Here, we thoroughly evaluate the risks and opportunities presented by variant annotation in bioactivity databases by extensively characterising variant-annotated bioactivity data in the ChEMBL 31 database. Through an assessment of annotation fidelity, the non-triviality of this task is highlighted, and adjustments are proposed to improve the ChEMBL variant annotation pipeline for future releases. A revised bioactivity dataset with protein amino acid substitution annotations is derived from this work and enriched with curated data from literature (Christmann subset) previously curated as part of the Papyrus dataset . The additional data is aggregated in this work with the ChEMBL annotated data following the pipeline with rigorous data curation and filtering, and standardization of molecular structures that were applied to obtain the Papyrus dataset. Furthermore, we investigate the distribution of variant-annotated bioactivity data points in the combined dataset across organisms, protein families, individual targets, and specific variants; and evaluate the effect of variants in bioactivity distribution and modelling. These findings not only contribute to advancing our understanding of the effects of amino acid substitutions in bioactivity but also provide invaluable insights for refining bioactivity data curation practices, particularly concerning variants, for enhanced predictive modelling purposes. Our work also highlights the importance of reporting comprehensively the full sequences of proteins used in bioassays and bioactivity measurements, in both the literature and when depositing data directly into databases.