Generating Diverse Pilot-Scale Libraries for Screening

生成用于筛选的多样化中试规模文库

• 批准号: 7684194
• 负责人: STEPHEN MARTIN
• 金额: $ 35.35万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-05 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7684194
• 关键词: Address; Biological; Biological Assay; Biological Factors; Biological Process; Chemistry; Collection; Complex; Computing Methodologies; Development; Diagnostic; Disease; Ensure; Exhibits; Genes; Genome; Health; Human; Individual; Institutes; Knowledge; Libraries; Maps; Metabolic Pathway; Metric; Molecular Bank; Parents; Pattern; Pharmaceutical Preparations; Physiological; Property; Proteins; Relative (related person); Screening procedure; Series; Signal Transduction; Structure; Structure-Activity Relationship; Technology; Texas; United States National Institutes of Health; Ursidae Family; base; chemical synthesis; design; member; novel; repository; sample collection; scaffold; small molecule; sound; therapeutic target; tool

DESCRIPTION (provided by applicant): The past decade has witnessed remarkable advances in scientific knowledge and technology that will have significant impacts upon human health. With the sequencing of the human and other genomes, new genes, gene products, signaling and metabolic pathways are being discovered at a rapid pace, thereby leading to the identification of numerous potential therapeutic targets that would have otherwise been unknown. Biological assays to determine activities have led to the discovery of numerous small molecules that have promising physiochemical and physiological properties. Conversely, small molecules are increasingly serving as invaluable tools to probe biological function and mechanism. Despite the stunning progress that has been made, one significant challenge that remains lies in identifying biologically active small molecules having novel chemotypes and structures. This problem is best addressed by the chemical synthesis of new, functionalized heterocyclic frameworks that may be easily elaborated to optimize biological activity. We will thus apply chemistry we have uniquely developed for the diversity-oriented synthesis of functionalized, heterocyclic scaffolds to prepare pure (>90%) samples of collections of distinct, novel compounds for submission to the NIH Molecular Libraries Small-Molecule Repository (MLSMR). These small molecules will be derived from a series of approximately 25-30 different heterocyclic scaffolds, some of which are both structurally and functionally complex, having different substitution patterns that are explicitly designed to optimally occupy three-dimensional space of the biological target. The design of each collection of molecules is based upon a sound biological rationale. For example, many members of the proposed libraries are natural product-like, whereas others embody known privileged structures. Prior to the synthesis of each library, computational methods, including diversity mapping, will be employed to ensure maximal structural diversity in the collection. Individual members of the collections will be verified as drug-like by application of various standard metrics, including the Lipinski Rule of Five. Each molecule will bear functionality that will allow for further development of structure activity relationships. It is expected that compounds submitted to the MLSMR will exhibit biological activities in a broad range of assays and serve as useful tools to explore biological function, thereby leading to significant improvements in disease treatment.

描述(申请人提供)：过去十年见证了科学知识和技术的显著进步，这将对人类健康产生重大影响。随着人类和其他基因组的测序，新的基因、基因产物、信号和代谢途径正在迅速被发现，从而导致识别出许多原本未知的潜在治疗靶点。为了确定活性而进行的生物测试导致了许多具有良好的物理化学和生理特性的小分子的发现。相反，小分子正越来越多地成为探索生物功能和机制的宝贵工具。尽管已经取得了惊人的进展，但仍然存在一个重大挑战，即识别具有新化学类型和结构的具有生物活性的小分子。这个问题最好通过化学合成新的、功能化的杂环框架来解决，这些框架可以很容易地阐述以优化生物活性。因此，我们将应用我们为以多样性为导向合成功能化杂环支架而独家开发的化学，以制备纯(&gt；90%)不同的、新的化合物集合的样品，以提交给NIH分子库小分子储存库(MLSMR)。这些小分子将由一系列大约25-30种不同的杂环支架衍生而来，其中一些在结构和功能上都很复杂，具有不同的取代模式，这些模式明确地设计为最佳地占据生物靶标的三维空间。每一组分子的设计都是基于合理的生物学原理。例如，提议的库中的许多成员都是类似天然产品的，而其他成员则体现了已知的特权结构。在合成每个文库之前，将采用包括多样性映射在内的计算方法，以确保集合中的最大结构多样性。通过应用各种标准指标，包括利平斯基规则五，集合的个别成员将被验证为类似药物。每个分子都将具有允许进一步发展结构活性关系的功能。预计提交给MLSMR的化合物将在广泛的检测中显示出生物活性，并成为探索生物功能的有用工具，从而显著改进疾病治疗。