Next-generation biophysical models for RNA dynamics, ligand binding, and catalysis

摘要 结构化RNA在生物过程中发挥着基础性作用，并正在积极作为靶标进行研究 治病。此外，受天然RNA启发的基于合成RNA的生物传感器和疗法 机器--正开始联网。这些RNA可以经历构象转换以结合小分子 分子并进行生化反应。不幸的是，RNA结构的不完整模型以及它是如何 识别分子阻碍了这些潜在的新设备和治疗方法的发展。如果没有 预测生物物理模型，该领域依赖于广泛的实验方法来探测RNA3D结构， 动力学和配基结合。核磁共振、低温电子显微镜、系统发育分析和 生化方法虽然功能强大，但往往不能完全捕获RNA的结构动力学和 构象变化。为了应对这些挑战，耶塞尔曼实验室正在开发新的RNA模型 三维结构和设计。我们已经演示了第一个高分辨率的RNA3D螺旋热力学模型， RNA 3D结构的自动化设计，并开发了新的实验方法来探测二次和3D 结构。在接下来的五年里，耶塞尔曼实验室旨在提高我们的理解和预测能力 RNA构象动力学、RNA-配体结合和RNA催化模型：(1)RNA构象 动力学：利用新的RNA3D设计和大规模并行生化分析，我们的目标是开发 RNA 3D动力学的通用模型，以更好地理解RNA如何经历构象转变和 与配体结合。(2)RNA-配体相互作用：我们的目标是建立第一个RNA/药物预测模型 通过分析小分子药物对数千个RNA结构的影响来实现相互作用 新颖的机器学习方法。(3)RNA催化活性：自切割核酶可切割RNA链。 与蛋白质相比，核酶的活性要低得多。一个关键的区别是核酶通常具有较少的3D 脚手架。当他们这样做时，他们包含远程第三方联系，但这些联系的强度和位置 相互作用可以极大地影响催化活性。确定核酶中3D支架的规则将 加深对RNA催化的了解，为设计新的核酶用于其他催化提供了可能 功能。这些研究领域的发现将解决RNA折叠方面的挑战和提高知识， 分子识别和设计。最终，我们的研究计划将在开发下一个 基于RNA的诊断和治疗技术的产生。

ABSTRACT Structured RNAs play fundamental roles in biological processes and are actively being pursued as targets to treat disease. Furthermore, synthetic RNA-based biosensors and therapeutics – inspired by natural RNA machines – are beginning to come online. These RNAs can undergo conformational transitions to bind small molecules and perform biochemical reactions. Unfortunately, incomplete models of RNA structure and how it recognizes molecules hinder the development of these potential novel devices and treatments. Without predictive biophysical models, the field relies on extensive experimental methods to probe RNA 3D structure, dynamics, and ligand binding. Experiments such as NMR, cryo-electron microscopy, phylogenetic analysis, and biochemical methods, although powerful, often fail to completely capture an RNA’s structural dynamics and conformational changes. To address these challenges, the Yesselman Lab is developing novel models of RNA 3D structure and design. We have demonstrated the first high-resolution RNA 3D helical thermodynamics model, automated design of RNA 3D structure, and developed novel experimental methods to probe secondary and 3D structures. Over the next five years, the Yesselman Lab aims to improve our understanding and predictive models of RNA conformational dynamics, RNA-ligand binding, and RNA catalysis: (1) RNA conformational dynamics: utilizing novel RNA 3D design and massively parallel biochemical assays, our goal is to develop general models for RNA 3D dynamics to understand better how RNA undergoes conformational transitions and binds to ligands. (2) RNA-ligand interactions: our goal is to build the first predictive model of RNA/drug interactions by assaying the effects of small molecule drugs on thousands of RNA structures combined with novel machine learning approaches. (3) RNA catalytic activity: self-cleaving ribozymes can cut RNA strands. Compared to proteins, ribozymes are significantly less active. A key difference is ribozymes often have less 3D scaffolding. When they do, they contain long-range tertiary contacts, but the strength and placement of these interactions can dramatically affect catalysis activity. Determining the rules of 3D scaffolding in ribozymes will increase our understanding of RNA catalysis and enable the design of new ribozymes for other catalytic functions. Findings from these research areas will address challenges and advance knowledge in RNA folding, molecular recognition, and design. Ultimately, our research program will play a critical role in developing the next generation of RNA-based diagnostics and therapeutics.