Bioinformatics Algorithms and Software for Proteomics

蛋白质组学生物信息学算法和软件

• 批准号: RGPIN-2016-03998
• 负责人: Ma, Bin
• 金额: $ 3.93万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=658167
• 关键词: Bioinformatics; Algorithms; Software; Proteomics

Proteomics aims to study all proteins in an organism, and is reshaping the health research and pharmaceutical industry. One important application of proteomics is the discovery of protein biomarkers that can be used for disease diagnoses and personalized medicine. The biomarkers also become excellent drug targets. One of the most active areas in cancer treatment today is the antibody-drug conjugates that use an antibody to recognize the biomarkers on the surface of cancer cells, and deliver the drug specifically to the cancer cells.******Mass spectrometry has become the primary method in proteomics for protein characterization. One mass spectrometry experiment can produce up to millions of mass spectra. Then, sophisticated computer algorithms are used to analyze the data and find out the proteins' identities, primary sequences, post-translational modifications (PTM), single amino acid polymorphisms (SAP), as well as quantities.******My proposed research program aims to develop the algorithms and software tools that facilitate the in-depth proteome characterization using mass spectrometry. Many of these tools will enable new capabilities for proteomics. In particular, the ultimate long-term goal of this research program is to enable the whole proteome sequencing, where all abundant proteins in a proteome, including the PTM and SAP, can be sequenced de novo in a high-throughput mass spectrometry experiment. The breakthrough will likely come from a joint innovation that involves a vast improvement of spectrometers, a novel experimental design, and innovative computer algorithms. The achievement of this goal will fundamentally change the way scientists conduct biological and health researches – just like how genome sequencing did in the past two decades. My research group has accumulated significant expertise and built a broad collaboration network with mass spectrometry labs and industrial partners. This puts us at a good position in making critical contributions to the whole proteome sequencing goal. The success will strengthen Canada's leading position in the international proteomics research.******The proteome sequencing goal may carry beyond the proposed renewal term of this NSERC Discovery program. By the end of the proposed term, we expect to have a method that can routinely de novo sequence a purified protein with mass spectrometry in minutes. This already has a profound impact to the whole proteomics field and pharmaceutical industry. Other shorter term goals include real-time PTM and SAP detection, protein quantification, as well as making the mass spectrometers smarter by result-dependent acquisition.******The accomplishment of these goals will inevitably require the participation of many talented graduate students. Many HQP will be trained in a cross-disciplinary environment. I envision that many of them will contribute innovative ideas, and grow to be independent researchers in the end.

蛋白质组学旨在研究生物体中的所有蛋白质，并正在重塑健康研究和制药行业。蛋白质组学的一个重要应用是发现可用于疾病诊断和个性化医疗的蛋白质生物标志物。生物标志物也成为优秀的药物靶标。当今癌症治疗中最活跃的领域之一是抗体-药物缀合物，其使用抗体识别癌细胞表面上的生物标志物，并将药物特异性地递送至癌细胞。质谱法已成为蛋白质组学中用于蛋白质表征的主要方法。一个质谱实验可以产生多达数百万个质谱。然后，使用复杂的计算机算法来分析数据，并找出蛋白质的身份，一级序列，翻译后修饰（PTM），单氨基酸多态性（SAP）以及数量。我提出的研究计划旨在开发的算法和软件工具，促进深入的蛋白质组表征使用质谱。其中许多工具将为蛋白质组学提供新的功能。特别是，这项研究计划的最终长期目标是实现整个蛋白质组测序，其中蛋白质组中所有丰富的蛋白质，包括PTM和SAP，都可以在高通量质谱实验中重新测序。这一突破可能来自一项联合创新，其中涉及光谱仪的巨大改进、新颖的实验设计和创新的计算机算法。这一目标的实现将从根本上改变科学家进行生物和健康研究的方式-就像基因组测序在过去二十年中所做的那样。我的研究小组积累了大量的专业知识，并与质谱实验室和工业合作伙伴建立了广泛的合作网络。这使我们处于一个很好的位置，为整个蛋白质组测序目标做出关键贡献。这一成功将加强加拿大在国际蛋白质组学研究中的领先地位。蛋白质组测序的目标可能会超出NSERC发现计划的拟议更新期限。到本学期末，我们希望有一种方法可以在几分钟内用质谱法对纯化的蛋白质进行常规的从头测序。这已经对整个蛋白质组学领域和医药行业产生了深远的影响。其他短期目标包括实时PTM和SAP检测、蛋白质定量，以及通过依赖于结果的采集使质谱仪更智能。**这些目标的实现不可避免地需要许多才华横溢的研究生的参与。许多HQP将在跨学科的环境中接受培训。我设想他们中的许多人将贡献创新的想法，并最终成长为独立的研究人员。