Targeting MDR-TB

针对耐多药结核病

• 批准号: 7936235
• 负责人: Robert C Reynolds
• 金额: $ 50万
• 依托单位: SOUTHERN RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-26 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7936235
• 关键词: Address; Animal Model; Antimycobacterial Agents; Antitubercular Agents; Biological Assay; Chemicals; Chemistry; Cluster Analysis; Collection; Commerce; Communities; Data; Data Set; Databases; Deposition; Development; Disease; Disease Resistance; Drug resistance; Exercise; Extreme drug resistant tuberculosis; Funding; Future; Goals; Government; Individual; Intention; Laboratories; Libraries; Mammalian Cell; Multi-Drug Resistance; Mycobacterium tuberculosis; National Institute of Neurological Disorders and Stroke; Pharmaceutical Chemistry; Pharmaceutical Preparations; Phosphotransferases; Property; Proteins; Proteome; PubChem; Publications; Publishing; Relative (related person); Reporting; Research; Research Institute; Research Personnel; Sampling; Screening Result; Screening procedure; Series; Staging; Structure-Activity Relationship; Systems Biology; Therapeutic Agents; Time; Translating; Translations; Tuberculosis; analog; base; computational chemistry; cytotoxicity; drug development; drug discovery; follow-up; high throughput screening; improved; inhibitor/antagonist; interest; literature citation; mycobacterial; novel therapeutics; programs; public health relevance; scaffold; small molecule libraries; tool; tuberculosis drugs

DESCRIPTION (provided by applicant): Highly drug resistant forms of tuberculosis termed multidrug resistant (MDR) and extensively drug resistant (XDR) tuberculosis are on the rise worldwide raising the specter that this disease may once again become virtually incurable. Through two government sponsored screening programs (the MLSCN and TAACF), a large amount of preliminary high throughput screening (HTS) data will soon become available to the research public relating to the discovery of compounds that might target highly drug resistant forms of tuberculosis. Unfortunately, these data are early stage preliminary results, and active compounds from these screens need further translation through the tuberculosis drug discovery pipeline. Oftentimes, however, individual researchers do not readily have access to the funds or tools required to properly prioritize the vast amounts of HTS data into specific scaffolds for further medicinal chemistry and drug development. It is our intention to carry out the appropriate early stage exercises necessary to translate this vast set of preliminary data into manageable information that will help the community and small biotech companies to focus on the best compound classes in their efforts to pursue new drugs against tuberculosis. Specifically, we will cluster the total data set of available HTS information into active sets of compounds that have good medicinal chemistry properties and minimal reactive functions; sets will be selected based on dissimilarity to known antitubercular drugs and known literature citations. With this information we will carry out chemistry through commerce, buying an initial follow up set of compounds in approximately ten of the top clusters for a total of 1,000 compounds. These samples will be screened in a variety of assays used for prioritizing potential new antitubercular drugs. From these results, a subset of 300 compounds will be identified and purchased in 3-5 of the most active clusters in order to flesh out a more thorough structure-activity relationship. Further screens are proposed to add value to the specific compounds chosen. Such an approach is more efficient in terms of time and money, and this program should help readily move the large screening data into focused drug discovery programs in the community. The proposed studies are anticipated to result in ten highly active clusters of compounds showing interesting antitubercular activity in a series of accepted panels of screens for new drug discovery candidates. Furthermore, we expect to identify approximately three classes of compounds showing significant activity throughout the prioritization panel including activity against MDR and XDR tuberculosis strains; these candidates should be a high priority for future drug discovery programs. Broadly, this application addresses the challenge of pursuing the development of new drugs for the treatment of drug resistant forms of tuberculosis, particularly MDR and XDR strains. Specifically, this program will continue the advancement of preliminary active compounds from the TAACF program further along the development pipeline. In terms of an impact, the goal of this application will be to bring data for a select set of compounds that have promise for new drug discovery into the public and commercial domain for further advancement towards new antitubercular agents to treat drug resistant disease.

描述（由申请人提供）：被称为多药耐药（MDR）和广泛耐药（XDR）结核病的高度耐药形式在全球范围内呈上升趋势，这引起了人们对这种疾病可能再次变得几乎无法治愈的担忧。通过两个政府资助的筛选计划（MLSCN和TAACF），大量的初步高通量筛选（HTS）数据将很快提供给研究公众，这些数据与发现可能靶向高度耐药形式的结核病的化合物有关。不幸的是，这些数据是早期阶段的初步结果，来自这些筛选的活性化合物需要通过结核病药物发现管道进一步转化。然而，通常情况下，个别研究人员并不容易获得所需的资金或工具，以适当地优先考虑大量的HTS数据到特定的支架，用于进一步的药物化学和药物开发。我们打算开展必要的适当早期工作，将这一庞大的初步数据转化为可管理的信息，帮助社区和小型生物技术公司在寻求抗结核新药的努力中专注于最佳化合物类别。具体来说，我们将聚类的总数据集的HTS信息到活性组的化合物，具有良好的药物化学性质和最小的反应功能;集将选择的基础上，已知的抗结核药物和已知的文献引用的相异。有了这些信息，我们将通过商业进行化学研究，在大约10个顶级集群中购买一组初始后续化合物，总共1,000种化合物。这些样本将在用于优先考虑潜在的新抗结核药物的各种测定中进行筛选。根据这些结果，将在3-5个最活跃的簇中鉴定和购买300种化合物的子集，以充实更全面的结构-活性关系。建议进一步筛选，以增加所选特定化合物的价值。这种方法在时间和金钱方面更有效，并且该计划应该有助于将大型筛选数据轻松地转移到社区的重点药物发现计划中。预计拟议的研究将产生10个高活性化合物簇，在一系列可接受的新药发现候选人筛选小组中显示出有趣的抗结核活性。此外，我们预计将确定大约三类化合物，这些化合物在整个优先级组中显示出显著的活性，包括对MDR和XDR结核菌株的活性;这些候选物应该是未来药物发现计划的高度优先事项。概括地说，本申请解决了寻求开发用于治疗结核病的耐药形式，特别是MDR和XDR菌株的新药的挑战。具体而言，该计划将继续推进TAACF计划中的初步活性化合物进一步沿着开发管道。就影响而言，本申请的目标是将一组有希望发现新药的选定化合物的数据带入公共和商业领域，以进一步推进新的抗结核药物治疗耐药性疾病。