Department of Precision Medicine, Institute for Antimicrobial Resistance Research and Therapeutics, Sungkyunkwan University School of Medicine, Suwon 16419, Korea.
Center of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad 38040, Pakistan.
Int J Mol Sci. 2020 Dec 23;22(1):61. doi: 10.3390/ijms22010061.
I-Motif is a tetrameric cytosine-rich DNA structure with hemi-protonated cytosine: cytosine base pairs. Recent evidence showed that i-motif structures in human cells play regulatory roles in the genome. Therefore, characterization of novel i-motifs and investigation of their functional implication are urgently needed for comprehensive understanding of their roles in gene regulation. However, considering the complications of experimental investigation of i-motifs and the large number of putative i-motifs in the genome, development of an in silico tool for the characterization of i-motifs in the high throughput scale is necessary. We developed a novel computation method, MD-TSPC4, to predict the thermal stability of i-motifs based on molecular modeling and molecular dynamic simulation. By assuming that the flexibility of loops in i-motifs correlated with thermal stability within certain temperature ranges, we evaluated the correlation between the root mean square deviations (RMSDs) of model structures and the thermal stability as the experimentally obtained melting temperature (Tm). Based on this correlation, we propose an equation for Tm prediction from RMSD. We expect this method can be useful for estimating the overall structure and stability of putative i-motifs in the genome, which can be a starting point of further structural and functional studies of i-motifs.
I- 基序是一种四聚体富含胞嘧啶的 DNA 结构，具有半质子化的胞嘧啶：胞嘧啶碱基对。最近的证据表明，人类细胞中的 i- 基序结构在基因组中发挥着调节作用。因此，为了全面了解它们在基因调控中的作用，迫切需要对新的 i- 基序进行特征描述，并研究其功能意义。然而，考虑到 i- 基序实验研究的复杂性和基因组中大量假定的 i- 基序，开发一种用于高通量规模 i- 基序特征描述的计算工具是必要的。我们开发了一种新的计算方法 MD-TSPC4，该方法基于分子建模和分子动力学模拟来预测 i- 基序的热稳定性。通过假设 i- 基序中环的灵活性与特定温度范围内的热稳定性相关，我们评估了模型结构的均方根偏差 (RMSD)与实验获得的熔解温度 (Tm)之间的相关性。基于这种相关性，我们提出了一个从 RMSD 预测 Tm 的方程。我们希望该方法可用于估计基因组中假定 i- 基序的整体结构和稳定性，这可以作为进一步研究 i- 基序结构和功能的起点。
