We demonstrate the use of multiscale polymer modeling to quantitatively predict DNA linear dichroism (LD) in shear flow. LD is the difference in absorption of light polarized along two perpendicular axes and has long been applied to study biopolymer structure and drug-biopolymer interactions. As LD is orientation dependent, the sample must be aligned in order to measure a signal. Shear flow via a Couette cell can generate the required orientation; however, it is challenging to separate the LD due to changes in polymer conformation from specific interactions, e.g., drug-biopolymer. In this study, we have applied a combination of Brownian dynamics and equilibrium Monte Carlo simulations to accurately predict polymer alignment, and hence flow LD, at modest computational cost. As the optical and conformational contributions to the LD can be explicitly separated, our findings allow for enhanced quantitative interpretation of LD spectra through the use of an in silico model to capture conformational changes. Our model requires no fitting and only five input parameters: the DNA contour length, persistence length, optical factor, solvent quality, and relaxation time, all of which have been well characterized in prior literature. The method is sufficiently general to apply to a wide range of biopolymers beyond DNA, and our findings could help guide the search for new pharmaceutical drug targets via flow LD.

中文翻译：

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DNA 的流二色谱性可以通过粗粒度分子模拟进行定量预测


我们展示了使用多尺度聚合物建模来定量预测剪切流中的 DNA 线性二色性 （LD）。LD 是沿两个垂直轴偏振的光的吸收差异，长期以来一直被用于研究生物聚合物结构和药物-生物聚合物相互作用。由于 LD 与方向相关，因此样品必须对齐才能测量信号。通过 Couette 单元的剪切流可以产生所需的取向;然而，由于聚合物构象的变化与特定相互作用（例如药物-生物聚合物）分离 LD 具有挑战性。在这项研究中，我们应用了布朗动力学和平衡蒙特卡洛模拟的组合，以适度的计算成本准确预测聚合物排列，从而准确预测流动 LD。由于光学和构象对 LD 的贡献可以明确分开，我们的研究结果允许通过使用计算机模型来捕获构象变化来增强对 LD 光谱的定量解释。我们的模型不需要拟合，只需要五个输入参数：DNA 轮廓长度、持久性长度、光学因子、溶剂质量和弛豫时间，所有这些都在以前的文献中得到了很好的表征。该方法足够通用，可以应用于 DNA 以外的广泛生物聚合物，我们的研究结果可以帮助指导通过流式 LD 寻找新的药物靶点。