In short, these matching algorithms and padding techniques create nine combinations (MinSum-Zero, EucDist-Zero, HungDist-Zero, MinSum-Trunc, EucDist-Trunc, HungDist-Trunc, MinSum-NN, EucDist-NN, and HungDist-NN). Next, we investigated how these combinations affected the performance of spectral matching. To achieve this, we matched the simulated HSQC spectra for the HMDB compounds to their GT and computed the normalized mean absolute error (MAE) corresponding to each matching/padding combination (Figure ). The MinSum-Zero strategy performed worst for all simulation techniques, whereas MNova with HungDist-Trunc or EucDist-Trunc gave the best results overall, although the differences between the top candidates were small. ACD was the second-best simulation technique followed by ML and DFT. Furthermore, zero-padding introduced the biggest systematic error for all matching methodologies.