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. 2022 Jul 7;9:909499. doi: 10.3389/fmolb.2022.909499

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Copyright © 2022 Pavan, Menin, Bassani, Sturlese and Moro.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Comparison of the performance of the two Autogrow protocols in the benchmark lead-optimization runs regarding their ability to generate compounds that pass the pharmacophore filter. The VINA protocol is reported as a blue line, while the IFP_CS one is reported as an orange line. Panel (A) depicts, for each protocol, the average molecular weight of compounds within the population that pass the pharmacophore filter on a per-generation basis. The vertical axis reports the molecular weight, while the horizontal axis reports the generation number. Panel (B) depicts, for each protocol, the distribution of generated compounds that pass the pharmacophore filter regarding their molecular weight and the similarity of shape and electrostatic properties to crystal inhibitors taken as reference. The vertical axis reports the average molecular weight in Da, while the horizontal axis reports the ET _combo value. The blue dots represent compounds generated by the VINA protocol, while the orange dots represent compounds generated by the IFP_CS one.