文献类型：期刊文献

英文题名：admetSAR 3.0-derived chemical navigability rules from DrugBank-approved drugs, applied to a commercially available 2 million compound library for early drug discovery

作者：Encinar, José Antonio[1]; Yang, Chen[2]; Fernández-Ginés, Raquel[3]; Tang, Yun[2]; Cuadrado, Antonio[3]

机构：[1] Institute for Research in Biotechnology and Health [IDIBE], Miguel Hernández University [UMH], Alicante, Elche, 03202, Spain; [2] Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China; [3] Department of Biochemistry, School of Medicine, Autonomous University of Madrid [UAM], Madrid, Spain

年份：2026

外文期刊名：Research Square

收录：EI(收录号：20260299367)

语种：英文

外文关键词：Digital libraries - Docking - Drug delivery - Drug discovery - Drug interactions

摘要：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. This study extracts interpretable patterns from model-derived data to support early-stage compound prioritization. Threshold ranges were established for 117 endpoints, including drug-induced liver injury, hERG inhibition, mutagenicity, intestinal absorption, cytochrome P450 interactions, and blood–brain barrier permeability. 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 modulators 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. These findings support chemical navigability as an ADMET-driven framework for efficient early-stage compound prioritization and virtual screening. In addition, we provide a freely accessible, curated database of more than two million ADMET-annotated commercially available compounds from the MolPort library, prefiltered according to the proposed chemical navigability guidelines. All datasets and scripts are publicly available through admetSAR.umh.es. ? 2026, CC BY.