Protein post-translational modification?PTM? plays key roles in the function of proteins and cellular processes. Nonsynonymous single nucleotide variations?nsSNVs? could damage PTMs. In this study, we performed a series of characteristic extraction and association analysis on nsSNVs and PTMs; moreover, based on the distribution of nsSNVs and PTMs in different diseases, we performed structural and functional analysis, network construction and identifying biomarkers. We chose eight important PTMs to perform the analysis and found that SUMOylation has the highest conservation while phosphorylation the least. We also found that PTM types with sequence selection have less nsSNVs around PTM sites, such as phosphorylation, glycosylation and hydroxylation; instead, acetylation, SUMOylation and Ubiquitylation have more nsSNVs around PTM sites. Only some of the nsSNVs can change the attributes of associated amino acids and affect PTMs directly. Next, we analyzed damaged PTM associated inherited diseases and cancers, the most significantly related inherited disease was “Li-Fraumeni syndrome,LFS”, the most significantly related cancer was “Lung cancer”. We performed protein-protein interaction analysis?PPI? and PTM crosstalk analysis for Lung cancer and LFS respectively and extracted the important modules: for lung cancer PPI network modules, the protein biomarkers bearing damaged PTMs included EGFR?MAP2K4?ABL1?STK33?KRAS?IGF1R;For “Li-Fraumeni syndrome”, we found T155?Phosphorylation?, K292?Ubiquitylation?, R213?Methylation? on TP53 showed crosstalk between PTM sites. In this study, we focused on the concept of damaged PTMs and calculated the impact of nsSNVs on PTMs with new statistical methods; we showed PTM crosstalk in network and found possible biomarkers or molecular targets in significantly related diseases for future research. |