Dissemination

传播

• 批准号: 8930719
• 负责人: Pavel A Pevzner
• 金额: $ 11.67万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8930719
• 关键词: Adoption; Antibiotics; Antibody Repertoire; Archives; Bioinformatics; Biological; Biological Factors; Biological Markers; Cancer Patient; Cataract; Chemicals; Clinical; Collaborations; Communities; Data; Data Set; Development; Drug toxicity; Fingerprint; Galaxy; Genomics; Histone Code; Infection; Institution; International; Journals; Malignant Neoplasms; Mass Spectrum Analysis; Monoclonal Antibodies; Oncogenes; Peptides; Post-Translational Protein Processing; Proteins; Proteomics; Publications; Scientist; Software Engineering; Software Tools; Students; System; Techniques; Technology; Therapeutic; Tissues; Training; base; biomedical scientist; breast cancer vaccine; collaborative environment; combinatorial; computerized tools; data sharing; human disease; interest; knowledge base; lectures; next generation; novel therapeutics; oral microbiome; polyclonal antibody; protein protein interaction; research and development; success; symposium; tool; web site

Project Summary 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 collaborative 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 interactions; (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 vaccines; (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 modifications 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.

项目摘要 质谱法基于碎片生物分子成较小的碎片，并使用碎片 质量是识别和量化生物分子的指纹。这是主要技术 研究健康和患病组织中的活性分子，并鉴定蛋白质靶标和天然产物 用于新颖的治疗学。当最初的计算质谱中心（CCM）为 在2007年提交的情况下，缺乏用于分析质谱数据数据的足够计算工具是 钥匙瓶颈。在实现新实验技术的应用方面取得了巨大成功 FTMS，ETD，HCD，自上而下的质谱法等，CCM的任务继续为 下一代计算技术的开发并将其应用于打开实验。在 这项建议，我们将利用我们最近在计算蛋白质组学各种子场的结果，并将 进一步分支到先前未开发的MS应用程序中。我们将专门关注桥接蛋白质组学 和基因组技术使用6个技术研发平台。 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和 分析抗体库； （b）序列天然抗生素； （c）通过光谱整理光谱数据 档案和网络； （d）开发用于肽识别的通用工具； （e）开发自上而下的工具 蛋白质组学； （f）分析多重光谱。技术平台是由多种协作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）检测物种间的化学相互作用； （d）开发一种用于乙酰基体治疗调节的系统方法； （E） 开发单克隆和多克隆抗体测序的工具； （f）开发乳腺癌疫苗； （g）临床癌蛋白质组学； （h）发现甘拟酰化药物； （i）发现蛋白质组学生物标志物 用于癌症患者的药物毒性； （j）鉴定白内障晶状体中蛋白质蛋白质相互作用和翻译后修饰。这些项目需要在广泛的主题上进行三路的协作努力 涉及来自各个机构的生物医学科学家，质谱学家和计算科学家。 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 广泛采用。