Abstract |
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Protein damage (partly followed by protein aggregation) plays a significant role in ageing, cancer and in neurodegenerative and other diseases. It is known that the proteinogenic amino acids differ in their susceptibility to non-enzymatic modification, such as hydroxylation, peroxidation, chlorination etc. In a novel bioinformatics approach, we introduce measures to quantify the susceptibility of the 20 standard proteinogenic amino acids to such modification. Based on these amino acid scores, we calculated different susceptibilities for 116,387 proteins, testing various scoring approaches. These approaches are based on review articles, text mining and a combination of both. We also show an application by combining the score information with a tool for visualization.