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Estimation of Maximum Recommended Therapeutic Dose Using Predicted Promiscuity and Potency

机译:使用预测的滥交和有力估计最大推荐治疗剂量

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We report a simple model that predicts the maximum recommended therapeutic dose (MRTD) of small molecule drugs based on an assessment of likely protein-drug interactions. Previously, we reported methods for computational estimation of drug promiscuity and potency. We used these concepts to build a linear model derived from 238 small molecular drugs to predict MRTD. We applied this model successfully to predict MRTDs for 16 nonsteroidal antiinflammatory drugs (NSAIDs) and 14 antiretroviral drugs. Of note, based on the estimated promiscuity of low-dose drugs (and active chemicals), we identified 83 proteins as "high-risk off-targets" (HROTs) that are often associated with low doses; the evaluation of interactions with HROTs may be useful during early phases of drug discovery. Our model helps explain the MRTD for drugs with severe adverse reactions caused by interactions with HROTs.
机译:我们报告了一个简单的模型,该模型基于对可能的蛋白质-药物相互作用的评估来预测小分子药物的最大推荐治疗剂量(MRTD)。以前,我们报道了药物滥交和效力的计算估计方法。我们使用这些概念建立了由238种小分子药物衍生的线性模型来预测MRTD。我们成功地将该模型应用于16种非甾体类抗炎药(NSAIDs)和14种抗逆转录病毒药物的MRTD预测。值得注意的是,根据低剂量药物(和活性化学物质)的混杂程度,我们确定了83种蛋白质为“高风险脱靶”(HROT),通常与低剂量有关。与HROT相互作用的评估可能在药物发现的早期阶段很有用。我们的模型有助于解释因与HROT相互作用而导致严重不良反应的药物的MRTD。

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