From Experiments to a Fast Easy-to-Use Computational Methodology to Predict Human Aldehyde Oxidase Selectivity and Metabolic Reactions,Journal of Medicinal Chemistry

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From Experiments to a Fast Easy-to-Use Computational Methodology to Predict Human Aldehyde Oxidase Selectivity and Metabolic Reactions
Journal of Medicinal Chemistry ( IF 6.8 ) Pub Date : 2017-12-29 00:00:00 , DOI: 10.1021/acs.jmedchem.7b01552
Gabriele Cruciani _{1,

2} , Nicolò Milani ₁ , Paolo Benedetti _{1,

2} , Susan Lepri ₁ , Lucia Cesarini ₁ , Massimo Baroni ₃ , Francesca Spyrakis ₄ , Sara Tortorella _{2,

5} , Edoardo Mosconi _{2,

6} , Laura Goracci _{1,

2}

Affiliation

Aldehyde oxidase (AOX) is a molibdo-flavoenzyme that has raised great interest in recent years, since its contribution in xenobiotic metabolism has not always been identified before clinical trials, with consequent negative effects on the fate of new potential drugs. The fundamental role of AOX in metabolizing xenobiotics is also due to the attempt of medicinal chemists to stabilize candidates toward cytochrome P450 activity, which increases the risk for new compounds to be susceptible to AOX nucleophile attack. Therefore, novel strategies to predict the potential liability of new entities toward the AOX enzyme are urgently needed to increase effectiveness, reduce costs, and prioritize experimental studies. In the present work, we present the most up-to-date computational method to predict liability toward human AOX (hAOX), for applications in drug design and pharmacokinetic optimization. The method was developed using a large data set of homogeneous experimental data, which is also disclosed as Supporting Information.

中文翻译：

从实验到快速易用的计算方法，以预测人类醛氧化酶的选择性和代谢反应

醛氧化酶（AOX）是一种Molibdo-flavoenzyme，近年来引起了极大的兴趣，因为在临床试验之前并不总是能够确定其对异源生物代谢的贡献，从而对新的潜在药物的命运产生负面影响。AOX在代谢异种生物中的基本作用还归因于药物化学家试图稳定候选物的细胞色素P450活性，这增加了新化合物易受AOX亲核试剂攻击的风险。因此，迫切需要新颖的策略来预测新实体对AOX酶的潜在责任，以提高效力，降低成本并优先进行实验研究。在目前的工作中，我们提出了最新的计算方法来预测对人类AOX（hAOX），用于药物设计和药代动力学优化。该方法是使用同类实验数据的大数据集开发的，该数据集也作为支持信息公开。

更新日期：2017-12-29

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