Deciphering the principles of selective recognition of complex RNAs by small molecules

摘要 非编码RNA(NcRNAs)是一类新的、不断增长的生物分子，越来越多地被证明是 是许多人类病原体的重要药物靶点。许多大多数人都需要新的药物靶点 人类疾病中的重要病原体，如耐药性、潜伏期和成本，仍然是 治疗。虽然已经做出了相当大的努力来针对这些重要的ncRNA，但最突出的 例如艾滋病毒中的茎环发夹，目前还没有化合物成功上市。这些研究 专注于可能不是理想药物靶点的简单RNA。简单的RNA往往具有“低可药性” 具有高溶剂暴露、有限的唯一结合部位和更高的灵活性等特性。我们假设 在制造以RNA为靶点的小分子药物方面缺乏成功在很大程度上是由于在 高选择性地瞄准这些发夹，特别是考虑到类似的发夹图案大量出现 在转录组中。然而，有越来越多的微生物ncRNA药物靶点折叠成更多 复杂的3D结构。这些RNA具有独特的二级结构基序、长程三级结构基序 接触，而且往往是更深更大的疏水口袋。这一提议的主要假设是 RNA结构的属性使其成为小分子抑制的更好的药物靶点 更简单的发夹。AIM 1将使用基于结构的调查、基于核磁共振的结合分析和计算 对接以测试复杂RNA具有独特的绑定口袋和模式的假设，这些模式允许高度 选择性地与配体结合，否则只能与普通发夹RNA弱结合。该目标还将考验 假设复杂RNA的结合口袋具有不同的属性，从而导致不同水平的 结合选择性，可以使用计算对接进行预测。AIM 2将使用以合奏为基础的 虚拟筛选方法，结合实验高通量筛选，验证假设 这种新的化学类型结合在复杂RNA的口袋上，其中一些可以改变或抑制生物功能。 该项目将提供关于RNA的可药性的更深层次的理解，识别新的化学类型 这可能会进一步优化新型抗微生物药物，并有助于解决选择性的挑战，这 是靶向小分子RNA的最大障碍之一。 由于对这些靶点的药物发现工作很少，这一筛选努力将极大地扩大 为RNA结合测量的化学空间。新发现的化学类型将导致更深层次的 了解高选择性相互作用的结构决定因素，并将成为铅的基础 可进一步优化用于新型抗菌药物的化合物。

ABSTRACT Noncoding RNAs (ncRNAs) are a new and growing class of biomolecules that are increasingly being shown to be important drug targets in many human pathogens. New drug targets are needed for many of the most important pathogens in human disease as resistance, latency, and cost are still significant challenges in treatment. While considerable effort has been made to target these essential ncRNAs, the most prominent examples being stem loop hairpins in HIV, no compounds have successfully reached the market. These studies have focused on simple RNAs that may not be ideal drug targets. Simple RNAs tend to have “low-druggability” properties such high solvent exposure, limited unique binding sites, and increased flexibility. We hypothesize that the lack of success in creating RNA-targeted small molecule drugs is due in large part due to difficulties in targeting these hairpins with high selectivity, especially given that similar hairpin motifs occur in great abundance in the transcriptome. However, there are a growing number of microbial ncRNA drug targets that fold into more complex 3D structures. These RNAs are marked by unique secondary structural motifs, long-range tertiary contacts, and often deeper and larger hydrophobic pockets. The main hypothesis of this proposal is that complex RNA structures have attributes that make them better drug targets for small molecule inhibition as compared to simpler hairpins. Aim 1 will used a structure-based survey, NMR-based binding assays, and computational docking to test the hypothesis that complex RNAs have unique binding pockets and modes that allow highly selective binding to ligands that otherwise only weakly bind to common hairpin RNAs. The Aim will also test the hypothesis that the binding pockets of complex RNAs have variable attributes that result in varying levels of binding selectivity, which can be predicted using computational docking. Aim 2 will use an ensemble-based virtual screening approach, in combination with experimental high throughput screening, to test the hypothesis that novel chemotypes bind to the pockets of complex RNAs, some of which can alter or inhibit biological function. This project will provide a deeper understanding regarding the druggability of RNA, identify novel chemotypes that may be further optimized for novel antimicrobial drugs, and help address the challenge of selectivity, which is one of the biggest obstacles in targeting RNA with small molecules. As very little drug discovery work has been done with these targets, this screening effort will vastly expand the chemical space surveyed for RNA binding. Novel chemotypes that are discovered will lead to a deeper understanding of the structural determinants of highly selective interactions and will become the basis of lead compounds that can be further optimized for novel antimicrobial drugs.