The Future of Drug Development with Quantum Computing.
Bhushan BondePratik PatilBhaskar ChoubeyPublished in: Methods in molecular biology (Clifton, N.J.) (2023)
Novel medication development is a time-consuming and expensive multistage procedure. Recent technology developments have lowered timeframes, complexity, and cost dramatically. Current research projects are driven by AI and machine learning computational models. This chapter will introduce quantum computing (QC) to drug development issues and provide an in-depth discussion of how quantum computing may be used to solve various drug discovery problems. We will first discuss the fundamentals of QC, a review of known Hamiltonians, how to apply Hamiltonians to drug discovery challenges, and what the noisy intermediate-scale quantum (NISQ) era methods and their limitations are.We will further discuss how these NISQ era techniques can aid with specific drug discovery challenges, including protein folding, molecular docking, AI-/ML-based optimization, and novel modalities for small molecules and RNA secondary structures. Consequently, we will discuss the latest QC landscape's opportunities and challenges.
Keyphrases
- drug discovery
- molecular docking
- molecular dynamics
- machine learning
- artificial intelligence
- molecular dynamics simulations
- energy transfer
- monte carlo
- emergency department
- single molecule
- high resolution
- current status
- deep learning
- mass spectrometry
- quality improvement
- single cell
- amino acid
- electronic health record