Stephan A. Sieber

Molecular generators often emit reactive, metal-binding, charged or assay-interference motifs, while molecules lacking a given motif are scattered across chemical space and hard to learn as a positive class. Negative extrapolation (NE) instead fine-tunes on motif-containing molecules and reverses the resulting weight update to suppress the motif directly. On the 3D flow-matching generator SemlaFlow, standard NE lowered the fraction of valid molecules carrying any target motif from 31.1% to 5.3% but cut RDKit-valid graph yield from 93.9% to 65.9%; adding a correction direction learned from motif-free molecules brought the motif fraction to 2.2%, restored valid graph yield to 88.3%, and raised fixed-budget 3D usable yield from 60.0% to 80.8%.

Molecular generators often emit reactive, metal-binding, charged or assay-interference motifs, while molecules lacking a given motif are scattered across chemical space and hard to learn as a positive class. Negative extrapolation (NE) instead fine-tunes on motif-containing molecules and reverses the resulting weight update to suppress the motif directly. On the 3D flow-matching generator SemlaFlow, standard NE lowered the fraction of valid molecules carrying any target motif from 31.1% to 5.3% but cut RDKit-valid graph yield from 93.9% to 65.9%; adding a correction direction learned from motif-free molecules brought the motif fraction to 2.2%, restored valid graph yield to 88.3%, and raised fixed-budget 3D usable yield from 60.0% to 80.8%.