| import json
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| import os
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| import matplotlib.pyplot as plt
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| import numpy as np
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| THIS_SCRIPT_PATH = os.path.abspath(__file__)
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| DATA_PATH = os.path.join(os.path.dirname(THIS_SCRIPT_PATH), "data")
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| OUTPUT_FOLDER = os.path.join(os.path.dirname(THIS_SCRIPT_PATH), "output", "figureS2")
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| def main():
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| os.makedirs(OUTPUT_FOLDER, exist_ok=True)
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| pdb_to_subunits = {}
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| benchmark_path = os.path.join(DATA_PATH, "benchmark2")
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| for filename in os.listdir(os.path.join(benchmark_path, "pdb_infos")):
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| jobname = filename.split(".")[0]
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| if not filename.endswith(".json"):
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| continue
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| pdb_to_subunits[jobname] = json.load(open(os.path.join(benchmark_path, "pdb_infos", filename), "rb"))
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| print("Benchmark size ", len(pdb_to_subunits), "PDB ids: ", list(pdb_to_subunits.keys()))
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| combfold_results = json.load(open(os.path.join(benchmark_path, "combfold_results.json"), "r"))
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| combfold_results = {k: v for k, v in combfold_results.items() if v is not None and k in pdb_to_subunits}
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| combfold_parsed_results = {}
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| for jobname, results in combfold_results.items():
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| if not results["scores"]:
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| continue
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| tm_and_scores = [(result['weighted_trans_score'], result['tm_score']) for result in results["scores"].values()]
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| combfold_parsed_results[jobname] = [i[1] for i in sorted(tm_and_scores, reverse=True)]
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| print("CombFold able to assemble ", len(combfold_parsed_results))
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| print("CombFold able to assemble correctly (TM-score > 0.7) ", len([i for i in combfold_parsed_results.values()
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| if max(i) > 0.7]))
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| afm3_results_path = os.path.join(benchmark_path, "AFMv3_results.json")
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| afm3_results = {}
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| validation_results = json.load(open(afm3_results_path, "r"))
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| all_jobnames = {i.split("_")[0] for i in validation_results}
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| for jobname in all_jobnames:
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| all_jobs = [i for i in validation_results if i.startswith(jobname)]
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| all_jobs_ranked = [i for i in all_jobs if "rank" in i]
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| if all_jobs_ranked:
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| all_jobs = all_jobs_ranked
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| all_jobs.sort()
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| afm3_results[jobname] = [validation_results[filename]["tm_score"] for filename in all_jobs]
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| print("AFMv3 able to assemble ", len([i for i in afm3_results.values() if i]))
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| rosetta_results_path = os.path.join(benchmark_path, "rosetta_results.json")
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| rosetta_results_json = json.load(open(rosetta_results_path, "r"))
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| rosetta_results = {jobname: [i["tm_score"] for i in results.values()] if results else []
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| for jobname, results in rosetta_results_json.items()}
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| print("Rosetta able to assemble ", len([i for i in rosetta_results.values() if i]))
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| name1, name2, name3 = "CombFold", "AFMv3", "RosettaFold2"
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| th_high, th_accept = 0.8, 0.7
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| bar_width = 0.3
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| fig, ax = plt.subplots()
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| labels = []
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| for count, max_t in enumerate([1, 5, 10]):
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| labels.append(f"Top {max_t}")
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| results1 = [max(v[:max_t], default=0) for v in combfold_parsed_results.values()]
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| results2 = [max(v[:max_t], default=0) for v in afm3_results.values()]
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| results3 = [max(v[:max_t], default=0) for v in rosetta_results.values()]
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| res1_high = len([i for i in results1 if i >= th_high])
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| res1_acceptable = len([i for i in results1 if th_high > i >= th_accept])
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| res2_high = len([i for i in results2 if i >= th_high])
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| res2_acceptable = len([i for i in results2 if th_high > i >= th_accept])
