Another significant complication arises from the fact that most tools only support a limited set of the most common PTMs, which are typically introduced during sample processing and of artificial origin . To include novel PTMs and expand the amino acid alphabet, most de novo sequencing tools must be entirely retrained, incorporating additional data that includes these new PTMs. This is problematic because many biologically relevant PTMs occur infrequently, making it difficult to gather sufficient training data. Identifying peptides that contain multiple types of PTMs remains a formidable challenge for deep learning de novo sequencing tools.