PyRosetta Workshops

Welcome to PyRosetta!

PyRosetta is an interactive Python-based interface to the powerful Rosetta molecular modeling suite. It enables users to design their own custom molecular modeling algorithms using Rosetta sampling methods and energy functions.

The Jupyter Notebooks below provide an introduction to the fundmamental principles and tools for using PyRosetta. The Notebooks can be viewed directly in nbviewer. To execute any of the notebooks either locally or in Google Colaboratory, please see Chapter 1 for setup instructions.

Many of the workshops have been adapted from the book The PyRosetta Interactive Platform for Protein Structure Prediction and Design: PyRosetta4 Update by Jeffrey Gray, Sidhartha Chaudhury, Sergey Lyskov, and Jason Labonte (Amazon). Other Rosetta developers have also lent their various areas of expertise to help create workshops for this series. Additional contributions to our open-source repository are always welcomed. To learn more about this project, check out our preprint.

Table of Contents

Keyword Index

Chapter 1.0 How to Get Started

• 1.1 How to Get PyRosetta on Your Personal Computer
• 1.2 Jupyter Notebooks, Python, and Google Colaboratory
• 1.3 Frequently Asked Questions/Troubleshooting Tips

Chapter 2.0 Introduction to PyRosetta

• 2.1 Pose Basics
• 2.2 Working with Pose residues
• 2.3 Accessing PyRosetta Documentation
• 2.4 Getting spatial features from a Pose
• 2.5 Protein Geometry
• 2.6 None
• 2.6 Visualization with the PyMOLMover
• 2.7 RosettaScripts in PyRosetta
• 2.8 Visualization and pyrosetta.distributed.viewer

Chapter 3.0 Rosetta Energy Score Functions

• 3.1 Score Function Basics
• 3.2 Practice: Analyzing energy between residues
• 3.3 Energies and the PyMOL Mover

Chapter 4.0 Introduction to Folding

• 4.1 Basic Folding Algorithm
• 4.2 Low-Res Scoring and Fragments

Chapter 5.0 Structure Refinement

• 5.1 High-Resolution Movers
• 5.2 Refinement Protocol

Chapter 6.0 Packing & Design

• 6.1 Side Chain Conformations and Dunbrack Energies
• 6.2 Packing and Relax
• 6.3 Protein Design with a Resfile and FastRelax
• 6.4 Protein Design 2
• 6.5 HBNet Before Design
• 6.6 De Novo Parametric Backbone Design
• 6.7 De Novo Protein Design with PyRosetta
• 6.8 Point Mutation Scan

Chapter 7.0 Docking

• 7.1 Fast Fourier Transform Based Docking via ZDOCK
• 7.2 Docking Moves in Rosetta

Chapter 8.0 Ligand Refinement in PyRosetta (a.k.a. High-Resolution Local Docking) Using the ligand.wts Scorefunction

• 8.1 Global Ligand Docking using XMLObjects Using the ref2015.wts Scorefunction
• 8.2 GALigandDock Protocol with pyrosetta.distributed Using the beta_cart.wts Scorefunction

Chapter 10.0 Working With Symmetry

Chapter 11.0 Working With Density

Chapter 12.0 Working With Antibodies

• 12.1 RosettaAntibody Framework
• 12.2 RosettaAntibodyDesign

Chapter 13.0 RosettaCarbohydrates

• 13.1 RosettaCarbohydrates: Trees, Selectors and Movers
• 13.2 RosettaCarbohydrates: Modeling and Design

Chapter 14.0 RNA in PyRosetta

Chapter 15.0 Modeling Membrane Proteins

• 15.1 Setting up a membrane protein in the bilayer
• 15.2 Predicting the ∆∆G of single point mutations

Chapter 16.0 Running Rosetta in Parallel

• 16.1 Distributed analysis example: exhaustive ddG PSSM
• 16.2 Distributed computation example: miniprotein design
• 16.3 Example of Using PyRosetta with GNU Parallel
• 16.4 Examples Using the dask Module
• 16.5 Part I: Parallelized Global Ligand Docking with pyrosetta.distributed
• 16.6 PyRosettaCluster Tutorial 1A. Simple protocol
• 16.7 PyRosettaCluster Tutorial 1B. Reproduce simple protocol
• 16.8 PyRosettaCluster Tutorial 2. Multiple protocols
• 16.9 PyRosettaCluster Tutorial 3. Multiple decoys
• 16.10 PyRosettaCluster Tutorial 4. Ligand params

Appendix A. Command Reference

Appendix B. Residue Parameter Files

Appendix C. Cleaning pdb files

Appendix D. Links to Online Help