Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India.
J Integr Bioinform. 2021 Nov 18;18(4):20210028. doi: 10.1515/jib-2021-0028.
Ovarian cancer is the third leading cause of cancer-related deaths in India. Epigenetics mechanisms seemingly plays an important role in ovarian cancer. This paper highlights the crucial epigenetic changes that occur in POTEE that get hypomethylated in ovarian cancer. We utilized the POTEE paralog mRNA sequence to identify major motifs and also performed its enrichment analysis. We identified 6 motifs of varying lengths, out of which only three motifs, including CTTCCAGCAGATGTGGATCA, GGAACTGCC, and CGCCACATGCAGGC were most likely to be present in the nucleotide sequence of POTEE. By enrichment and occurrences identification analyses, we rectified the best match motif as CTTCCAGCAGATGT. Since there is no experimentally verified structure of POTEE paralog, thus, we predicted the POTEE structure using an automated workflow for template-based modeling using the power of a deep neural network. Additionally, to validate our predicted model we used AlphaFold predicted POTEE structure and observed that the residual stretch starting from 237-958 had a very high confidence per residue. Furthermore, POTEE predicted model stability was evaluated using replica exchange molecular dynamic simulation for 50 ns. Our network-based epigenetic analysis discerns only 10 highly significant, direct, and physical associators of POTEE. Our finding aims to provide new insights about the POTEE paralog.
卵巢癌是印度癌症相关死亡的第三大主要原因。表观遗传机制似乎在卵巢癌中起着重要作用。本文重点介绍了在卵巢癌中发生的重要表观遗传变化，即 POTEE 去甲基化。我们利用 POTEE 旁系同源 mRNA 序列来识别主要基序，并对其进行了富集分析。我们确定了 6 个不同长度的基序，其中只有 3 个基序，包括 CTTCCAGCAGATGTGGATCA、GGAACTGCC 和 CGCCACATGCAGGC，很可能存在于 POTEE 的核苷酸序列中。通过富集和出现识别分析，我们将最佳匹配基序纠正为 CTTCCAGCAGATGT。由于没有经过实验验证的 POTEE 旁系同源物结构，因此我们使用基于模板的建模的自动化工作流程，利用深度神经网络的强大功能，对 POTEE 结构进行了预测。此外，为了验证我们预测的模型，我们使用了 AlphaFold 预测的 POTEE 结构，并观察到从 237-958 开始的剩余伸展具有非常高的残基置信度。此外，还使用 replica exchange 分子动力学模拟对 POTEE 预测模型的稳定性进行了 50ns 的评估。我们基于网络的表观遗传分析仅识别出 10 个高度显著、直接和物理关联的 POTEE。我们的发现旨在为 POTEE 旁系同源物提供新的见解。
