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

破译小分子选择性识别复杂RNA的原理

基本信息

  • 批准号:
    10231110
  • 负责人:
  • 金额:
    $ 5.1万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-09-01 至 2022-08-31
  • 项目状态:
    已结题

项目摘要

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.
摘要

项目成果

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