2026 Amber Workshop Activities

Welcome to the 2026 Amber Workshop Activities!

This workshop is taking place in Donostia, Basque Country, Spain from July 13th to July 17th, 2026.

For details and registration, see the workshop web page: 2026 Amber Workshop.

Warning

These activities are currently under development! Please check back closer to the workshop date for the finalized versions.

Day 1: Introduction to force fields, visualization, and Amber

• 1. Hands-On Session 1: Use VMD and CPPTRAJ to visualize and analyze AMBER simulations
  • 1.1. Learning Objectives
  • 1.2. Relevant literature
  • 1.3. Activities
• 2. Hands-On Session 2: Introduction to Molecular Dynamics Simulations with Amber
  • 2.1. Learning Objectives
  • 2.2. Relevant Literature
  • 2.3. Activities

Day 2: Generating non-standard force-field parameters in Amber

• 3. Hands-On Session 3: Build an RNA enzyme (Ribozyme) containing 12-6-4 divalent ions and non-standard residues
  • 3.1. Learning Objectives
  • 3.2. Relevant literature
  • 3.3. Activities
• 4. Hands-On Session 4: Calculating Free Energy Surfaces Using QM/MM-Δ Machine Learning Potentials
  • 4.1. Learning Objectives
  • 4.2. Relevant literature
  • 4.3. Activities
  • 4.4. References
• 5. Hands-On Session 5: Perform SASM calculations to study catalytic mechanisms of a ribozyme
  • 5.1. Learning Objectives
  • 5.2. Relevant literature
  • 5.3. Activities
  • 5.4. Preparing an initial guess containing and intermediate
  • 5.5. Introduction to running SASM simulations
  • 5.6. Analyzing a set of strings
  • 5.7. Visualizing the path progression
  • 5.8. Comparing the DFTB3 result to the ΔMLP grid
  • 5.9. Additional exercise: bootstrap error analysis
  • 5.10. References

Day 3: QM/MM and Delta Machine Learning Potential Models and Free Energy Surfaces

• 6. Hands-On Session 6: Generate Protein forcefield parameters for drug-like molecules utilizing charge fitting procedures and the general AMBER force field
  • 6.1. Learning Objectives
  • 6.2. Activities
  • 6.3. Relevant literature
• 7. Hands-On Session 7: Using QM and Machine Learning Potentials to Parameterize Torsion Terms for Flexible Molecules
  • 7.1. Learning objectives
  • 7.2. Activities

Day 4: Alchemical Free Energy Methods

• 8. Hands-On Session 8: Analyzing Alchemical Free Energy Results Using FE-Toolkit
  • 8.1. Learning Objectives
  • 8.2. Activities
  • 8.3. Relevant Literature
• 9. Hands-On Session 9: Principles of Relative Binding Free Energy Calculations
  • 9.1. Learning Objectives
  • 9.2. Activities
  • 9.3. Relevant literature
• 10. Hands-On Session 10: Principles of Absolute Binding Free Energy Calculations
  • 10.1. Learning objectives
  • 10.2. Activities
  • 10.3. Relevant Literature

Day 5: Machine Learning Models and Platforms for Accurate Free Energy Predictions

• 11. Hands-On Session 11: Transfer learning: active learning to fine-tune a foundational machine learning potential to a specific target system for improved accuracy
  • 11.1. Learning Objectives
  • 11.2. Relevant literature
  • 11.3. Activities
• 12. Hands-On Session 12: Indirect free energy “book-ending”: efficiently correct low-level MM force field results to high-level QDπ
  • 12.1. Learning Objectives
  • 12.2. Activities
  • 12.3. Relevant literature
• 13. Hands-On Session 13: Using AmberStudio to Perform Alchemical Free Energy Simulations
  • 13.1. Learning Objectives
  • 13.2. Activities
  • 13.3. Relevant literature

Reference Materials

• AMBER and Molecular Simulation File Formats
  • Notes on Usage