Developing an integrative bioinformatic approach for the selection of therapeutic targets

与人类生物学相关的基因组和结构数据的爆炸式增长，以及用于查询这些数据的计算工具的不断发展，为研究人类生物学提供了新的机会。本研究计划的目标是将这种范式应用于目标发现过程。我们将开发新的方法来识别蛋白质靶点，这些蛋白质靶点既与疾病有明确的遗传联系，又在结构上是可药物化的。我们的长期目标是扩大从这一工作中吸取的方法和经验教训，以进一步在原子和遗传水平上整合作为生物过程基础的分子电路。拥抱开放科学的概念将促进我们的发现在我们现有的合作者网络中传播，并最大限度地发挥我们的影响。靶蛋白的选择是大多数药物发现计划的第一步，并决定该计划是否成功或失败，以提供新的药物给患者。如果目标的三维结构在化学上不容易处理，程序在开始之前就注定要失败。同样重要的是，必须确定靶蛋白在疾病途径中的致病和重要作用。为了提高药物发现的成功率，需要更好地了解目标选择过程。开始充斥生物医学界的大数据是一种变革性的信息来源。我研究项目的全球目标是整合结构和基因组学数据来研究人类生物学，重点是健康和疾病中的转录调节。在这项提案中，我们将把重点放在基因表达调控上，这是一个对多种疾病途径至关重要但抵制大多数药物发现努力的生物学领域，我们将把癌症患者染色体畸变的大型数据库与合成致死性筛选相结合。（其中基因A的缺失导致对基因B的生存依赖性）以鉴定肿瘤特异性遗传脆弱性，并揭示药物应该靶向的蛋白质。我们还将分析数千种人类蛋白质高分辨率结构表面结合口袋的药物可药性和结构多样性，以确定物理上可以被药物靶向的靶点。我们将在蛋白质网络和信号通路的背景下绘制能够、应该和被药物靶向的蛋白质，并确定迄今为止被忽视的新的高优先级靶点。从事该项目的学生将获得结构生物信息学和计算基因组学方面的一套罕见的专业知识，并将受益于由结构生物学家，生物化学家，细胞生物学家组成的跨学科，开放空间环境。他们还将能够与多伦多市中心充满活力的当地生物信息学社区分享和学习。

The exploding volume of genomic and structural data related to human biology, and the continuous development of computational tools to interrogate this data generate novel opportunities to investigate human biology. The goal of this research program is to apply this paradigm to the target discovery process. We will develop novel methodologies to identify protein targets that both have clear genetic linkage to disease, and are structurally druggable. Our long-term goal is to expand methodologies and lessons learnt from this exercise to further integrate at the atomic and genetic level the molecular circuitry that underlies biological processes. Embracing an open science concept will facilitate the dissemination of our findings across and beyond our existing network of collaborators, and maximize our impact.******Selection of a target protein is the first step in most drug discovery programs, and determines whether the program will succeed or fail to deliver a new drug to patients. If the three-dimensional structure of the target is not chemically tractable, the program is doomed before it started. Equally important is the necessity to establish a causative and essential role of the targeted protein in the disease pathway. To increase the success rate in drug discovery, the target selection process needs to be better informed.******Big Data that started flooding the biomedical community is a transformative source of information. The global goal of my research program is to integrate structural and genomics data to investigate human biology, with a focus on the regulation of transcription in health and disease. In this proposal, while focusing on the regulation of gene expression, an area of biology that is central to multiple disease pathways but has resisted most drug discovery efforts, we will interface large databases of chromosomal aberrations from cancer patients and synthetic lethality screens (where deletion of Gene A causes dependency on Gene B for survival) to identify tumor-specific genetic vulnerabilities, and reveal proteins that should be targeted by drugs. We will also analyze the druggability and structural diversity of binding pockets at the surface of thousands of high-resolution structures of human proteins to identify targets that physically can be targeted by drugs. We will map proteins that can, that should, and that are targeted by drugs in the context of protein networks and signalling pathways, and identify novel high-priority targets that so far have been neglected. Students working on this project will acquire a rarely combined set of expertise in structural bioinformatics and computational genomics, and will benefit from a cross-disciplinary, open space environment composed of structural biologists, biochemists, cell biologists. They will also be able to share with and learn from the vibrant local bioinformatics community of downtown Toronto.