Introducing structure-based three-dimensional pharmacophore models for accelerating the discovery of selective BRD9 binders
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Updated: Oct 12, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
Martina Pierri1, Erica Gazzillo1, Maria Giovanna Chini2
1Department of Pharmacy, University of Salerno, Via Giovanni Paolo II 132, Fisciano 84084, Italy; PhD Program in Drug Discovery and Development, University of Salerno, Via Giovanni Paolo II 132, Fisciano 84084, Italy.
Abstract:
A well-structured in silico workflow is here reported for disclosing structure-based pharmacophore models against bromodomain-containing protein 9 (BRD9), accelerating virtual screening campaigns and facilitating the identification of novel binders. Specifically, starting from 23 known ligands co-crystallized with BRD9, three-dimensional pharmacophore models, namely placed in a reference protein structure, were developed. Specifically, we here introduce a fragment-related pharmacophore model, useful for the identification of new promising small chemical probes targeting the protein region responsible of the acetyllysine recognition, and two further pharmacophore models useful for the selection of compounds featuring drug-like properties. A pharmacophore-driven virtual screening campaign was then performed to facilitate the selection of new selective BRD9 ligands, starting from a large library of commercially available molecules. The identification of a promising BRD9 binder (7) prompted us to re-iterate this computational workflow on a second focused in-house built library of synthesizable compounds and, eventually, three further novel BRD9 binders were disclosed (8-10). Moreover, all these compounds were tested among a panel comprising other nine bromodomains, showing a high selectivity for BRD9. Preclinical bioscreens for potential anticancer activity highlighted compound 7 as that showing the most promising biological effects, proving the reliability of this in silico pipeline and confirming the applicability of the here introduced structure-based three-dimensional (3D) pharmacophore models as straightforward tools for the selection of new BRD9 ligands.
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