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家健康的能力。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。结构基因组学为我们提供了前所未有的蛋白质详细三维结构，在许多情况下，蛋白质与调节其功能的小分子药物结合。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-靶点相互作用的详细机制理解与药物效应的系统观点相结合，以创造关于新治疗机会的新颖，高置信度的假设。在这项提案中，我们将联合收割机在3D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相结合，提出了一项研究计划，将联合收割机的结构和功能数据结合起来进行药物再开发-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，我们可以检测到遥远的结合位点相似性，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“孤儿”疾病治疗的背景下共同开发这些药物。我们提出了一个重点计划：（1）开发新的方法来预测蛋白质的“药物性”，（2）创建用于检测两个口袋之间结合相似性的算法，（3）创建使用表达数据的过滤器，以找到最有吸引力的途径，通过单一或多种重新用途的药物靶向，（4）应用我们的方法来提出新的癌症疗法和新的罕见病疗法。随着成功，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，在重新利用的背景下，但最终的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.