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Reset repository and upload final project (part 27)

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  1. .gitattributes +2 -0
  2. configs/._known_good_pdb_complexes.yaml +0 -0
  3. configs/._large_benchmark.yaml +0 -0
  4. configs/._multifidelity_defaults.yaml +0 -0
  5. configs/._multifidelity_regularized.yaml +0 -0
  6. configs/._overnight_stop_model.yaml +0 -0
  7. configs/._policy_repair_benchmark.yaml +0 -0
  8. configs/._ppi_benchmark.yaml +0 -0
  9. configs/._ppi_sanity_check.yaml +0 -0
  10. configs/._reference_free_triage_bandit_defaults.yaml +0 -0
  11. configs/._smoke_test.yaml +0 -0
  12. configs/_tmp_smoke_check.yaml +27 -0
  13. configs/benchmarks/._three_pdb_targets.yaml +0 -0
  14. configs/benchmarks/three_pdb_targets.yaml +31 -0
  15. configs/budget_efficiency_benchmark.yaml +140 -0
  16. configs/default.yaml +38 -0
  17. configs/demo_mdm2.yaml +35 -0
  18. configs/discovery_benchmark.yaml +100 -0
  19. configs/discovery_benchmark_reduced.yaml +100 -0
  20. configs/epsilon_regret_benchmark.yaml +64 -0
  21. configs/experimental_benchmark.yaml +72 -0
  22. configs/experimental_benchmark_single_library.yaml +73 -0
  23. configs/experimental_validation.yaml +36 -0
  24. configs/large_benchmark.yaml +87 -0
  25. configs/multifidelity_regularized.yaml +119 -0
  26. configs/overnight_stop_model.yaml +175 -0
  27. configs/policy_repair_benchmark.yaml +98 -0
  28. configs/ppi_benchmark.yaml +25 -0
  29. configs/ppi_sanity_check.yaml +24 -0
  30. configs/reference_free_triage_bandit_defaults.yaml +42 -0
  31. configs/smoke_test.yaml +39 -0
  32. conftest.py +42 -0
  33. data/._.DS_Store +0 -0
  34. data/._.cache +0 -0
  35. data/datasets/._.DS_Store +0 -0
  36. data/datasets/._rdock_3PTB_50k_pubchem_local +0 -0
  37. data/datasets/rdock_3PTB_50k_pubchem_local/._.DS_Store +0 -0
  38. data/datasets/rdock_3PTB_50k_pubchem_local/._dataset_manifest.json +0 -0
  39. data/datasets/rdock_3PTB_50k_pubchem_local/._ligands +0 -0
  40. data/datasets/rdock_3PTB_50k_pubchem_local/._logs +0 -0
  41. data/datasets/rdock_3PTB_50k_pubchem_local/._qc +0 -0
  42. data/datasets/rdock_3PTB_50k_pubchem_local/._target +0 -0
  43. data/datasets/rdock_3PTB_50k_pubchem_local/dataset_manifest.json +907 -0
  44. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/._all_ligands.sdf +0 -0
  45. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/._all_ligands.smi +0 -0
  46. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/._invalid_ligands.csv +0 -0
  47. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/._ligand_metadata.csv +0 -0
  48. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/._ligand_preparation_progress.json +0 -0
  49. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/._obabel_batches +0 -0
  50. data/datasets/rdock_3PTB_50k_pubchem_local/ligands/all_ligands.sdf +3 -0
.gitattributes CHANGED
@@ -204,3 +204,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
204
  .venv_haddock/lib/python3.12/site-packages/scipy/stats/_stats_pythran.cpython-312-darwin.so filter=lfs diff=lfs merge=lfs -text
205
  .venv_haddock/lib/python3.12/site-packages/scipy/stats/_unuran/unuran_wrapper.cpython-312-darwin.so filter=lfs diff=lfs merge=lfs -text
206
  .venv_haddock/lib/python3.12/site-packages/yaml/_yaml.cpython-312-darwin.so filter=lfs diff=lfs merge=lfs -text
 
 
 
