Experimentally validated HERG pharmacophore models as cardiotoxicity prediction tools

Area of Science:

• Drug Discovery and Development
• Cardiovascular Pharmacology
• Computational Chemistry

Background:

• The human Ether- குழு A-related Gene (hERG) channel is a critical target in drug development due to its association with cardiotoxicity, a leading cause of drug attrition.
• Identifying hERG channel blockers early is essential to mitigate risks and improve drug safety profiles.

Purpose of the Study:

• To design, validate, and implement a virtual screening workflow for the discovery of novel hERG channel blockers.
• To establish reliable computational tools for predicting cardiotoxic risks in early-stage drug development.

Main Methods:

• Development and theoretical validation of a ligand-based pharmacophore model collection.
• Virtual screening of compound libraries using seven selected pharmacophore models.
• Experimental validation of hit compounds using patch clamp electrophysiology to assess hERG channel inhibition.

Main Results:

• The virtual screening workflow successfully identified potential hERG channel blockers.
• Fifty selected compounds were experimentally tested for bioactivity.
• Twenty compounds demonstrated inhibition of hERG channels with IC50 values ranging from 0.13 to 2.77 µM.

Conclusions:

• The developed virtual screening models are effective for predicting hERG channel inhibition.
• The workflow serves as a valuable tool for preclinical cardiotoxicity assessment.
• This approach aids in the identification of safer drug candidates by flagging potential cardiotoxic liabilities early.