Morning: Welcome & Foundations
Welcome and introductions with Prof. Matthew O'Meara and the teaching team; bootcamp goals, structure, norms, and cohort formation
Introduction to Protein Design: the modern design pipeline and why the order of steps matters
Protein Science Basics: amino acids, secondary and tertiary structure, what makes a protein "designed"
Brief Intro to PyMol: loading structures, navigating chains and residues, visualizing surfaces
Afternoon: Installation & Cluster Day
Install the toolkit on your home cluster: RFdiffusion, ProteinMPNN, ESMFold (AlphaFold and RoseTTAFold run via Colab notebooks)
HPC / cluster orientation: logging in, environments, submitting jobs, command-line basics
Experienced students pair with those still setting up
Evening: Intro to ML — Lecture & Tutorial
Core ML concepts plus the transformer architecture that underpins most current tools
Hands-on tutorial
Study Hall: open study time with instructor support
Morning: Structure Prediction — Concepts & Tools
Complete the Machine Learning Activities [Link here]
How structure prediction became tractable and how AlphaFold changed the field
Tool survey: AlphaFold2/3, Boltz-1/2, Chai-1 — trade-offs and use cases
Interpreting outputs: pLDDT, PAE, and common failure modes
Afternoon: AF2 Tutorial and Sequence Design — ProteinMPNN & Protein Language Models
Sequence-structure compatibility: what makes a sequence fold as intended
ProteinMPNN: how it works, how to run it, what the output score means
Protein Language Models: ESM2/ESM3 as encoders vs. generative models; zero-shot mutation scoring
When to use structure-based vs. language-model approaches
Evening: Sequence Design Tutorials
Study Hall: open study time with instructor support
Morning: Backbone Generation with RFdiffusion
Diffusion models conceptually; RFdiffusion key parameters and setting up a generation campaign
Run backbone generation, inspect outputs, build intuition by comparing results
[Optional: Rosetta Commons RFD 3 Tutorial RFD3 Tutorial ]
Afternoon: RFDiffusion Tutorial cont., RFD3 Lecture
Evening: Binder Design Optimization with EvoPro, HBDesigner
Study Hall: open study time with instructor support
Morning: BindCraft and Evaluating a Binder, Rosetta Pose, and Rosetta Scoring
The Rosetta Pose object: what it is and how Rosetta uses it (folded in here alongside scoring)
Using Rosetta to evaluate ML-generated designs; score terms that matter (interface energy, shape complementarity, buried unsatisfied H-bonds)
Filtering and ranking a design set: from many candidates to a short experimental list
Afternoon: Project Work
Groups run the full pipeline: structure prediction → backbone generation → sequence design → Rosetta scoring
Several worked examples provided so groups can branch beyond a single template
Instructor and TA support throughout; iterative refinement
Resources: [ Project folder with notebooks ]
Evening: Extended Project Work
Continue running and evaluating pipelines; optional: refold designs with Boltz/Chai and compare to AlphaFold
Resources: [ Project folder ]
Study Hall: open study time with instructor support
Morning: Presentation Preparation
Groups finalize outputs and prepare 10–12 minute presentations: design target & strategy, pipeline decisions, results & scores, limitations, proposed next steps
Peer review: exchange notebooks or slides and give feedback
Afternoon: Group Presentations & Closing
Group presentations with Q&A from instructors and peers
Closing discussion: what did we learn, what surprised us, what would we do differently?
Introduction to the Rosetta Commons: community resources and opportunities
Next steps: recommended readings, tools to explore, and how to build on the week
Resources: [ Papers & resources page ]
Evening: Free — well earned!