204
  .venv_haddock/lib/python3.12/site-packages/scipy/stats/_stats_pythran.cpython-312-darwin.so filter=lfs diff=lfs merge=lfs -text
205
  .venv_haddock/lib/python3.12/site-packages/scipy/stats/_unuran/unuran_wrapper.cpython-312-darwin.so filter=lfs diff=lfs merge=lfs -text
206
  .venv_haddock/lib/python3.12/site-packages/yaml/_yaml.cpython-312-darwin.so filter=lfs diff=lfs merge=lfs -text
207
+ data/datasets/rdock_3PTB_50k_pubchem_local/ligands/all_ligands.sdf filter=lfs diff=lfs merge=lfs -text
208
+ data/datasets/rdock_3PTB_50k_pubchem_local/ligands/ligand_metadata.csv filter=lfs diff=lfs merge=lfs -text
configs/._known_good_pdb_complexes.yaml ADDED
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configs/._large_benchmark.yaml ADDED
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configs/._multifidelity_defaults.yaml ADDED
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configs/._multifidelity_regularized.yaml ADDED
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configs/._overnight_stop_model.yaml ADDED
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configs/._policy_repair_benchmark.yaml ADDED
Binary file (4.1 kB). View file
 
configs/._ppi_benchmark.yaml ADDED
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configs/._ppi_sanity_check.yaml ADDED
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configs/._reference_free_triage_bandit_defaults.yaml ADDED
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configs/._smoke_test.yaml ADDED
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configs/_tmp_smoke_check.yaml ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ backend:
2
+ allow_mock_if_missing: true
3
+ n_runs: 3
4
+ type: rdock
5
+ clustering:
6
+ butina_cutoff: 0.4
7
+ n_hyperclusters: 2
8
+ data:
9
+ benchmark_metadata: data/benchmarks/smoke_metadata.json
10
+ ligand_table: data/ligands/smoke_ligands.csv
11
+ target_id: smoke_mdm2
12
+ target_path: data/targets/smoke_target.pdb
13
+ encoding:
14
+ fingerprint_bits: 512
15
+ fingerprint_radius: 2
16
+ generate_3d: false
17
+ run:
18
+ max_batches: 2
19
+ name: smoke_test
20
+ output_dir: results/smoke_check
21
+ random_seed: 7
22
+ scheduler:
23
+ batch_size: 4
24
+ conservative_deprioritize: false
25
+ init_coverage_fraction: 0.5
26
+ scoring:
27
+ interface_weight: 1.0
configs/benchmarks/._three_pdb_targets.yaml ADDED
Binary file (4.1 kB). View file
 
