Introducing structure-based three-dimensional pharmacophore models for accelerating the discovery of selective BRD9...

Area of Science:

• Medicinal Chemistry
• Computational Drug Discovery
• Structural Biology

Background:

• Bromodomain-containing protein 9 (BRD9) is an emerging target in oncology.
• Developing selective BRD9 inhibitors is crucial for therapeutic applications.
• Structure-based drug design requires efficient methods for identifying novel ligands.

Purpose of the Study:

• To develop and validate an in silico workflow for structure-based pharmacophore modeling of BRD9.
• To accelerate the virtual screening and identification of novel, selective BRD9 binders.
• To discover potential anticancer agents targeting BRD9.

Main Methods:

• Development of three-dimensional (3D) pharmacophore models based on 23 known BRD9 ligands.
• Structure-based pharmacophore model generation using known co-crystallized ligand information.
• Pharmacophore-driven virtual screening of large chemical libraries.
• Iterative refinement of the workflow using focused libraries of synthesizable compounds.

Main Results:

• Identification of a fragment-related pharmacophore model for targeting the acetyllysine recognition site.
• Discovery of novel selective BRD9 binders (compounds 7-10) through virtual screening.
• Demonstration of high selectivity for BRD9 against a panel of nine other bromodomains.
• Compound 7 exhibited promising preclinical anticancer activity, validating the in silico approach.

Conclusions:

• The reported in silico workflow effectively generates structure-based 3D pharmacophore models for BRD9.
• This computational pipeline accelerates the identification of novel and selective BRD9 ligands.
• The validated models serve as valuable tools for discovering potential therapeutic agents, particularly for anticancer applications.