Toward the accurate prediction of P450-mediated metabolism and adverse drug reactions using novel MM methods and QM-derived rules.

使用新的 MM 方法和 QM 衍生规则准确预测 P450 介导的代谢和药物不良反应。

• 批准号: 469677-2014
• 负责人: Moitessier, Nicolas
• 金额: $ 2.91万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=563665
• 关键词: Toward; accurate; prediction; P450; mediated

Despite the large investment in toxicology and clinical trials of drug candidates, adverse drug reactions remain a leading cause of drug withdrawal. This form of toxicity of drugs may only affect a small fraction of the patients and is not detected in clinical trials. However, if the drug is already on the market and widely used this toxicity may be fatal. Over the years, medicinal chemists have relied on "structural alerts" to identify potential toxicity of drugs and more specifically idiosyncratic toxicity. These functional groups are often activated by metabolic enzymes (e.g., P450) into reactive metabolites leading to the observed toxicity. However the presence of such a functional group does not always correlate with toxicity as the bioactivation

尽管对候选药物的毒理学和临床试验进行了大量投资，但药物不良反应仍然是停药的主要原因。这种形式的药物毒性可能只影响一小部分患者，并且在临床试验中未检测到。然而，如果这种药物已经上市并广泛使用，这种毒性可能是致命的。多年来，药物化学家一直依赖于“结构警报”来识别药物的潜在毒性，更具体地说是特异质毒性。这些官能团通常被代谢酶（例如，P450）转化为反应性代谢物，导致观察到的毒性。然而，这种官能团的存在并不总是与毒性相关，因为生物活化