pyrosetta jupyternotebooks teach biomolecular structure prediction and design · 2020-05-02 ·...

PyRosetta Jupyter Notebooks Teach Biomolecular Structure Prediction and Design

Students can access the PyRosetta workshops in Google Colaboratory

Kathy H. Le1, Jared Adolf-Bryfogle2, Jason C. Klima3,4, Sergey Lyskov1, Jason Labonte1,5, Steven Bertolani6, Shourya S. Roy Burman1, Andrew Leaver-Fay7, Brian Weitzner3,4, Jack Maguire7, Ramya Rangan8, Matt A. Adrianowycz8, Rebecca F. Alford1, Aleexsan Adal1, Morgan L. Nance1, Yuanhan Wu8, Jordan Willis2, Daniel Kulp8, Rhiju Das9, Roland L. Dunbrack, Jr.10, William Schief2, Brian Kuhlman7, Justin B. Siegel6, Jeffrey J. Gray1*

Student version Notebooks are automatically generated with nbgrader tool

Instructor version

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Student version

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Keyword Index and ToC are automatically generated with nbpages tool

Jupyter Notebook Workshopsnbpages

Keyword Index Table of Contents

Topics in The New Notebooks

Multimedia examples in PyRosetta Notebooks

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Download PyRosetta package and workshops from GitHub Repository.

Follow instructions in Chapter 1 to configure PyRosetta with Google Colaboratory (~12 min).

Access PyRosetta Notebooks in Google Colaboratory:

1

3

Solution: Hands-on learning with PyRosetta

Goal: to add compelling and relevant multimedia to the set of Jupyter Notebook workshops (Clark & Mayer, 2016)

Jupyter Notebooks:

Shareable web application that supports live code, equations, visualization, and text

Google Colaboratory:

Free Jupyter Notebook environment that requires no setup and runs entirely on the cloud

Acknowledgements

1Johns Hopkins University, 2The Scripps Research Institute, 3University of Washington, 4Lyell Immunopharma, 5Franklin & Marshall College, 6University of California, Davis, 7University of North Carolina at Chapel Hill, 8Wistar Institute, 9Stanford University, 10Fox Chase Cancer Center, *Corresponding author: jgray@jhu.edu

SummaryHands-on learning with PyRosetta:1. Google Drive-based• Familiar to most students• No local machine setup necessary

2. Adaptable for class or independent learning3. Interactive exercises and multimedia4. Easily expandable by adding more notebooksMoving GIF from Chapter 5.01:

High-Resolution MoversSchematic from Chapter 12:

Working with Antibodies

Schematic from Chapter 2.08: Visualization

and pyrosetta.distributed.viewer

Goal: to add compelling and relevant multimedia to the set of Jupyter Notebook workshops

Jupyter Notebooks:Shareable web application that supports live code, equations,

visualization, and text

Google Colaboratory:Free Jupyter Notebook

environment that requires no setup and runs entirely on the cloud

Part II: Advanced10. Working with Symmetry

11. Working with Density12. Working with Antibodies

13. Carbohydrates14. RNA Basics

15. Membrane Modeling16. Running PyRosetta in Parallel

Part I: Introduction1. How to Get Started2. Intro to PyRosetta

3. Rosetta Energy Score Function4. Intro to Folding

5. Structure Refinement6. Intro to Packing & Design

7. Protein Docking8. Ligand Docking9. Loop Modeling

Need for Interactive Teaching MaterialFinding ways to train people in molecular modeling is a longstanding problem, but certain challenges remain.

100,000+ downloads of print material12,000+ lecture video views in ~4 years

Beginner Intermediate Advanced

Rosetta REU C++ BootcampPython Bootcamp XML docs

Cyrus GUI

Technical Challenges

• Need for constantly-updated material

• Personal computer incompatibility

• Difficult for students to independently set up software

Pedagogical Challenges

• Need for multimodal engagement (Sankey, et al., 2010)

• Need material for active learning (Berge, 2002)

• Self-paced learning vs. classroom setting

Links:GitHub Repository

Preprint

Links:GitHub Repository

Preprint

We would like to thank the JHU Center for Educational Resources, NIH, NSF, and Rosetta Commons for funding and support. We would also like to thank Jeffrey Kantor for his advice and insight.

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