Infrastructure

基础设施

• 批准号: 8798314
• 负责人: Nuno Bandeira
• 金额: $ 26万
• 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/8798314
• 关键词: Adoption; Algorithms; Antibiotics; Antibody Repertoire; Architecture; Archives; Biological; Biological Factors; Biological Markers; Cancer Patient; Cataract; Chemicals; Clinical; Communities; Complex; Data; Development; Drug toxicity; Environment; Fingerprint; Genomics; Histone Code; Infection; Institution; Knowledge; Malignant Neoplasms; Mass Spectrum Analysis; Mission; Monoclonal Antibodies; Oncogenes; Peptides; Post-Translational Protein Processing; Proteins; Proteomics; Research Infrastructure; Scientist; Services; Software Engineering; Software Tools; Students; System; Techniques; Technology; Testing; Therapeutic; Tissues; Training; base; biomedical scientist; breast cancer vaccine; combinatorial; computerized tools; cost; empowered; human disease; next generation; novel; novel therapeutics; oral microbiome; polyclonal antibody; protein protein interaction; repository; research and development; software development; success; tool

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 质谱法是基于将生物分子碎片化为更小的碎片，并使用碎片 质量作为指纹用于识别和量化生物分子。它是一种主导技术， 研究健康和患病组织中的活性分子，识别蛋白质靶点和天然产物 用于新的治疗方法。当计算质谱中心（CCMS）最初的提案是 在2007年提交的，缺乏足够的计算工具来分析质谱数据是 关键瓶颈。在新的实验技术的应用方面取得了巨大成功， FTMS、ETD、HCD、自上而下的质谱法和许多其他方法，CCMS的任务仍然是 开发下一代计算技术，并将其应用于开放实验。在 这个建议，我们将利用我们最近在计算蛋白质组学的不同子领域的结果，并将 进一步分支到以前未开发的MS应用程序。我们将特别关注桥接蛋白质组学 基因组学技术，利用6个技术研发平台。 具体而言，我们将（a）应用蛋白质基因组学方法发现异常癌症基因， 分析抗体库;（B）对天然抗生素进行测序;（c）通过光谱分析整理光谱数据; 档案和网络;（d）开发肽鉴定的通用工具;（e）开发自上而下的工具 蛋白质组学;和（f）分析多重光谱。这些技术平台是由大量的合作生物医学研究驱动的，其中使用CCMS开发的工具对其成功至关重要。这些 研究包括（a）解开人类疾病中的组合组蛋白密码;（B）蛋白质基因组学 研究口腔微生物组和多细菌感染的方法;（c）检测物种间的化学相互作用;（d）开发乙酰组治疗调节的系统方法;（e） 开发单克隆和多克隆抗体测序工具;（f）开发乳腺癌疫苗;（g）临床癌症蛋白基因组学;（h）发现羊毛硫抗生素;（i）发现蛋白质组学生物标志物 用于癌症患者中的药物毒性;以及（j）鉴定白内障透镜中的蛋白质-蛋白质相互作用和翻译后修饰。这些项目需要三方在广泛的主题上进行合作 包括来自不同机构的生物医学科学家、质谱学家和计算科学家。 CCMS还将在计算蛋白质组学方面培训来自世界各地的学生和实践科学家， 并教育蛋白质组学社区关于现代计算质谱法，以鼓励其 广泛采用。