028. eCollection 2017 Aug 29.
Recommended by the World Health Organization (WHO), drug compounds have been classified into 14 main ATC (Anatomical Therapeutic Chemical) classes according to their therapeutic and chemical characteristics. Given an uncharacterized compound, can we develop a computational method to fast identify which ATC class or classes it belongs to? The information thus obtained will timely help adjusting our focus and selection, significantly speeding up the drug development process. But this problem is by no means an easy one since some drug compounds may belong to two or more than two ATC classes. To address this problem, using the DO (Drug Ontology) approach based on the ChEBI (Chemical Entities of Biological Interest) database, we developed a predictor called iATC-mDO. Subsequently, hybridizing it with an existing drug ATC classifier, we constructed a predictor called iATC-mHyb. It has been demonstrated by the rigorous cross-validation and from five different measuring angles that iATC-mHyb is remarkably superior to the best existing predictor in identifying the ATC classes for drug compounds. To convenience most experimental scientists, a user-friendly web-server for iATC-mHyd has been established at http://www.jci-bioinfo.cn/iATC-mHyb, by which users can easily get their desired results without the need to go through the complicated mathematical equations involved.
根据世界卫生组织（WHO）的建议，药物化合物已根据其治疗和化学特性被分为14个主要的解剖学治疗学化学（ATC）类别。对于一种未表征的化合物，我们能否开发一种计算方法来快速识别它所属的ATC类别？由此获得的信息将及时帮助我们调整重点和选择，显著加快药物开发过程。但这个问题绝非易事，因为一些药物化合物可能属于两个或两个以上的ATC类别。为了解决这个问题，我们基于ChEBI（生物感兴趣的化学实体）数据库，采用药物本体（DO）方法，开发了一个名为iATC-mDO的预测器。随后，将其与现有的药物ATC分类器进行杂交，构建了一个名为iATC-mHyb的预测器。经过严格的交叉验证并从五个不同的测量角度证明，iATC-mHyb在识别药物化合物的ATC类别方面明显优于现有的最佳预测器。为了方便大多数实验科学家，已在http://www.jci-bioinfo.cn/iATC-mHyb建立了一个用户友好的iATC-mHyd网络服务器，通过该服务器用户可以轻松获得他们想要的结果，而无需处理所涉及的复杂数学方程。
