and affected the performance of most models (Figure and Supplementary Table ) but improved the performance of models when used in combination with LOVO cross-validation (Figure and Supplementary Table ) for most proteins. Nonetheless, the general trend showed no clear difference between 'QSAR-All' and 'PCM-All' models derived from LOVO cross-validation from the common subsets (Figure ), suggesting that the extrapolation to new variants using PCM is similar to random prediction. These results show the complexity of accurately predicting bioactivity for individual variants. Moreover, they highlight the impact of data sparsity on model performance and how the limited size of current datasets restricts extrapolation in the protein feature space when focusing on analogue molecules. Labelled points correspond to data-rich proteins (see Table ).