Increasing the speed and accuracy of proteomics protocols through the development of accurate peptide retention prediction models in RP-HPLC

在过去的二十年里，质谱学(MS)和液相色谱学(LC)的发展取得了重大突破，为生物和健康科学的研究提供了前所未有的能力。我的团队的研究主要集中在开发高效液相色谱中的多肽保留预测模型，以及它们在实际蛋白质组学分析中的应用：准确的多肽保留预测将使LC-MS系统的整体分辨率和性能显著提高。我的研究计划的首要目标是开发一个多肽与疏水色谱介质相互作用的综合物理化学模型。除了代表了层析科学的重大进展外，这项研究还将有助于理解蛋白质/肽与疏水生物膜的相互作用--这是细胞生物学和生化研究中的关键过程之一。 自2004年发表以来，我们的序列特异性保留计算器模型已经成为该领域的基准工具，引起了普通蛋白质组学社区的关注。马尼托巴大学和领先的蛋白质组设备和软件制造商之一ThermoFisher Science于2010年10月签署了一项许可协议，将SSRCalc纳入他们仪器的分析软件中，进一步表明了这一主题的重要性和我们在该领域的领导地位。 我们通过对α-螺旋结构与疏水固定相相互作用时稳定性的物理化学模拟，进一步提高了SSRCalc算法的精度。我们还计划开发新的实用方法，利用高性能商品图形卡作为多肽识别引擎，快速动态生成多肽排除/包含列表，从而提高LC-MS分析的速度和容量。

Significant breakthroughs in development of mass-spectrometry (MS) and liquid chromatography (LC) in the past two decades now provide unprecedented capabilities for studies in biological and health sciences. My group's research has focused on the development of peptide retention prediction models in liquid chromatography, and their application to practical proteomic analysis: accurate peptide retention prediction will allow significant increase in overall resolution and performance of LC-MS systems. The overarching goal of my research program is the development of a comprehensive physico-chemical model of peptide interaction with hydrophobic chromatographic media. In addition to representing significant advances in chromatographic science, this research will also help in the understanding of protein/peptide interactions with hydrophobic biological membranes - one of the key processes in cell biology and biochemical studies. Since its publication in 2004, our Sequence Specific Retention Calculator model has become a benchmark tool in the field, attracting attention from the general proteomics community. The University of Manitoba and one of the leading manufacturers of proteomic equipment and software, ThermoFisher Scientific, signed a licensing agreement in October 2010 to incorporate SSRCalc into the analytical software of their instruments, further indicating importance of this topic and our leadership in this field. We propose further improvements to the SSRCalc algorithm's accuracy through the physico-chemical modeling of the stabilization of alpha-helical structures upon interaction with hydrophobic stationary phase. We also plan to develop new applied approaches that will increase both the speed and capacity of LC-MS analyses using the fast on-the-fly generation of peptide exclusion/inclusion lists using high performance commodity graphics cards as peptide identification engines.