Abstract 6996: Integrating high-throughput screening with ligand-based pharmacophore modeling and virtual screening strategies to optimize exonuclease 1 inhibitor design

Abstract Pharmacophores are the specific steric and electronic features of a small molecule that are necessary to ensure interaction with a specific biological target and to trigger or block its biological response. Three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore modeling is a computational approach that utilizes data collected from in vitro experiments and molecular docking to map the shared features of known actives, producing a template that can be used to optimize the physical and chemical properties of lead compounds. Our goal is to generate a 3D-QSAR model for exonuclease 1 (EXO1) inhibition to support the pre-clinical development of a potent, EXO1-specific, small molecule inhibitor and define the molecular interactions that drive inhibitor specificity toward EXO1 instead of related nucleases. Construction of this model will facilitate the development of a potent EXO1 inhibitor that is selective, cancer-specific, and synthetic lethal with BRCAness. Additionally, it will establish a structural foundation for enhancing the selectivity of inhibitors targeting highly similar 5’ nuclease family members, such as FEN1. Here, we describe our approach to integrating the high-throughput and virtual screening data we have collected for ∼365, 000 small molecule compounds to map a preliminary 3D-QSAR hypothesis for EXO1 inhibition. Citation Format: Jessica Hess, Li Zheng, Binghui Shen. Integrating high-throughput screening with ligand-based pharmacophore modeling and virtual screening strategies to optimize exonuclease 1 inhibitor design [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6996.