Generated 3D-common feature hypotheses using the HipHop method for developing new topoisomerase I inhibitors

Area of Science:

• Medicinal Chemistry
• Computational Drug Discovery
• Pharmacology

Background:

• Designing novel topoisomerase I (Topo I) inhibitors is crucial for cancer therapy.
• Existing computer-aided drug discovery efforts for Topo I inhibitors are limited, and structure-based methods have drawbacks.

Purpose of the Study:

• To develop a ligand-based, three-dimensional (3D) pharmacophore model for identifying novel Topo I inhibitory scaffolds.
• To overcome limitations of structure-based drug design by focusing on common features of known ligands.

Main Methods:

• Utilized the HipHop module in Discovery Studio to generate pharmacophore hypotheses.
• Used clinically approved Topo I inhibitors (camptothecin, topotecan, belotecan, SN-38) as input.
• Selected topotecan's docked pose as a reference and analyzed the best hypothesis (Hypo 01) with six features.

Main Results:

• Generated 10 pharmacophore hypotheses, with Hypo 01 selected for further analysis.
• Hypo 01 comprised two hydrogen-bond acceptors, one hydrogen-bond donor, one hydrophobic aromatic, one hydrophobic aliphatic, and one aromatic ring.
• Validated the model using camptothecin derivatives and identified five potential Topo I inhibitors from the DruglikeDiverse database.

Conclusions:

• The developed 3D pharmacophore model is a valuable tool for discovering new Topo I inhibitory scaffolds.
• This ligand-based approach can guide the design of novel and potent Topo I-targeting antitumor drugs.