Quantum computing for drug discovery

Yu-Yuan (Stuart) Yang | Feb 16, 2025 min read

[The summary is organized by GPT-4o.]

The project explores how quantum computing is revolutionizing drug discovery by accelerating timelines and reducing costs in a traditionally lengthy and expensive process. It highlights quantum applications in key stages of drug development.

Key Points

1. Drug Development Process

  • Involves target discovery, hit identification, lead optimization, preclinical/clinical trials, and typically spans 10-15 years with costs exceeding $2 billion.

2. Role of Quantum Computing

  • Protein Structure Prediction: Quantum algorithms optimize protein modeling, surpassing classical methods in some cases.
  • Molecular Docking: Quantum devices improve docking accuracy by identifying optimal binding poses.
  • Quantum Simulations: Used to solve complex quantum systems like protein-ligand interactions.
  • QSAR Models: Hybrid quantum-classical models predict compound activities with improved efficiency.

3. Challenges and Future Directions

  • Current quantum devices are limited by noise and scalability.
  • Hybrid quantum-classical approaches are critical until quantum technology matures.
  • Future research will focus on robust quantum algorithms and broader applications, such as patent analysis and ligand-based drug design.

Conclusion

Quantum computing is poised to transform drug discovery by solving problems classical computers struggle with, making drug development faster, cheaper, and more efficient.

Know more from reference…

Wang, P. H., Chen J. H., Yang, Y. Y., Lee, C., and Tseng, Y. J. (Mar. 2023). “Recent advances in quantum computing for drug discovery and development.” IEEE Nanotechnology Magazine, DOI: 10.1109/MNANO.2023.3249499