Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS

Understand

The discovery of small molecules with therapeutic potential is a long-standing challenge in chemistry and biology.

• Researchers have increasingly leveraged novel computational techniques to streamline the drug development process to increase hit rates and reduce the costs associated with bringing a drug to market.
• To this end, we introduce a quantum-classical generative model that seamlessly integrates the computational power of quantum algorithms trained on a 16-qubit IBM quantum computer with the established reliability of classical methods for designing small molecules.
• Our hybrid generative model was applied to designing new KRAS inhibitors, a crucial target in cancer therapy.