Nature Chemical Biology ( IF 12.9 ) Pub Date : 2022-08-11 , DOI: 10.1038/s41589-022-01110-7
Aayushi Mittal 1 , Sanjay Kumar Mohanty 1 , Vishakha Gautam 1 , Sakshi Arora 1 , Sheetanshu Saproo 2 , Ria Gupta 1 , Roshan Sivakumar 1 , Prakriti Garg 1 , Anmol Aggarwal 1 , Padmasini Raghavachary 1 , Nilesh Kumar Dixit 1 , Vijay Pal Singh 3 , Anurag Mehta 4 , Juhi Tayal 4 , Srivatsava Naidu 2 , Debarka Sengupta 1 , Gaurav Ahuja 1
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The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats owing to its constant exposure to a myriad of heterogeneous compounds. Despite the availability of innate DNA damage responses, some genomic lesions trigger malignant transformation of cells. Accurate prediction of carcinogens is an ever-challenging task owing to the limited information about bona fide (non-)carcinogens. We developed Metabokiller, an ensemble classifier that accurately recognizes carcinogens by quantitatively assessing their electrophilicity, their potential to induce proliferation, oxidative stress, genomic instability, epigenome alterations, and anti-apoptotic response. Concomitant with the carcinogenicity prediction, Metabokiller is fully interpretable and outperforms existing best-practice methods for carcinogenicity prediction. Metabokiller unraveled potential carcinogenic human metabolites. To cross-validate Metabokiller predictions, we performed multiple functional assays using Saccharomyces cerevisiae and human cells with two Metabokiller-flagged human metabolites, namely 4-nitrocatechol and 3,4-dihydroxyphenylacetic acid, and observed high synergy between Metabokiller predictions and experimental validations.
中文翻译:
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人工智能揭示致癌的人类代谢物
真核细胞的基因组通常容易受到内在和外在威胁,因为它不断暴露于无数的异质化合物中。尽管存在先天 DNA 损伤反应,但一些基因组损伤会触发细胞的恶性转化。由于关于真实(非)致癌物的信息有限,准确预测致癌物是一项极具挑战性的任务。我们开发了 Metabokiller,这是一种集成分类器,通过定量评估致癌物的亲电性、诱导增殖的潜力、氧化应激、基因组不稳定性、表观基因组改变和抗凋亡反应来准确识别致癌物。与致癌性预测相结合,Metabokiller 是完全可解释的,并且优于现有的致癌性预测最佳实践方法。代谢杀手揭示了潜在的致癌人类代谢物。为了交叉验证 Metabokiller 预测,我们使用酿酒酵母和人类细胞与两种 Metabokiller 标记的人类代谢物(即 4-硝基邻苯二酚和 3,4-二羟基苯乙酸)进行了多种功能测定,并观察到 Metabokiller 预测和实验验证之间的高度协同作用。