Table 3.

Sample code for the evaluation of a multistep design pipeline

Action	Code Sample
Load	import rstoolbox as rs import matplotlib.pyplot as plt
Read	# With Rosetta installed, scoring can be run for a single structure baseline = rs.io.get_sequence_and_structure(‘1kx8.pdb’, minimize = True) slen = len(baseline.iloc[0 ].get_sequence (‘A’)) # Pre-calculated sets can also be loaded to contextualize the data # 70% homology filter cath = rs.utils.load_refdata(‘cath’, 70) # Length in a window of 10 residues around expected design length cath = cath[(cath[‘length’] > = slen - 5) & (cath[‘length’] < = slen + 5)] # Designs were performed in two rounds gen1 = rs.io.parse_rosetta_file(‘1kx8_gen1.designs’) gen2 = rs.io.parse_rosetta_file(‘1kx8_gen2.designs’) # Identifiers of selected decoys: decoys = [‘d1’, ‘d2’, ‘d3’, ‘d4’, ‘d5’, ‘d6’] # Load experimental data for d2 (best performing decoy) df_cd = rs.io.read_CD(‘1kx8_d2/CD’, model = ‘J-815’) df_spr = rs.io.read_SPR(‘1kx8_d2/SPR.data’)
Plot	fig = plt.figure(figsize = (170 / 25.4, 170 / 25.4)) grid = (3, 4) # Compare scores between the two generations axs = rs.plot.multiple_distributions(gen2, fig, (3, 4), values = [‘score’, ‘hbond_bb_sc’, ‘hbond_sc’, ‘rmsd’], refdata = gen1, violins = False, showfliers = False)
	# See how the selected decoys fit into domains of similar size qr = gen2[gen1[‘description’].isin(decoys)] axs = rs.plot.plot_in_context(qr, fig, (3, 2), cath, (1, 0), [‘score’, ‘cav_vol’]) axs[0].axvline(baseline.iloc[0][‘score’], color = ‘k’, linestyle = ‘--’) axs[1].axvline(baseline.iloc[0][‘cavity’], color = ‘k’, linestyle = ‘--’)
	# Plot experimental validation data ax = plt.subplot2grid(grid, (2, 0), fig = fig, colspan = 2) rs.plot.plot_CD (df_cd, ax, sample = 7) ax = plt.subplot2grid(grid, (2, 2), fig = fig, colspan = 2) rs.plot.plot_SPR (df_spr, ax, fitcolor = ‘black’)
	plt.tight_layout() plt.savefig(‘BMC_Fig4.png’, dpi = 300)

The code shows how to combine the data from multiple Rosetta simulations and assess the different features between two design populations in terms of scoring as well as the comparison between the final designs and the initial structure template. Code comments are presented in italics while functions from the rstoolbox are highlighted in bold. Styling commands are skipped to facilitate reading, but can be found in the repository’s notebook.