Table 2:

List of workshop topics and learning objectives in Part II.

10.00 Working with Symmetry	• Create crystallographic symmetry files • Load proteins with symmetric components • Convert a monomer into a symmetric assembly. • Learn how to use common Rosetta protocols with symmetry enabled
11.00 Working with Density	• Convert PDB density files into Rosetta-readable files • Load density files into Rosetta • Use RosettaDensity to score a structure and use density to guide modeling
12.00 Working with Antibodies 12.01 Rosetta Antibody Framework and Simple Metrics 12.02 Rosetta Antibody Design	• Load antibody structures into the RosettaAntibody framework • Retrieve antibody specific information such as CDR loop regions, clusters, etc. for use in custom protocols • Set antibody-specific residue selectors and configure task operations for use in modeling and design • Design new antibodies with the RosettaAntibodyDesign protocol
13.00 Carbohydrates 13.01 Glycan Trees, Selectors and Movers 13.02 Glycan Modeling and Design	• Load an oligosaccharide or a glycoprotein. • Use RosettaCarbohydrates to add glycans conjugated to proteins. • Evaluate sugar-sugar linkage energies. • Select carbohydrates and get carbohydrate chemical and connectivity information • Optimize carbohydrate structure through linkage torsions, ring conformers, and sidechain conformers. Design carbohydrate recognition motifs (sequons) for designing glycans into proteins
14.00 RNA Basics	• Load nucleic acids and identify nucleic acid residues in poses. • Identify canonical and non-canonical base pairs in RNA structures. • View and manipulate nucleic acid torsion angles. • Evaluate nucleic acid energies using RNA-specific low- and high-resolution score functions. Isolate RNA-specific score terms (e.g. stacking energies, base pairing potential). • Decompose RNA structures into 3D RNA motifs. • Use idealized torsion angles for RNA residues to generate an idealized A-form helix. • Replace RNA residues with a new sequence for homology modeling. • Use RNA fragments when building an RNA backbone and use minimization to refine resulting structures. Build a Monte Carlo search strategy using these approaches. • Use the FARFAR protocol for sampling RNA structures, which combines fragment assembly and high-resolution minimization moves.
15.00 Modeling Membrane Proteins 15.01 Accounting for the Lipid Bilayer 15.02 Membrane Protein ddG of mutation	• Use membrane tools to orient a protein in the lipid bilayer. • Calculate the lowest energy orientation for a membrane protein. • Identify membrane protein pores and cavities. • Interpret model quality using terms from franklin2019, the membrane energy function. • Compute the ΔΔG of mutation
16.00 Running PyRosetta in Parallel 16.01 PyData, DDGs, and PSSMs 16.02 PyData Miniprotein Design 16.03 GNU parallel 16.04 dask.delayed via SLURM 16.05 Ligand Docking dask	• Parallelize macromolecule modeling tasks using distributed computing, elastic cloud computing, and high-performance computing infrastructures. • Parallelize PyRosetta jobs using GNU parallel and the SLURM job scheduling system. • Visualize and execute PyRosetta job parallelization with the dask module. • Analyze outputs from parallelized PyRosetta jobs in real-time as completed.