k-nearest neighbours (kNN) regression models were implemented using the KNeighborsRegressor function in Scikit-Learn using pre-computed dissimilarity matrices. For simplification and to facilitate further analysis, k = 1 was used; considering more than one neighbour (k > 1) provided only a slight improvement in performance (Fig. ). A 5-fold crossvalidation implemented in scikit-learn was used to calculate the mean absolute error (MAE) as a function of the number of training samples. The k closest neighbours of each structure in the dataset were found using the n-smallest method implemented in Pandas and the precomputed dissimilarity matrix.