Assessing Significance of Peptide Spectrum Match Scores
Natural products are chemical compounds that are produced by a living organism and some of them have evolved to become perfect defence weapons. Despite advances in synthetic methodology, 68% of antibacterial, and 54% of new anticancer chemical entities are nonlinear natural products and such natural products as Vancomycin and Daptomycin are among the most effective antibiotics. Recently, new mass spectrometry-based methods have been developed for interpreting mass spectra of cyclic peptides using de novo sequencing and database search. Unfortunately, the question of evaluating statistical significance of Peptide Spectrum Matches (PSM) in database search for these peptides remains open, which leads us to the problem of rare events estimation. In this work, we develop a method for estimating statistical significance of PSMs defined by any peptide and the key idea of our method is using Markov Chain Monte-Carlo approach coincidentally with Wang-Landau algorithm.