Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi, Okhla, Phase III, New Delhi, Delhi, India.
Department of Bio-Medical Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, India.
Nat Chem Biol. 2022 Nov;18(11):1204-1213. doi: 10.1038/s41589-022-01110-7. Epub 2022 Aug 11.
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.
由于真核细胞的基因组经常暴露于无数种异质化合物中，因此它常常容易受到内在和外在威胁的影响。尽管存在先天的 DNA 损伤反应，但一些基因组损伤会引发细胞的恶性转化。由于对真正的（非）致癌物的信息有限，因此准确预测致癌物仍然是一项极具挑战性的任务。我们开发了 Metabokiller，这是一种通过定量评估其亲电性、诱导增殖、氧化应激、基因组不稳定性、表观遗传改变和抗细胞凋亡反应的潜力来准确识别致癌物的集成分类器。Metabokiller 不仅可以进行致癌性预测，而且具有完全可解释性，并优于现有的最佳致癌性预测方法。Metabokiller 揭示了潜在的致癌人类代谢物。为了对 Metabokiller 的预测进行交叉验证，我们使用酿酒酵母和人类细胞进行了多个功能测定，其中包括两种被 Metabokiller 标记的人类代谢物，即 4-硝基儿茶酚和 3,4-二羟基苯乙酸，并观察到 Metabokiller 预测与实验验证之间存在高度协同作用。
