Bio-X Center, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.
PLoS One. 2010 Mar 8;5(3):e9568. doi: 10.1371/journal.pone.0009568.
Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer's disease (AD) drug-oriented chemical-protein interactome (CPI) using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE), and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER) and histone deacetylase (HDAC), which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover "behind-the-scenes" aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm.
药物不可避免地不仅会影响其预期的蛋白质靶标,还会影响其他蛋白质。在这项研究中,我们假设具有相同治疗效果的药物不仅通过靶向已知的药物靶点,而且通过与相同隐匿靶点的意外相互作用,具有共同的治疗机制。通过构建和挖掘针对阿尔茨海默病(AD)的药物导向化学-蛋白质相互作用网络(CPI),我们使用了一组已知的 10 种治疗 AD 的药物分子矩阵,针对 401 个人类蛋白质口袋,发现了这样的隐匿靶点。我们从 CPI 中恢复了 AD 的唯一经过验证的治疗靶点乙酰胆碱酯酶(ACHE),并强调了其他几个假定的靶点。例如,我们发现雌激素受体(ER)和组蛋白去乙酰化酶(HDAC),它们最近被确定为 AD 的两个新的治疗靶点,可能已经被市场上的 AD 药物所针对。我们进一步确定,药物的 CPI 图谱可以反映其与多蛋白组的相互作用特征,并且具有相同治疗属性的药物将具有相似的相互作用图谱。这些发现表明 CPI 可以代表化学-蛋白质相互作用的全景,并揭示现有药物治疗机制的“幕后”方面,为网络药理学的关键节点或单一靶点药理学范式的全新药物靶点提供可测试的假设。