Center for Computational Mass Spectrometry

计算质谱中心

• 批准号: 8798310
• 负责人: Vineet Bafna
• 金额: $ 135.79万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-20 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8798310
• 关键词: Acetylation; Address; Adoption; Algorithmic Software; Algorithms; Antibiotics; Antibodies; Antibody Repertoire; Archives; Area; Biological; Biological Factors; Biological Markers; Cancer Patient; Cancer Vaccine Related Development; Cataract; Chemicals; Clinical; Communicable Diseases; Communities; Complex; Computer software; DNA Sequence; Data; Databases; Dental caries; Development; Drug Targeting; Drug toxicity; Emerging Technologies; Fingerprint; Generations; Genes; Genome; Genomics; Goals; Guanine Nucleotide Exchange Factors; Health; Histone Code; Histones; Human; Human Microbiome; Industry; Infection; Institution; Libraries; Link; Malignant Neoplasms; Mass Spectrum Analysis; Mining; Monoclonal Antibodies; Mutation; Oncogenes; Peptides; Post-Translational Protein Processing; Protein Isoforms; Proteins; Proteome; Proteomics; Protocols documentation; Research; Scientist; Services; Software Tools; Students; System; Techniques; Technology; Therapeutic; Therapeutic antibodies; Tissues; Training; base; biomedical scientist; combinatorial; computerized tools; drug discovery; human disease; improved; instrument; instrumentation; lens; malignant breast neoplasm; microbial; next generation; next generation sequencing; novel; novel therapeutics; oral microbiome; polyclonal antibody; protein aminoacid sequence; protein protein interaction; research and development; response; success; tool

DESCRIPTION: Mass spectrometry is based on fragmenting biological molecules into smaller pieces, and using the fragment masses as a fingerprint for identifying and quantifying bio-molecules. It is the dominant technology for studying active molecules in healthy and diseased tissue, and identifying protein targets and natural products for novel therapeutics. When the initial proposal Center for Computational Mass Spectrometry (CCMS) was submitted in 2007, the lack of adequate computational tools for analyzing mass spectrometry data was the the key bottleneck. With great success in enabling applications of new experimental techniques such as FTMS, ETD, HCD, top-down mass spectrometry, and many others, the mandate of CCMS continues to be the development of next generation computational technologies and to apply them to open experimental. In this proposal, we will capitalize on our recent results in diverse subfields of computational proteomics and will further branch into previously unexplored MS applications. We will focus specifically on bridging proteomics and genomics technologies using 6 technology research and development platforms. Specifically, we will (a) apply proteogenomics approach for the discovery of abberant cancer genes and analyzing antibody repertoires; (b) sequence natural antibiotics; (c) collate spectral data through spectral archives and networks; (d) develop universal tools for peptide identification; (e) develop tools for top-down proteomics; and, (f) analyzing multiplexed spectra. The technology platforms are driven by a multitude of col- laborative biomedical studies where the use of CCMS developed tools is essential for their success. These studies include (a) unraveling the combinatorial histone code in human diseases; (b) a proteogenomics approach to studies of oral microbiome and polybacterial infections; (c) detecting inter-species chemical in- teractions; (d) developing a systems approach towards the therapeutic modulation of the acetylome ; (e) developing tools for monoclonal and polyclonal antibody sequencing; (f) development of breast cancer vac- cines; (g) clinical cancer proteogenomics; (h) discovery of lantibiotics; (i) discovering proteomic biomarkers for drug toxicity in cancer patients; and, (j) identifying protein-protein interactions and post-translational mod- ifications in cataractous lens. These projects require three-way collaborative efforts on a wide range of topics involving biomedical scientists, mass spectrometrists, and computational scientists from various institutions. CCMS will also train students and practicing scientists from all over the world in computational proteomics, and educate the proteomics community about modern computational mass spectrometry to encourage its wide adoption.

描述：质谱法基于将生物分子分成较小的碎片，并将碎片质量用作指纹识别和量化生物分子的指纹。它是研究健康和患病组织中活性分子的主要技术，并鉴定出用于新型治疗剂的蛋白质靶标和天然产物。当最初的计算质谱中心（CCM）于2007年提交时，缺乏用于分析质谱数据数据的足够计算工具是关键的瓶颈。在实现新实验技术（例如FTMS，ETD，HCD，自上而下的质谱法）等新实验技术方面的应用方面取得了巨大成功，CCM的任务继续是下一代计算技术的发展，并将其应用于开放实验。在此提案中，我们将利用我们最近在计算蛋白质组学的各种子场的结果，并将进一步分为以前未开发的MS应用程序。我们将使用6个技术研发平台专门关注桥接蛋白质组学和基因组技术。具体而言，我们将（a）采用蛋白质组学方法来发现绿色癌基因并分析抗体库； （b）序列天然抗生素； （c）通过光谱档案和网络对光谱数据进行整理； （d）开发用于肽识别的通用工具； （e）开发自上而下蛋白质组学的工具； （f）分析多重光谱。技术平台是由多种集体生物医学研究驱动的，在该研究中，使用CCMS开发的工具对于它们的成功至关重要。这些研究包括（a）在人类疾病中阐明组合组蛋白代码； （b）一种蛋白质组学方法，用于研究口腔微生物组和多分裂感染的研究； （c）检测物种间化学的侵蚀； （d）开发一种用于乙酰基体治疗调节的系统方法； （e）开发用于单克隆和多克隆抗体测序的工具； （f）开发乳腺癌毒素； （g）临床癌蛋白质组学； （h）发现甘拟酰化药物； （i）发现蛋白质组学 癌症患者药物毒性的生物标志物； （j）识别白内障晶状体中蛋白质 - 蛋白质相互作用和翻译后的模型。这些项目需要在涉及生物医学科学家，质谱学家和来自各个机构的计算科学家的广泛主题上进行三路协作。 CCMS还将培训来自世界各地的学生和实践科学家的计算蛋白质组学，并教育蛋白质组学社区有关现代计算质谱法的教育，以鼓励其广泛采用。