Hybrid-CatBoost: an empirical comparison of molecular representations for aqueous-solubility prediction on the TDC benchmark
Year: 2026
Type: preprint
Abstract: Aqueous-solubility prediction depends on both molecular representation and the definition of the target. We compared fingerprint, descriptor, hybrid, and graph-based representations on the TDC Solubility_AqSolDB benchmark using five official scaffold splits and a fixed test set of 1,997 records. Hybrid-CatBoost achieved a five-run test MAE of 0.749631 ± 0.016216 TDC logS units, compared with 0.764558 ± 0.009666 for descriptor-only CatBoost. However, the corresponding validation improvement was small (ΔMAE = −0.004932) and occurred in only two of five matched splits. Errors increased toward both target extremes and showed opposite-signed residual biases. These results indicate that descriptor-based models capture most of the predictive signal in this benchmark, while the added Morgan fingerprint provides only a modest and split-dependent benefit. Interpretation is limited by incomplete assay metadata and the use of a single fixed test set, which does not provide external validation.
Source: ChemRxiv
Author: Ruming Li
Institution: Beijing University of Chemical Technology
Language: English
Subfield: Drug Discovery
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7220679730