Apo2ph4: A Versatile Workflow for the Generation of Receptor-based Pharmacophore Models for Virtual Screening

Area of Science:

• Computational chemistry and cheminformatics
• Drug discovery and medicinal chemistry

Background:

• Pharmacophore models are crucial for virtual screening (VS) in drug discovery.
• Traditional pharmacophore generation requires known active ligands or ligand-target complex structures.
• Discovering initial active ligands for novel targets is a significant bottleneck.

Purpose of the Study:

• To introduce a novel workflow, apo2ph4, for rapid pharmacophore model derivation.
• To enable pharmacophore generation solely from the 3D structure of target receptors.
• To demonstrate the workflow's utility in virtual screening and drug design.

Main Methods:

• Developed the apo2ph4 workflow for generating pharmacophore models from apo-receptor structures.
• Retrospectively applied apo2ph4 to the M2 muscarinic acetylcholine receptor.
• Validated apo2ph4 on 15 targets from the LIT-PCBA dataset and the GABA_A receptor.

Main Results:

• apo2ph4 successfully generated pharmacophore models without prior knowledge of active ligands.
• VS using apo2ph4-derived models achieved significant active enrichment for 13 out of 15 tested targets.
• In vitro testing of hits from a GABA_A receptor model showed 95% efficacy in enhancing GABA currents.

Conclusions:

• The apo2ph4 workflow provides a powerful method for generating high-quality pharmacophore models.
• This approach overcomes the limitation of requiring known active ligands for pharmacophore development.
• apo2ph4 demonstrates broad applicability and significant potential for accelerating real-world drug design projects.