Overlaps in source data. The CPI2M dataset, derived from the integration of EquiVS and Papyrus data and originated from various public databases, necessitates a thorough examination of data overlaps to assess the need for data integration and redundancy elimination. Fig. and their intersecting dataset occupy similar structural spaces. This coherence in structural adjacency suggests that the integration of these datasets is unlikely to introduce significant shifts or discontinuities within the CPI2M dataset, supporting the validity of our data integration approach. In contrast, the visualization of protein space is notably sparser, featuring some isolated samples. A further investigation into the protein diversity was conducted by analyzing the Top 10 protein families from the InterPro 37 database within the EquiVS and Papyrus datasets, as depicted in Fig. ). This result highlights a high degree of overlap (8 out of 10) among the most prevalent protein families, such as the protein kinase superfamily, G-protein coupled receptor 1 family, and Tyr protein kinase family. This overlap signifies that the integration of EquiVS and Papyrus datasets not only complements but significantly enriches the protein diversity in the CPI2M dataset without incorporating detrimental outof-distribution samples. The examination of unique measurements and structural spaces for the CPI2M source data validates the comprehensive nature of our data curation and processing strategies.