PhosphoSitePlus (PSP), a comprehensive knowledgebase for mammalian post-translational modifications (PTMs), has expanded significantly since its inception in 2003. The database now contains over 330,000 non-redundant PTMs, with over 95% derived from mass spectrometry (MS) experiments. To enhance data reliability, early MS data have been reanalyzed using contemporary algorithms, and sites with p > 0.05 have been filtered out. Two new datasets, 'Regulatory Sites' and 'PTMVar,' are available from PSP. The 'Regulatory Sites' dataset provides curated information about modification sites that regulate cellular processes, molecular functions, and protein-protein interactions. The 'PTMVar' dataset identifies over 25,000 PTMVars (PTMs impacted by variants) that can alter signaling pathways, including missense mutations associated with diseases, polymorphisms, and cancers. The paper also discusses the evolution of sequence space, the reprocessing of high-throughput (HTP) data, and the generation of sequence logos and PSSMs from kinase-substrate interactions. The results highlight the importance of evolutionary divergence in understanding the functional significance of PTMs and the potential impact of disease-causing mutations on signaling networks.PhosphoSitePlus (PSP), a comprehensive knowledgebase for mammalian post-translational modifications (PTMs), has expanded significantly since its inception in 2003. The database now contains over 330,000 non-redundant PTMs, with over 95% derived from mass spectrometry (MS) experiments. To enhance data reliability, early MS data have been reanalyzed using contemporary algorithms, and sites with p > 0.05 have been filtered out. Two new datasets, 'Regulatory Sites' and 'PTMVar,' are available from PSP. The 'Regulatory Sites' dataset provides curated information about modification sites that regulate cellular processes, molecular functions, and protein-protein interactions. The 'PTMVar' dataset identifies over 25,000 PTMVars (PTMs impacted by variants) that can alter signaling pathways, including missense mutations associated with diseases, polymorphisms, and cancers. The paper also discusses the evolution of sequence space, the reprocessing of high-throughput (HTP) data, and the generation of sequence logos and PSSMs from kinase-substrate interactions. The results highlight the importance of evolutionary divergence in understanding the functional significance of PTMs and the potential impact of disease-causing mutations on signaling networks.