Mathematical Modeling of a Self-Assembled Probe for Non Intercalator Type Real-Time Monitoring of PCR

项目摘要/摘要 实时定量聚合酶链式反应已经成为分子诊断领域中的重要工具，许多方法已经被应用 开发的目的是在反应进行时监控聚合酶链式反应。这个应用程序的目标是检查感知 与苯基硼酸(1，2，4-二苯基-1，2，4，4，4，4，4，4，4，4，6，6，6，6，6，5，6，6，5，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，6，7，6，6，6，6，7，6，6，6，6，7，6，6，6，6，7，7，6，6，6，6，6，6，7，7，7，6，6，7，7，7，6，6，4，4，4，4，4，4，4，4，4，4， 茜素红S用于非嵌入型实时监测聚合酶链式反应的数学模型和方法 实验观察。根据初步数据提出的中心假设是， 1.锌-ARS传感器对DNA扩增的副产物焦磷酸(PPI)具有较强的选择性 磷酸盐。不同的分析证据表明，存在多个相互交织的自我均衡 组装了1.锌染料传感器，但磷酸盐传感过程背后的分子机制 都没有被很好地理解。我们的长期目标是了解这种非常复杂的自我 装配组合不仅限于通过数学建模的这些示例，而且 通过开发新的生物传感策略来扩大这方面的知识。建议进行这项研究的理由是 找出对核糖核酸检测过程的未知影响，以增进我们对自我 组装的超分子主客体热力学，并生成适体和适体的可测试假设 药物筛选程序。为了解决这些目标，我们的目标是开发一种数学算法，它可以模拟 整个27个分子相互作用和超分子探针之间的反应，1，锌- ARS和生物磷酸盐。我们将确定相互作用的热力学参数和 利用所开发的数学模型、实验设计和电位计的数据拟合进行反应 测量。然后，我们将介绍最佳实时低聚磷酸盐的最佳实验条件 基于数学建模和计算机模拟的监测。此外，作为原则的证明，我们 将模拟结果与实验实时聚合酶链式反应观测结果进行验证。本研究具有创新性。 因为将使用复杂的数学模型和计算机模拟来研究该反应 1.Zn-ARS-PPI形成不同客体-宿主结合的途径。计算机模拟将会 使不同的结合常数、温度、离子强度、 任何可能的实验条件的浓度、启动PHS等，并为 实时生物分子传感。拟议的项目意义重大，因为通过结合 用数学模型进行超分子自组装，更好地理解1.Zn-ARS-PPI分子 它们复杂的化学网络中的相互作用将被实现，这可以推广到许多其他 在制药和生物化学科学中帮助检测和监测分析物的复杂化学过程 在医学上很重要。

PROJECT SUMMARY/ABSTRACT Real-time PCR has become a crucial tool in many fields of molecular diagnostics, and many methods have been developed to monitor PCR as the reaction proceeds. The objective of this application is to examine sensing molecules such as the assembles of ZnII–DPA-attached phenylboronic acid (1.Zn) and catechol-type dyes like alizarin red S (ARS) for non-intercalator type real-time monitoring of PCR using mathematical modeling and experimental observation. The central hypothesis, which was formulated based on preliminary data, is that the 1.Zn–ARS sensor is selective towards pyrophosphate (PPi), the byproduct of DNA amplification, over the other phosphates. Different analytical evidence displayed existence multiple intertwined equilibria for the self- assembled 1.Zn-dyes sensors, yet the molecular mechanisms that underlie the phosphate sensing processes are not well understood. The long-term goal is to understand the molecular details of such very complicated self- assembly combinations that are not only limited to these examples through mathematical modeling, and to broaden this knowledge by developing novel biosensing strategies. The rationale for the proposed research is to identify unknown influences on ribonucleotide detection processes, to advance our understanding of self- assembled supramolecular host-guest thermodynamics, and to generate testable hypotheses for aptamer and drug screening procedures. To address these goals, we aim to develop a mathematical algorithm that can model the entire twenty-seven molecular intertwined interactions and reactions among the supramolecular probe, 1.Zn- ARS, and biological phosphates. We will determine the thermodynamic parameters of the interactions and reactions using the developed mathematical model, experimental design, and data fitting of the potentiometric measurements. We will then introduce optimum experimental conditions for the best real-time oligophosphate monitoring based on mathematical modeling and computer simulations. In addition, as a proof of principle, we will validate the simulated results with the experimental real-time PCR observations. This study is innovative because a sophisticated mathematical model and computer simulations will be used to investigate the reaction pathways for the formation of different guest-host bindings of 1.Zn-ARS-PPi. The computer simulations will enable the visualization of the effects of different values of binding constants, temperatures, ionic strengths, concentrations, starting pHs, etc. for any possible experimental conditions and provide appropriate directions for real-time biomolecular sensing. The proposed project is significant because, by combining the power of supramolecular self-assemblies with mathematical modeling, a better understanding of 1.Zn-ARS-PPi molecular interactions within their complex chemical networks will be achieved that can be generalized to many other complex chemical processes in pharmaceutical and biochemistry sciences to help detect and monitor analytes of medical importance.