J Chem Inf Model. 2026 Jul 21. doi: 10.1021/acs.jcim.6c01901. Online ahead of print.
ABSTRACT
Clinical attrition in drug development is frequently driven by suboptimal pharmacokinetic and toxicological (ADMET) properties rather than inadequate target efficacy. Accordingly, early-stage ADMET assessment has become an increasingly important component of Structure-Based Drug Design (SBDD). Here, we present empirically derived chemical navigability guidelines based on an analysis of ADMET-related properties predicted by admetSAR 3.0 across approved drugs curated from DrugBank. These parameters were integrated into an intuitive color-coded visualization framework for rapid compound assessment. The proposed guidelines are intended as context-dependent heuristics derived from statistical trends within the predicted chemical space of approved drugs rather than as universal decision rules. The utility of the ADMET-first strategy was further evaluated using an external and independent library of 1,756 KEAP1/NRF2 modulator compounds from ChEMBL, employing experimentally determined biological activity (pChEMBL) instead of docking-derived metrics. Enrichment analysis demonstrated that ranking compounds according to the ADMET-score identified true active compounds substantially earlier than random selection, achieving an enrichment factor (EF) of 1.29 in the top 5% of the library and recovering approximately 80% of active compounds within a limited fraction of the evaluated chemical space. We provide a freely accessible (https//admetSAR.umh.es), curated database of more than two million ADMET-annotated commercially available compounds from the MolPort library, prefiltered according to the proposed chemical navigability guidelines.
PMID:42478342 | DOI:10.1021/acs.jcim.6c01901
