Additional 60 peptide sets were included in the benchmark to test the performances of the fingerprints for large biomolecules. For each of 30 random linear sequences, a set containing 10,000 single-point mutants and a set containing 10,000 scrambled versions of the random sequence were generated and BLAST analogues labelled as actives. The precise generation procedure of the peptide datasets is described in our previous publication. For every set, 5 randomly selected actives were extracted and stored in a separate file. Each of the selected actives was used as a query to rank the remaining compounds in the set based on fingerprint similarity (Jaccard similarity for MinHashed fingerprints; Dice similarity for folded fingerprints). AUC, EF1, EF5, BEDROC20, BEDROC100, RIE20 and RIE100 metrics were calculated for the obtained ranked lists and averaged along the 5 queries for every set in the benchmark. Additionally, the fingerprints were ranked based on the obtained performance metrics and finally the average rank of each fingerprint determined for all metrics.