Workshop Materials
Welcome to the York Group’s Workshop Tutorials!
These are collections of tutorials that have been used for past workshops, and have been left in the final state from that workshop.
Workshop Tutorials
- 2024 Amber Workshop Tutorials
- VMD and CPPTRAJ Basics for Visualization and Analysis of MD Trajectories
- Simulating the MTR1 ribozyme
- Preparing a Small Molecule from PDB to Simulation
- Parameterizing a non-standard residue for the MTR1 ribozyme
- Building and Simulating TYK2 Protein Ligand System
- Reaction Free Energy Profiles from QM/MM simulations: Methyl Transfer reaction in MTR1
- Absolute Solvation Free Energy using ACES
- Relative Binding Free Energy using ACES
- QM/MM+ΔMLP simulations of the MTR1 ribozyme
- MM-to-QM/MM Free Energy “Bookend” Corrections using GFN2-xTB and QDπ2 machine learning potential.
- 2026 Amber Workshop Tutorials
- Hands-On Session 1: Using VMD to Visualize Amber Simulations
- Hands-On Session 2: Introduction to Molecular Dynamics Simulations with Amber
- Hands-On Session 3: Building Protein-Ligand Complexes Containing Non-standard Residues with Antechamber
- Hands-On Session 4: Building Ribozyme-Substrate Complexes Containing 12-6-4 Divalent Ions and Non-Standard Residues
- Hands-On Session 5: Using QM and Machine Learning Potentials to Parameterize Torsion Terms for Flexible Molecules
- Hands-On Session 6: Calculating Free Eenrgy Surfaces Using QM/MM-Delta MLP Potentials
- Hands-On Session 6: Performing Surface-Accelerated String Calculations to PRedict Catalytic Mechanisms of RNA Enzymes
- Hands-On Session 8: Analyzing Alchemical Free Energy Results Using FE-Toolkit
- Hands-On Session 9: Performing AFE Simulations for Absolute and Relative Solvation Free Energies
- Hands-On Session 10: Performing AFE Simulations for Absolute and Relative Binding Free Energies
- Hands-On Session 11: Training Machine Learning Potentials for Enzyme Design to Ab Initio QM/MM Target Data Using Active Learning
- Hands-On Session 12: Using Machine Learning Potentials to Book-End Drug Discovery Simulations
- Hands-On Session 13: Training AI-FEP Models for High-Throughput Virtual Screening