HEDGEHOG: Hierarchical Evaluation of Drug Generators Through Rigorous Filtration
Generative molecular models can support early drug discovery by proposing new candidate compounds de novo. In practice, useful candidates must balance target-relevant activity, physicochemical properties, and other multiparameter design constraints. However, standard metrics commonly used to evaluate molecular generators only weakly reflect whether the generated compounds are medicinally plausible and suitable for downstream computation. This can produce an incomplete view of model performance and inefficient use of computational resources. We introduce HEDGEHOG, a unified six-stage filtration benchmark that is constructed as a hit identification workflow: (i) preprocessing; (ii) physicoc...
| Authors | Daria A. Ryabchenko, Pavel Gurevich, Shamil Kadyrov et al. |
|---|---|
| Primary category | cs.LG |
| Published | 14 July 2026 |
| Last updated at source | 29 September 2026 |
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