Summary of Cardiogenai: a Machine Learning-based Framework For Re-engineering Drugs For Reduced Herg Liability, by Gregory W. Kyro et al.
CardioGenAI: A Machine Learning-Based Framework for Re-Engineering Drugs for Reduced hERG Liability
by Gregory W. Kyro, Matthew T. Martin, Eric D. Watt, Victor S. Batista
First submitted to arxiv on: 12 Mar 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Biomolecules (q-bio.BM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The presented machine learning-based framework, called CardioGenAI, aims to re-engineer both developmental and commercially available drugs with reduced hERG activity while preserving their pharmacological activity. This framework incorporates novel discriminative models for predicting hERG channel activity as well as activity against the voltage-gated NaV1.5 and CaV1.2 channels. The authors applied this framework to pimozide, an FDA-approved antipsychotic agent with high affinity to the hERG channel, generating 100 refined candidates. One notable outcome is fluspirilene, a compound that exhibits over 700-fold weaker binding to hERG compared to pimozide while maintaining similar pharmacological activity. This method has potential applications in rescuing drug development programs stalled due to hERG-related safety concerns. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary CardioGenAI is a new way to make medicines safer by using artificial intelligence. The problem is that some drugs can stop the heart from beating properly, which is very bad. So, scientists want to find ways to make these drugs safer without losing their benefits. CardioGenAI helps do this by looking at how well different molecules interact with the hERG channel in cells and then uses this information to create new medicines that are less likely to cause problems. |
Keywords
* Artificial intelligence * Machine learning
