Computationally predicting prokaryotic protein subcellular localization, using experimentally-based criteria

使用基于实验的标准计算预测原核蛋白质亚细胞定位

• 批准号: 240644-2011
• 负责人: Brinkman, Fiona
• 金额: $ 4.42万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=524654
• 关键词: Computationally; predicting; prokaryotic; protein; subcellular

Computationally predicting proteins located on the surface of bacterial cells is of wide interest in both medicine and agriculture, to identify new potentially accessible (surface-exposed) drug targets, diagnostic markers, and vaccine candidates. Such analysis also aids identification of markers for environmental detection of microbes, characterization of proteins of industrial interest for their stability from thermo/cold tolerant Archaea, general genome annotation, and design of proteomic experiments. Previously, I led the development of PSORTb, which is currently the most precise predictor of bacterial and archaeal protein subcellular localization, including cell surface protein localization.

计算预测位于细菌细胞表面的蛋白质在医学和农业中具有广泛的意义，以识别新的潜在可接近（表面暴露）的药物靶标，诊断标记物和候选疫苗。这样的分析还有助于鉴定用于微生物的环境检测的标记物、表征工业感兴趣的蛋白质的耐热/耐寒性、一般基因组注释和蛋白质组学实验的设计的稳定性。此前，我领导了PSORTb的开发，这是目前细菌和古细菌蛋白质亚细胞定位（包括细胞表面蛋白定位）的最精确预测因子。