Dysregulation of vascular endothelial growth factor (VEGF) and its receptor (VEGFR) contributes to atherosclerosis and cardiovascular disease (CVD), making it a potential target for CVD risk assessment. High-throughput screening (HTS) approaches have resulted in large-scale in vitro data, providing mechanistic information that can help assess chemical toxicity and identify molecular ini­tiating events (MIEs) of adverse outcome pathways (AOPs). AOPs represent a logical sequence of biological responses contributing to toxicity and are valuable tools to inform chemical risk assessment. Here, we used HTS data to formulate an AOP relating VEGF signaling perturbation to atheroscle­rosis. ToxCast, Tox21, and PubChem data were evaluated to obtain bioprofiles of 4165 compounds active in assays targeting VEGFR. Cheminformatics analysis identified 109 enriched structural fin­gerprints. Applying a subspace clustering approach based on chemical structure bioactivity yielded 12 primary targets, whose relevance to CVD was confirmed by an AI-assisted literature review. An AOP was hypothesized by coupling mechanistic relationships highlighted by HTS data with literature review findings, linking serotonin receptor (HTR), estrogen receptor alpha (ERα), and vasopressin receptor (AVPR) targets with VEGFR activity, angiogenic signaling, and atherosclerosis. Several endocrine disrupting chemicals (EDCs), e.g., bisphenols, triclosan, dichlorodiphenyltrichloroethane (DDT), and polychlorinated biphenyls (PCBs), were identified as relevant chemical stressors. Sub­space clustering of these chemicals evaluated potential MIEs and highlighted associations with use case classes. By applying computational methods to profile HTS data and hypothesize a mechanistic AOP, this study proposes a data-driven approach to evaluating environmental cardiotoxicity, which could eventually supplement and reduce the need for animal testing in toxicological assessments.

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http://dx.doi.org/10.14573/altex.2403211DOI Listing

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