Learning the drug target‐likeness of a protein
Learning the drug target‐likeness of a protein
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了解蛋白质的药物靶点相似性
DOI：
10.1002/pmic.200700062
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发表时间：
2007
期刊：
影响因子：
3.4
通讯作者：
Xin Chen
中科院分区：
文献类型：
--
作者：
Huan Xu;Hangyang Xu;Mingzhi Lin;W. Wang;Zi;Jiaju Huang;Yuzong Chen;Xin Chen
目前的药物发现和开发方法在很大程度上依赖于确定和确认适当的靶点；例如，那些具有适销对路和强大疗法的靶点。针对这一问题进行了广泛的努力，并开发了各种方法来确定与疾病相关的基因作为候选基因。在这项工作中，我们以统计学意义表明，成功的药物靶点除了与疾病有关外，还具有与疾病无关的共同特征。例如，在已知靶标和平均蛋白质之间，观察到在功能类别、组织特异性和序列可变性方面的显著差异。这些结果引出了一个有趣的假设：潜在的好的药物靶点应该具有一些我们所希望的特性，我们称之为“药物靶点相似”，这超出了它们与疾病的联系。由于全面的蛋白质特征数据有限，我们试图在序列水平上了解药物的靶向性。结果表明，支持向量机模型能够完全利用序列特征准确区分目标和非目标。我们希望这些令人鼓舞的结果将引发未来系统的蛋白质组规模实验，以收集必要的蛋白质特征数据，以准确和预测地定义“药物靶标相似”，为理解和追求有效的治疗方法提供一个新的视角。
Current drug discovery and development approaches rely extensively on the identification and validation of appropriate targets; for example, those with marketable and robust therapeutics. Wide‐ranging efforts have been directed at this problem and various approaches have been developed to identify disease‐associated genes as candidates. In this work, we show with statistical significance that successful drug targets, in addition to their linkage to disease, share common characteristics that are disease‐independent. For example, marked differences in functional category, tissue specificity, and sequence variability are observed between known targets and average proteins. These results lead to an interesting hypothesis: potentially good drug targets shall have some desired properties, which we refer to as “drug target‐likeness” that are beyond their disease‐associations. Because of the limited availability of comprehensive protein characteristics data, we tried to learn the drug target‐likeness property at the sequence level. Results show that a support vector machine model is able to accurately distinguish targets from nontargets entirely with sequence features. It is our hope that these encouraging results will invite future systematic proteomic scale experiments to gather necessary protein characteristics data for the accurate and predictive definition of “drug target‐likeness”, providing a new perspective toward understanding and pursuing effective therapeutics.
物理化学参数在距离几何和相关三维定量构效关系中的应用：使用大肠杆菌二氢叶酸还原酶抑制剂的演示。
影响因子：
7.3
作者：
Ghose,AK;Crippen,GM
通讯作者：
Crippen,GM
影响因子：
3.8
作者：
Davison, AJ;Dolan, A;Hayward, GS
通讯作者：
Hayward, GS
影响因子：
45.3
作者：
Attia, P;Phan, GQ;Rosenberg, SA
通讯作者：
Rosenberg, SA