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

摘要 结构化RNA在生物学过程中起着重要作用，并且正被积极地用作靶点， 治疗疾病。此外，基于合成RNA的生物传感器和疗法-受天然RNA的启发 机器-开始联机。这些RNA可以经历构象转变以结合小分子RNA。 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 认识到分子阻碍了这些潜在的新设备和治疗的发展。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RNA的3D结构， 动力学和配体结合。实验，如核磁共振，冷冻电子显微镜，系统发育分析， 生物化学方法虽然强大，但往往无法完全捕获RNA的结构动力学， 构象变化为了应对这些挑战，Yesselman实验室正在开发新的RNA模型， 3D结构与设计我们已经证明了第一个高分辨率的RNA三维螺旋热力学模型， 自动设计RNA的三维结构，并开发了新的实验方法来探测二级和三维 结构.在接下来的五年里，Yesselman实验室的目标是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催化的模型：（1）RNA构象动力学 动力学：利用新的RNA 3D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，以更好地了解RNA如何经历构象转变， 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/药物的预测模型 通过分析小分子药物对数千种RNA结构的影响， 新的机器学习方法。(3)RNA催化活性：自切割核酶可以切割RNA链。 与蛋白质相比，核酶的活性明显较低。一个关键的区别是核酶通常具有更少的3D 脚手架当它们这样做时，它们包含远程三级接触，但这些接触的强度和位置 相互作用可以显著地影响催化活性。确定核酶中三维支架的规则将 增加我们对RNA催化的理解，并使设计新的核酶用于其他催化 功能协调发展的这些研究领域的发现将解决RNA折叠方面的挑战和先进知识， 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.