Advance of Peptide Detectability Prediction on Mass Spectrometry Platform in Proteomics
Abstract Mass spectrometry (MS) is one of the core technologies for proteome researches, by which large-scale, high-throughput qualitative and quantitative protein analysis can be carried out. Because of the complexity of samples and experimental processes, the repeatability of MS experiments is still not satisfactory; the results of peptide identification and quantification show a high randomicity, and the probability of peptides being detected by MS in proteome researches, especially in quantitative proteomic studies, has received considerable attention. Therefore, many experimental researches have been carried out, and a number of computational prediction methods have been developed. In this article, the important factors influencing the peptide detectability are summarized, the existing prediction methods are studied, and their application in experimental studies is reviewed.