In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align؉, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of topdown protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align؉ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align؉ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align؉ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set. Molecular & Cellular Proteomics 11: 10.1074/mcp.M111.008524, 1-13, 2012.In the past two decades, proteomics was dominated by bottom-up mass spectrometry that analyzes digested peptides rather than intact proteins. Bottom-up approaches, although powerful, do have limitations in analyzing protein species, e.g. various proteolytic forms of the same protein or various protein isoforms resulting from alternative splicing. Top-down mass spectrometry focuses on analyzing intact proteins and large peptides (1-10) and has advantages in localizing multiple post-translational modifications (PTMs) 1 in a coordinated fashion (e.g. combinatorial PTM code) and identifying multiple protein species (e.g. proteolytically processed protein species) (11). Until recently, most top-down studies were limited to single purified proteins (12-15). Topdown studies of protein mixtures were restricted by difficulties in separating and fragmenting intact proteins and a shortage of robust computational tools. In the last two years, because of advances in protein separation and top-down instrumentation, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples containing hundreds and even thousands of proteins (16 -21). Because algorithms for interpreting topdown spectra are still in their infancy, many recent developments include computational innovations in protein identification.