Iodine-based staining techniques are commonly used in histological imaging and micro-computed tomography (μCT) due to the affinity of iodine to bind to certain molecules. However, the basis for tissue-specific contrast has not yet been sufficiently explored. In this study, we analyse the human proteome and try to identify proteins with high potential for iodine binding, especially those rich in heterocyclic amino acids. Using bioinformatic methods, we assess the occurrence of heterocyclic, homocyclic and non-aromatic amino acids in over 20,000 proteins, including isoforms. The proteins were categorized into families using curated (HGNC) and automated datasets (UniProt Similarity Index, InterPro). In particular, structural proteins such as Titin, Mucins and Collagens showed a high absolute number of heterocyclic amino acids, while small protein-rich proteins showed a high relative number. These results may explain the high μCT contrast in muscle, skin and mucosal tissues. Our results provide a general baseline