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| res3_high = len([i for i in results3 if i >= th_high])
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| res3_acceptable = len([i for i in results3 if th_high > i >= th_accept])
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| print(name1, max_t, res1_high, res1_acceptable)
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| print(name2, max_t, res2_high, res2_acceptable)
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| print(name3, max_t, res3_high, res3_acceptable)
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| ax.bar(count, [res1_high / len(pdb_to_subunits)], color='#1f78b4', width=bar_width, edgecolor='grey',
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| label=f"{name1}\nHigh")
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| ax.bar(count, [res1_acceptable / len(pdb_to_subunits)], color='#1f78b4', alpha=0.5, width=bar_width,
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| edgecolor='grey', bottom=[res1_high / len(pdb_to_subunits)], label=f"{name1}\nAcceptable")
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| ax.bar(count + bar_width, [res2_high / len(pdb_to_subunits)], color='#ff7f00', width=bar_width, edgecolor='grey',
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| label=f"{name2}\nHigh")
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| ax.bar(count + bar_width, [res2_acceptable / len(pdb_to_subunits)], color='#ff7f00', alpha=0.5, width=bar_width,
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| edgecolor='grey', bottom=[res2_high / len(pdb_to_subunits)], label=f"{name2}\nAcceptable")
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| ax.bar(count + 2 * bar_width, [res3_high / len(pdb_to_subunits)], color='#33a02c', width=bar_width, edgecolor='grey',
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| label=f"{name3}\nHigh")
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| ax.bar(count + 2 * bar_width, [res3_acceptable / len(pdb_to_subunits)], color='#33a02c', alpha=0.5, width=bar_width,
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| edgecolor='grey', bottom=[res3_high / len(pdb_to_subunits)], label=f"{name3}\nAcceptable")
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| plt.ylabel('Success rate', fontsize=11)
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| plt.xticks([i + bar_width / 2 for i in range(len(labels))], labels, fontsize=8)
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| plt.yticks(np.arange(0.1, 0.9, 0.1), fontsize=8)
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| handles, labels = plt.gca().get_legend_handles_labels()
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| new_labels, new_handles = [], []
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| for handle, label in zip(handles, labels):
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| if "High" not in label:
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| continue
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| small_label = label.replace("\nHigh", "")
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| if small_label not in new_labels:
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| new_labels.append(small_label)
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| new_handles.append(handle)
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| ax.legend(new_handles, new_labels, bbox_to_anchor=(1, 0), loc='lower left', fontsize=8, ncol=2)
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| fig.set_size_inches(2, 1.5)
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| fig.set_dpi(300)
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| plt.gca().spines['top'].set_visible(False)
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| plt.gca().spines['right'].set_visible(False)
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| plt.savefig(os.path.join(OUTPUT_FOLDER, "FigS2A.png"), bbox_inches='tight', dpi=300)
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| MAX_T = 1
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| combfold_tm_results, afm2_tm_results = [], []
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| for jobname in pdb_to_subunits:
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| combfold_tm_results.append(max(combfold_parsed_results.get(jobname, [])[:MAX_T], default=0))
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| afm2_tm_results.append(max(afm3_results.get(jobname, [])[:MAX_T], default=0))
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| if afm2_tm_results[-1] > 0.7 > combfold_tm_results[-1]:
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| print(jobname, "better on AFMv3", afm2_tm_results[-1], combfold_tm_results[-1])
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| fig, ax = plt.subplots(figsize=(2.25, 1.75), dpi=600)
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| ax.scatter(combfold_tm_results, afm2_tm_results, alpha=0.4, s=10, edgecolor='none')
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| ax.set_xlabel("CombFold", fontsize=11)
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| ax.set_ylabel("AFMv3", fontsize=11)
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| plt.yticks(np.arange(0, 1.2, 0.2), fontsize=8)
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| plt.xticks(np.arange(0, 1.2, 0.2), fontsize=8)
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| ax.text(0.5, 1.1, "Top-1 TM-score", ha='center', va='center', transform=ax.transAxes, fontsize=11)
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| plt.gca().spines['top'].set_visible(False)
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| plt.gca().spines['right'].set_visible(False)
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| plt.plot([0, 1], [0, 1], 'r--')
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| plt.savefig(os.path.join(OUTPUT_FOLDER, "FigS2B.png"), bbox_inches='tight', dpi=300)
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|
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| if __name__ == "__main__":
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| main() |
