Combining systems biology and structural biology to find new therapeutics

描述(由申请人提供)：在过去的几年里，安全有效的新药流入市场的速度已经放缓，并威胁到我们继续改善国民健康的能力。与此同时，我们测量生物系统并了解其功能的能力正在爆炸式增长。结构基因组学让我们前所未有地获得了蛋白质的详细三维结构，在许多情况下，这些结构与调节其功能的小分子药物结合在一起。对细胞基因表达的功能基因组学测量为我们提供了药物如何通过其多种物理相互作用影响整个细胞的图景。现在的机会是将对药物结合和药物靶标相互作用的详细机制理解与药物效应的系统观点相结合，创建关于新的治疗机会的新的、高度可信的假设。在这份提案中，我们将我们在三维结构分析和基因表达分析方面的信息学专业知识与我们的医学和药物遗传学专业知识结合起来，提出一项研究计划，将结构和功能数据结合起来用于药物再利用--将先前批准的安全药物单独或与其他药物联合用于新的适应症。我们的初步工作表明，我们可以检测远距离结合部位的相似性，为现有药物提供新的靶点。它还表明， 我们可以根据新基因的表达模式，将它们与疾病和药物反应联系起来。我们建议在癌症和罕见的“孤儿”疾病的治疗方面共同发展这些。我们提出了一个有重点的计划，以(1)开发新的方法来预测蛋白质的“可药性”，(2)创建用于检测两个口袋之间的结合相似性的算法，(3)创建使用表达数据来寻找通过单一或多个重新用途的药物来靶向的最有吸引力的途径的过滤器，以及(4)应用我们的方法来提出新的癌症疗法和新的罕见疾病疗法。如果成功，我们的方法将展示如何利用分子生物学和基因组学的革命来帮助药物发现-最初是在重新用途的背景下，但最终目标是设计全新的小分子疗法。

DESCRIPTION (provided by applicant): The flow of safe and effective new drugs to the market has slowed in the last several years, and threatens our ability to continue to improve the nation's health. At the same time, our ability to measure biological systems and understand their function is exploding. Structural genomics has given us unprecedented access to the detailed three-dimensional structure of proteins, in many cases bound to small molecule drugs that modulate their function. Functional genomics measurements of cellular gene expression have given us a picture of how drugs impact the entire cell through their multiple physical interactions The opportunity now is to combine the detailed mechanistic understanding of drug binding and drug-target interaction with a systems view of drug effect, to create novel, high-confidence hypotheses about new therapeutic opportunities. In this proposal, we combine our informatics expertise in 3D structure analysis and gene expression analysis, with our medical and pharmacogenetic expertise to propose a research program to combine structural and functional data for drug repurposing-the use of previously approved and safe drugs for new indications, alone or in combination with other drugs. Our preliminary work has shown that we can detect distant binding site similarities to suggest new targets for existing drugs. It has also shown that we can associate novel sets of genes to diseases and drug-responses based on their patterns of expression. We propose to develop these together in the context of cancer and the treatment of rare "orphan" diseases. We present a focused plan to (1) develop novel methods for predicting the "druggability" of a protein, (2) create algorithms for detecting binding similarity between two pockets, (3) create filters that use expression data to find the most attractive pathways to target through single or multiple repurposed drugs, and (4) to apply our methods to propose new cancer therapies and new rare disease therapies. With success, our methods will demonstrate how the revolution in molecular biology and genomics can be harnessed to assist drug discovery-initially, in the context of repurposing, but with an eventual goal of designing entirely new small molecule therapies.