Cross-linking mass spectrometry (XL-MS) is a technique for investigating protein-protein interactions (PPIs) and protein structures. In the realm of biology, post-translational modifications (PTMs) play a critical role in regulating PPIs and reshaping protein structures. However, existing cross-linking workflows generally require PTMs to be specified in advance, making it difficult to directly inspect modified cross-linked peptides in XL-MS data. Given the large number of candidate PTMs catalogued in the Unimod database, directly prioritizing plausible PTM hypotheses from complex cross-linked spectra remains a practical bottleneck. Here, we introduce SeaPIC, a computational screening tool that complements standard XL-MS workflows by prioritizing unspecified PTM candidates directly from cross-linked spectra and exporting compact candidate sets for downstream confirmation in regular XL-MS search engines. Using the BIOGRID data, we identify 304,969 CSMs containing 49 uncommon PTMs that would be difficult to examine in routine preset-modification searches. These results suggest that SeaPIC can facilitate PTM-oriented exploration in cross-linking studies without changing established downstream identification pipelines.