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基于新型生物信息学方法的用于检测内分泌干扰化学小分子的适体生物传感器设计。

Aptamer biosensor design for the detection of endocrine-disrupting chemicals small organic molecules using novel bioinformatics methods.

机构信息

Department of Bioinformatics and Computational Biology, Gaziantep University, Turkey.

Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Birulia 1216, Ashulia, Dhaka, Bangladesh; Faculty of Pharmaceutical Science, Assam Down Town University, Guwahati, Assam, India.

出版信息

J Mol Graph Model. 2024 Sep;131:108785. doi: 10.1016/j.jmgm.2024.108785. Epub 2024 May 2.

Abstract

Endocrine-disrupting chemicals (EDCs) are substances that can disrupt the normal functioning of hormones.Using aptamers, which are biological recognition elements, biosensors can quickly and accurately detect EDCs in environmental samples. However, the elucidation of aptamer structures by conventional methods is highly challenging due to their complexity. This has led to the development of three-dimensional aptamer structures based on different models and techniques. To do this, we developed a way to predict the 3D structures of the SS DNA needed for this sequence by starting with an aptamer sequence that has biosensor properties specific to bisphenol-A (BPA), one of the chemicals found in water samples that can interfere with hormones. In addition, we will elucidate the intermolecular mechanisms and binding affinity between aptamers and endocrine disruptors using bioinformatics techniques such as molecular docking, molecular dynamics simulation, and binding energies. The outcomes of our study are to compare modeling programs and force fields to see how reliable they are and how well they agree with results found in the existing literature, to understand the intermolecular mechanisms and affinity of aptamer-based biosensors, and to find a new way to make aptamers that takes less time and costs less.

摘要

内分泌干扰化学物质(EDCs)是能够扰乱激素正常功能的物质。使用适体,即生物识别元件,生物传感器可以快速准确地检测环境样本中的 EDC。然而,由于其复杂性,传统方法阐明适体结构极具挑战性。这导致了基于不同模型和技术的三维适体结构的发展。为此,我们开发了一种方法,通过从具有针对双酚 A(一种存在于水样中的化学物质,可干扰激素)的生物传感器特性的适体序列开始,预测需要该序列的 SS DNA 的 3D 结构。此外,我们将使用分子对接、分子动力学模拟和结合能等生物信息学技术阐明适体与内分泌干扰物之间的分子间机制和结合亲和力。我们研究的结果是比较建模程序和力场,以了解它们的可靠性以及它们与现有文献中发现的结果的一致性如何,以了解基于适体的生物传感器的分子间机制和亲和力,并找到一种新的方法来制造适体,这种方法耗时更少,成本更低。

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