Predicting new indications for approved drugs using a proteochemometric method.
Predicting new indications for approved drugs using a proteochemometric method.
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DOI：
10.1021/jm300576q
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发表时间：
2012-08-09
影响因子：
7.3
通讯作者：
Byers, Stephen W.
中科院分区：
文献类型：
--
作者：
Dakshanamurthy, Sivanesan;Issa, Naiem T.;Assefnia, Shahin;Seshasayee, Ashwini;Peters, Oakland J.;Madhavan, Subha;Uren, Aykut;Brown, Milton L.;Byers, Stephen W.
从靶标识别到临床应用的最有效方法是识别已经批准的具有激活或抑制非预期靶标的潜力的药物（重新定位或重新定位）。这通常通过高通量化学筛选、转录组匹配或简单的硅配体对接来实现。我们现在描述了一种新的快速计算蛋白质化学计量方法，称为“训练，匹配，匹配，流线”（TMFS），以绘制新的药物-靶标相互作用空间并预测新的用途。TMFS方法结合了形状、拓扑和化学特征，包括配体的对接评分和功能接触点，以惊人的准确性预测潜在的药物-靶标相互作用。利用TMFS方法，我们对2335种人类蛋白质晶体结构中的3671种FDA批准的药物进行了广泛的分子拟合计算。TMFS方法对大多数药物预测药物靶标相关性的准确率为91%。在所有3,671种药物中，超过58%的已知最佳配体被正确预测为排名靠前的，其次是排名前10、20、30和40的药物分别为66%、76%、84%和91%。排名在前1-40位的药物，没有经过特定靶点的实验验证，现在成为重新定位的候选药物。此外，我们使用TMFS方法发现，最近发现的具有意想不到的抗癌特性的抗寄生虫药物甲苯达唑具有抑制VEGFR2的结构潜力。我们通过实验证实，甲苯达唑抑制VEGFR2激酶活性以及血管生成的剂量与其已知的对钩虫的作用相当。TMFS还预测，并通过表面等离子体共振证实，二甲基塞来昔布和抗炎药塞来昔布可以结合钙粘蛋白-11，这是一种粘附分子，在类风湿关节炎和预后不良的恶性肿瘤中很重要，目前尚无靶向治疗方法。我们预计，将我们的TMFS方法扩展到全球范围内所有靶点的27,000种临床活性药物，将对现有药物重新定位新的治疗靶点最有用。
The most effective way to move from target identification to the clinic is to identify already approved drugs with the potential for activating or inhibiting unintended targets (repurposing or repositioning). This is usually achieved by high throughput chemical screening, transcriptome matching or simple in silico ligand docking. We now describe a novel rapid computational proteo-chemometric method called “Train, Match, Fit, Streamline” (TMFS) to map new drug-target interaction space and predict new uses. The TMFS method combines shape, topology and chemical signatures, including docking score and functional contact points of the ligand, to predict potential drug-target interactions with remarkable accuracy. Using the TMFS method, we performed extensive molecular fit computations on 3,671 FDA approved drugs across 2,335 human protein crystal structures. The TMFS method predicts drug-target associations with 91% accuracy for the majority of drugs. Over 58% of the known best ligands for each target were correctly predicted as top ranked, followed by 66%, 76%, 84% and 91% for agents ranked in the top 10, 20, 30 and 40, respectively, out of all 3,671 drugs. Drugs ranked in the top 1–40, that have not been experimentally validated for a particular target now become candidates for repositioning. Furthermore, we used the TMFS method to discover that mebendazole, an anti-parasitic with recently discovered and unexpected anti-cancer properties, has the structural potential to inhibit VEGFR2. We confirmed experimentally that mebendazole inhibits VEGFR2 kinase activity as well as angiogenesis at doses comparable with its known effects on hookworm. TMFS also predicted, and was confirmed with surface plasmon resonance, that dimethyl celecoxib and the anti-inflammatory agent celecoxib can bind cadherin-11, an adhesion molecule important in rheumatoid arthritis and poor prognosis malignancies for which no targeted therapies exist. We anticipate that expanding our TMFS method to the >27,000 clinically active agents available worldwide across all targets will be most useful in the repositioning of existing drugs for new therapeutic targets.
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影响因子：
5.6
作者：
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通讯作者：
Thornton, Janet M.
影响因子：
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作者：
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作者：
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通讯作者：
Grabowski, HG
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作者：
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Montalto, Giuseppe