Core A - Discovery Core

项目摘要 筛选核心将以我们的成功为基础，利用传统和虚拟筛选方法来 识别调节支气管运动张力的小分子。常规筛选与虚拟筛选的融合 工作流使我们能够快速从主要筛选命中转移到详细的结构-活动关系 (SAR)，以及从计算预测到定量实验数据。核心的关系 与其他区域筛选资源建立了合作关系(兰克瑙化学基因组学中心； 天然产品发现研究所(NPDI)；蒙内尔化学感官中心(MCSC))确保访问 为建议的筛选项目提供高质量的分子多样性，以及我们经过验证的专业知识 信使和蛋白质相互作用分析将加速发现偏向信号的探针和靶标 利用排列的和表达的分子多样性来源在呼吸道平滑肌中的通路。 Jefferson Discovery核心为核心A提供传统的筛选功能，使用In- 分子多样性的馆藏资源以及从区域和国家资源(NCI- DTP)，以确定在细胞基础上产生与呼吸道松弛相关的表型的小分子， 高通量筛选(HTS)分析。第二信使(cAMP、Ca~(2+))和蛋白质相互作用分析 (酶-片段互补)已被优化用于在多孔板和通过 荧光激活细胞分选，这使得能够使用排列的和表达的分子来源 识别调控影响支气管运动张力的信号通路的探针和靶点的多样性。 用于G12信号抑制物的HTS(项目1)、TAS2R14的内化(项目2)、HTS、SAR和MEDICAL 化学发现和优化2AR的Gs偏向激动剂和变构调节剂(项目3)和 通过虚拟筛选(项目4)预测的OGR1的Gs偏置变构调节子的评估位居榜首 优先事项。 核心A使用计算建模和对接方法来指导和告知 传统的筛查方法。基于CHARMM的分子对接方法将用于预测 从高通量筛选中确定的小分子结合模式，开发了SAR模型和 预测具有更高活性和物理化学性质的衍生物。这些研究与 平行的HTS实验工作，特别是在跟踪HTS确定的最有希望的热门项目方面。 2AR和OGR1小分子变构调节剂的并行建模研究将针对 确定导致Gs偏向的信号的共同结构特征。将使用基于结构的知识 提供并行虚拟筛选策略，以确定2AR和OGR1新的变构调节子。最后， 一种虚拟筛选方法将被用来识别G12和GQ的小分子抑制剂，它们将模仿 GQ特异性抑制剂YM-254890的药理作用。

Project Summary The screening core will build on our success utilizing conventional and virtual screening approaches to identify small molecules that regulate bronchomotor tone. The integration of conventional and virtual screening workflows enabled us to move rapidly from primary screening hits to detailed structure-activity relationships (SAR), and from computational predictions to quantitative experimental data. The relationships that the core has established with other regional screening resources (Lankenau Chemical Genomics Center (LCGC); Natural Products Discovery Institute (NPDI); Monell Chemical Senses Center (MCSC)) ensures access to high-quality molecular diversity for proposed screening projects, and our validated expertise in second messenger and protein interaction assays will expedite discovery of probes and targets that bias signaling pathways in airway smooth muscle using arrayed and expressed sources of molecular diversity. The Jefferson Discovery Core provides the conventional screening capabilities for Core A, using in- house sources of molecular diversity as well as libraries obtained from regional and national resources (NCI- DTP) to identify small molecules engendering phenotypes that correlate with airway relaxation in cell-based, high-throughput screening (HTS) assays. Second messenger (cAMP, Ca2+) and protein interaction assays (enzyme-fragment complementation) have been optimized for detection both in multiwell plates and by fluorescence-activated cell sorting, which enables use of both arrayed and expressed sources of molecular diversity for identification of probes and targets regulating signaling pathways affecting bronchomotor tone. HTS for inhibitors of G12 signaling (project 1), internalization of TAS2R14 (project 2), HTS, SAR and medicinal chemistry to discover and optimize Gs-biased agonists and allosteric modulators of 2AR (project 3) and evaluation of Gs-biased allosteric modulators of OGR1 predicted by virtual screening (project 4) are the top priorities. Computational modeling and docking approaches are used by Core A both to direct and inform conventional screening approaches. CHARMM-based molecular docking approaches will be used to predict the binding modes of small-molecules identified from high-throughput screening, develop SAR models and predict derivatives with improved activity and physiochemical properties. These studies are synergistic with parallel experimental HTS efforts, particularly in following-up on the most promising hits identified from HTS. Parallel modeling studies of small-molecule allosteric modulators of 2AR and OGR1 will be aimed at identifying common structural features leading to Gs-biased signaling. Structure-based knowledge will be used to inform parallel virtual screening strategies to identify novel allosteric modulators of 2AR and OGR1. Finally, a virtual screening approach will be used to identify small-molecule inhibitors of G12 and Gq that would mimic the pharmacological action of the Gq specific inhibitor YM-254890.