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Lecture 03
Paper 01 - Methods

Date: Sep 11, 2024

Today's paper: Champion, C., Gall, R., Ries, B., Rieder, S. R., Barros, E. P., & Riniker, S. (2023). Accelerating Alchemical Free Energy Prediction Using a Multistate Method: Application to Multiple Kinases. Journal of Chemical Information and Modeling, 63(22), 7133-7147. DOI: 10.1021/acs.jcim.3c01469

Learning objectives

What you should be able to do after today's lecture:

  1. Describe the basic stages of drug discovery and explain the role of computational methods in modern drug design.
  2. Identify the main types of molecular forces and explain how they relate to binding affinity and free energy.
  3. Explain basic concepts of statistical thermodynamics, including ensemble averages and the relationship between microscopic properties and macroscopic observables.
  4. Explain the basic principles of molecular simulations, including the concept of force fields and molecular dynamics.
  5. Differentiate between relative and absolute binding free energies and discuss their importance in drug design.
  6. Compare and contrast Free Energy Perturbation (FEP) and Thermodynamic Integration (TI), including their advantages and limitations.
  7. Describe the concept of alchemical transformations and explain how they differ from physical pathways in free energy calculations.
  8. Define the concept of sampling in molecular simulations and explain why enhanced sampling methods are necessary for accurate free energy calculations.
  9. Explain how replica exchange methods enhance sampling in molecular simulations and their application in free energy calculations.
  10. Describe the basic concept of EDS and how it differs from traditional free energy calculation methods.
  11. Explain how RE-EDS combines replica exchange with EDS and discuss its advantages over standard methods.

Presentation