FaSTPACE: a fast and scalable tool for peptide alignment and consensus extraction

Several novel high-throughput experimental techniques have been developed in recent years that generate large datasets of putative biologically functional peptides. However, many of the computational tools required to process these datasets have not yet been created. In this study, we introduce FaSTPACE, a fast and scalable computational tool to rapidly align short peptides and extract enriched specificity determinants. The tool aligns peptides in a pairwise manner to produce a position-specific global similarity matrix for each peptide. Peptides are realigned in an iterative manner scoring the updated alignment based on the global similarity matrices of the peptides and updating the global similarity matrices based on the new alignment. The method then iterates until the global similarity matrices converge. Finally, an alignment and consensus motif are extracted from the resulting global similarity matrices. The tool is the first to support custom weighting for the input peptides to satisfy the pressing need to include experimental attributes encoding peptide confidence in specificity determinant extraction. FaSTPACE exhibited state-of-the-art performance and accuracy when benchmarked against similar tools on motif datasets generated using curated peptides and high-throughput data from proteomic peptide phage display. FaSTPACE is available as an open-source Python package and a web server.