Sequence analysis and Amino Acid composition of Micropeptides derived from 15 Cancer types

Noncoding peptides (ncPEPs), which are small peptides derived from noncoding RNAs, have gained immense attention in recent years because of their diverse biological functions and their specific expression. Recent advancements in technologies such as ribosome profiling and mass spectrometry have provided valuable insights into the coding potential of noncoding RNAs and their involvement in encoding micropeptides. These peptides are involved in crucial biological roles, including gene expression, cellular communication, metabolism and immune system regulation. Furthermore, they are also linked to various disease conditions, including cancer, making the study and characterization of ncPEPs essential for understanding their biological importance. This study focuses on analyzing a large dataset of ncPEPs from the SPENCER database to explore structural features and amino acid composition, with a specific focus on posttranslational modification sites. ncPEPs derived from 15 different cancer types were retrieved, with a subset of 4,505 unique sequences retained for detailed analysis. All sequences, ranging from 7 to 52 amino acids, were used for amino acid composition analysis, with a subset of peptides between 15 and 52 amino acids further subjected to structure prediction using AlphaFold2 and AlphaFold3. A particular focus was placed on serine, threonine and tyrosine residues as key sites of posttranslational modification.