Peptide and Protein Identification via Tandem MS and Mixed-Integer Optimization

描述（由申请人提供）： 多肽鉴定和蛋白质鉴定是蛋白质组学中的重要问题。我们建议研究一个新的多管齐下的框架从头肽测序和蛋白质鉴定下的不确定性问题，使用串联质谱。所提出的方法将基于通过混合整数优化的数学建模的基本进展，以及不确定性下的优化理论和算法。我们期望在理论和算法增强方面取得重大进展。我们提出了以下四个具体目标： 具体目标1：研究和开发一种新的肽从头计算方法 基于肽谱中的离子峰的信息以及混合整数优化建模和算法框架的识别。 具体目标2：研究用于鉴定复杂蛋白质中肽段的新方法 混合物，这将解释在计算离子峰的质/荷比时的实验不确定性。 具体目标3：研究和开发一种新的计算机混合方法，该方法将联合收割机特异性目标1的从头方法与用于肽鉴定的数据库方法相结合。 具体目标4：研究和开发一种新的蛋白质鉴定方法，该方法将联合收割机在特异性目的1-3中的进展与基于数据库同源性的方法相结合。 初步研究报告见具体目标1、2和3（第C.1、C.2、D.1、D.2、D.3节）， 通过比较研究和计算效率，结果证明了所提出的研究对于高通量肽和蛋白质鉴定的潜力。

DESCRIPTION (provided by applicant): The problems of peptide identification and protein identification are of fundamental importance in proteomics. We propose to study a new multi-pronged framework for the de novo peptide sequencing and protein identification under uncertainty problems using tandem mass spectroscopy. The proposed approach will be based on fundamental advances in mathematical modeling via mixed integer optimization, as well as theory and algorithms for optimization under uncertainty. We expect that significant advances will be introduced in theory and algorithmic enhancements. We put forward the following four specific aims: Specific Aim 1: Investigate and develop a novel de novo computational approach for the peptide identification based on information of the ion peaks in the peptide spectrum and a mixed-integer optimization modeling and algorithmic framework. Specific Aim 2: Investigate novel de novo methods for the identification of peptides in complex protein mixtures which will account for experimental uncertainty in the calculation of the mass/charge ratios of the ion peaks. Specific Aim 3: Study and develop a new hybrid in silico method which will combine the de novo approach of Specific Aim 1 with database methods for the peptide identification. Specific Aim 4: Investigate and develop a new approach for the protein identification which will combine the advances in Specific Aims 1-3 with database homology based methods. Preliminary studies are reported in Specific Aims 1, 2, and 3 (sections C.1, C.2, D.1, D.2, D.3), and the results, via comparative studies and computational efficiency, demonstrate the potential of the proposed research for high throughput peptide and protein identification.