Pharmacogenomics/natural products + antifungal activity

描述(由申请人提供)： 免疫功能低下(艾滋病)的机会性真菌感染患者经常遭受高 发病率(70%)和死亡率，尽管接受了治疗，但由于缺乏治疗效果或毒性，以及对现有药物的抗药性。该项目的目标是通过将来自传统抗真菌药物发现的信息和化合物与药物基因组学方法相结合来加强抗真菌药物的发现。我们的前两个目标将是确定天然产品和FDA批准的具有抗真菌活性的药物的药物基因组学特征。这些比较药物基因组学筛选将侧重于真核细胞(人类)的毒性和致病真菌的活性。传统的药物开发过程使用一组急性和慢性毒性测试来评估安全性。然而，这种方法很耗时，动物生命代价高昂，而且往往无法预测。药物基因组学是一种有效的工具，可以测量暴露于抗真菌药物的真核细胞的差异表达基因。在成百上千个基因中观察到的差异表达可能表明一种化合物如何影响细胞过程。“签名”的细胞过程将被用来更有效地指导生物化学和动物试验 NCNPR.我们的第三个目标是建立一个“签名”数据库，并开发一个预测新代理人行为的模型。对作用机制的确认和人类不良副作用的识别是开发新药的主要挑战之一。抗真菌化合物的转录行为或“签名”数据库可以用生化、药理学和毒理学数据建模，以预测新药物的结果。在其他有希望的化合物的签名中识别潜在的毒性可能有助于更早地识别那些可能在临床试验中失败的化合物，或者允许研究人员专注于临床前研究。认识到具有新的抗真菌生物体作用机制的制剂也是一个潜在的好处。比较有希望的候选药物的“非靶标”特征的范围和特点，可以为无关的诊断提供指征的洞察。我们模型的长期好处应该包括开发一种可以从我们的模型发展出来的“治疗阵列”。此数组 将主要包含来自不同组织部位和酵母的转录本。用暴露于新型抗真菌药物的细胞中的真核mRNA来探测这一阵列将预测共同的作用机制以及毒性、活性和耐药性的可能性。

DESCRIPTION (provided by applicant): Immunocompromised (AIDS) patients with opportunistic fungal infections frequently suffer high morbidity (>70%) and mortality in spite of therapy, due to a lack of therapeutic efficacy or toxicity, and resistance to currently available agents. The goal of this project is to enhance antimycotic drug discovery by integrating information and compounds derived from traditional antifungal discovery with a pharmacogenomics approach. Our first two objectives will be to identify pharmacogenomic characteristics of natural products and FDA approved drugs with antifungal activity. These comparative pharmacogenomic screenings will focus on eukaryotic cell (human) toxicity and activity in pathogenic fungi. Traditional drug development processes utilize batteries of acute and chronic toxicity tests to evaluate safety. However, this approach is time consuming, costly in terms of animal life, and often not predictive. Pharmacogenomics is an efficient tool, permitting measurements of differentially expressed genes from eukaryotic cells exposed to antifungal agents. The differential expression observed in hundreds to thousands of genes can suggest how a compound affects cellular processes. The cellular processes of "signatures" will be used to more efficiently direct biochemical and animal testing in the NCNPR. Our third objective is to establish a database of "signatures" and develop a model that is predictive of a novel agent's behavior. Confirmation of the mechanism of action and the identification of undesirable secondary effects in man are among the main challenges in developing new drugs. A database of transcriptional behaviors or "signatures" for antimycotic compounds can be modeled with biochemical, pharmacological and toxicological data to predict outcomes of new agents. Recognition of potential toxicities in the signatures of otherwise promising compounds may allow earlier identification of those likely to fail in clinical trials or allow investigators to focus preclinical investigations. Recognition of agents with new mechanisms of action against mycotic organisms is also a potential benefit. Comparing the extent and peculiarities of "off-target" signatures of promising drug candidates could provide insight into indications for an unrelated diagnoses. A long-term benefit of our model should include the development of a "therapeutic array" which could be developed from our model. This array would contain mainly transcripts from various tissue sites and yeast. Probing this array with eukaryotic mRNA from cells exposed to novel antifungals would predict common mechanism of action and likelihood of toxicity, activity and resistance.