Week 4: Protein Design Part I

Context
Week 4 focuses on in-silico exploration of proteins and introductory design workflows (no wet lab this week).
Goals for this week
- Pick a protein of interest (from PDB or literature) and explore its structure.
- Practice core visualization & analysis tasks (secondary structure, residue types, surfaces).
- Try a structure prediction or mutational design thought-experiment to see how sequence ↔ structure relates.
- Capture clear screenshots and short notes you can reuse in Week 5.
Part A — Explore a real structure (PDB)
Use one of these web viewers to open your protein (search by PDB ID or UniProt):
- RCSB PDB 3D View (Mol*) — interactive rendering, color by secondary structure/residue type, measure distances.
https://www.rcsb.org/3d-view/ - iCn3D (NCBI) — web viewer with synced sequence/structure and quick analysis panels (hydrophobicity, H-bonds, pockets).
https://github.com/ncbi/icn3d
Try these views/tasks
- Representations: cartoon / ribbon / ball-and-stick.
- Coloring: by secondary structure (helices vs sheets) and by residue type (hydrophobic/hydrophilic).
- Sites: identify ligands or pockets; note any catalytic residues or binding motifs.
- Screenshots: save at least 3 views (overall fold, active/binding site, colored by residue properties).
Tip
Pro tip: Mol* and iCn3D can export high-res images and shareable states. Keep a consistent background and label key residues for clarity.
Part B — Predict or compare a structure (quick)
If your protein lacks an experimental structure or you want to test variants:
- ColabFold (AlphaFold2 in Colab) — paste a sequence, run a single/complex prediction, and download PDBs.
https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb - Background & docs: https://github.com/sokrypton/ColabFold
Deliverable ideas
- Compare the predicted model to a known template (if any): RMSD impression, domain arrangement, confidence (pLDDT/PAE).
- If you mutate 1–3 residues (e.g., core → larger hydrophobe; surface → polar), what changes do you observe in predicted packing?
Warning
Predictions can be confident but wrong—treat them as hypotheses to guide thinking, not as proof.
Optional — Local tools
- PyMOL (desktop) for publication-quality images and measurements: https://pymol.org/
- PyRosetta notebooks for folding/design basics in Jupyter/Colab:
https://rosettacommons.github.io/PyRosetta.notebooks/
Use these if you want more control than web viewers provide.
What to deliver (minimum)
- Protein choice (name, organism, PDB or UniProt reference).
- 3 screenshots showing:
- cartoon/ribbon overview;
- colored by secondary structure (helices vs sheets);
- colored by residue type (hydrophobic vs hydrophilic) and/or surface/pocket.
- Short notes (5–10 bullets): what you learned about fold, interface, and residue distribution.
- (Optional) Prediction/variant: brief comparison and what you’d test next.
Handy references
- RCSB PDB 3D View (Mol*): https://www.rcsb.org/3d-view/
- Mol* project page: https://molstar.org/
- iCn3D overview & tutorial: https://www.ncbi.nlm.nih.gov/Structure/icn3d/guide/iCn3D_Tutorial_by_Jakubowski_072121.pdf
- iCn3D paper (features & analysis): https://academic.oup.com/bioinformatics/article/36/1/131/5520951
- ColabFold notebook (AlphaFold2): https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb
- ColabFold docs & Q&A: https://github.com/sokrypton/ColabFold
- PyMOL homepage: https://pymol.org/
- PyRosetta notebooks hub: https://rosettacommons.github.io/PyRosetta.notebooks/