configs/benchmarks/three_pdb_targets.yaml ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "targets": [
3
+ {
4
+ "target_id": "mdm2_4hg7",
5
+ "pdb_id": "4HG7",
6
+ "pdb_path": "data/targets/prelim_set_mdm2_4hg7/mdm2_4hg7.pdb",
7
+ "receptor_chain": "A",
8
+ "reference_ligand_resname": "NUT",
9
+ "reference_ligand_chain": "A",
10
+ "ligands_csv": "data/ligands/prelim_set_mdm2_4hg7/shared_library_dedup.csv"
11
+ },
12
+ {
13
+ "target_id": "egfr_4wkq",
14
+ "pdb_id": "4WKQ",
15
+ "pdb_path": "data/targets/prelim_set_egfr_4wkq/egfr_4wkq.pdb",
16
+ "receptor_chain": "A",
17
+ "reference_ligand_resname": "IRE",
18
+ "reference_ligand_chain": "A",
19
+ "ligands_csv": "data/ligands/prelim_set_egfr_4wkq/shared_library_dedup.csv"
20
+ },
21
+ {
22
+ "target_id": "abl1_1iep",
23
+ "pdb_id": "1IEP",
24
+ "pdb_path": "data/targets/prelim_set_abl1_1iep/abl1_1iep.pdb",
25
+ "receptor_chain": "A",
26
+ "reference_ligand_resname": "STI",
27
+ "reference_ligand_chain": "A",
28
+ "ligands_csv": "data/ligands/prelim_set_abl1_1iep/shared_library_dedup.csv"
29
+ }
30
+ ]
31
+ }
configs/budget_efficiency_benchmark.yaml ADDED
@@ -0,0 +1,140 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: budget_efficiency_benchmark
3
+ output_dir: results/budget_efficiency_benchmark
4
+ random_seed: 20260416
5
+ batch_size: 64
6
+ allow_resume: true
7
+ max_batches: 500
8
+ budgets: [100, 500, 2500, 5000, 10000]
9
+ time_importance_values: [0.0, 0.5, 1.0]
10
+
11
+ backend:
12
+ type: rdock
13
+ require_real_backend: true
14
+ n_runs: 1
15
+ mapper_radius: 6.0
16
+ command_timeout_seconds: 240
17
+ parallel_jobs: auto-minus-4
18
+ allow_skip_failed_ligands: true
19
+ max_failed_ligands: 200
20
+
21
+ encoding:
22
+ fingerprint_radius: 2
23
+ fingerprint_bits: 1024
24
+ generate_3d: false
25
+
26
+ feature_extraction:
27
+ compute_partial_charges: false
28
+ compute_sasa: false
29
+
30
+ clustering:
31
+ butina_cutoff: 0.35
32
+ n_hyperclusters: 40
33
+
34
+ scheduler:
35
+ init_coverage_fraction: 0.35
36
+ conservative_deprioritize: true
37
+ surrogate:
38
+ prefer_xgboost: true
39
+ n_estimators: 180
40
+ min_train_samples: 20
41
+ max_depth_small: 3
42
+ max_depth_large: 6
43
+ model_weight_schedule:
44
+ sample_knots: [20, 50, 100, 200, 500]
45
+ weight_knots: [0.1, 0.3, 0.5, 0.7, 0.9]
46
+ max_weight: 0.9
47
+ min_weight: 0.05
48
+ instability_threshold: 2.0
49
+ instability_decay: 0.25
50
+
51
+ early_stop:
52
+ min_evaluated: 600
53
+ patience_rounds: 8
54
+ min_model_weight: 0.35
55
+ quantile: 0.15
56
+ uncertainty_weight: 0.2
57
+ min_improvement: 0.02
58
+ exploration_margin: 0.45
59
+ exploitation_margin: 0.1
60
+ reference_evaluations: 10000
61
+
62
+ policies:
63
+ adaptive_hard_stop: { enabled: true }
64
+ adaptive_soft_stop:
65
+ enabled: true
66
+ soft_recovery_batches: 16
67
+ soft_threshold_relax: 0.35
68
+ soft_model_weight_cap: 0.45
69
+ soft_exploration_boost: 0.25
70
+ max_soft_recoveries: 1
71
+ adaptive_no_stop: { enabled: true }
72
+ adaptive_cluster_bootstrap:
73
+ enabled: true
74
+ cluster_bootstrap_rounds: 24
75
+ adaptive_soft_stop_cluster_floor:
76
+ enabled: true
77
+ cluster_bootstrap_rounds: 20
78
+ min_cluster_coverage: 0.60
79
+ min_hypercluster_coverage: 0.55
80
+ soft_recovery_batches: 20
81
+ soft_threshold_relax: 0.40
82
+ soft_model_weight_cap: 0.40
83
+ soft_exploration_boost: 0.30
84
+ pre_floor_model_weight_cap: 0.35
85
+ max_soft_recoveries: 2
86
+
87
+ matrix:
88
+ naive_random_seeds: [11, 22, 33]
89
+ cluster_naive_seeds: [101, 202, 303]
90
+
91
+ disk_guard:
92
+ min_free_gb: 10.0
93
+ projected_output_gb: 3.0
94
+ keep_raw_batches: 6
95
+
96
+ dataset_A:
97
+ name: dataset_A
98
+ protein_name: EGFR
99
+ target_id: egfr_budget
100
+ docking_reference_pdb: "4WKQ"
101
+ docking_target_path: data/targets/budget_efficiency_benchmark_A/egfr_4wkq.pdb
102
+ reference_id: ref_gefitinib
103
+ pdb_id: "4WKQ"
104
+ ligand_comp_id: "IRE"
105
+ reference_name: Gefitinib
106
+ reference_smiles: "COC1=C(C=C2C(=C1)N=CN=C2NC3=CC(=C(C=C3)F)Cl)OCCCN4CCOCC4"
107
+ benchmark_dataset:
108
+ output_dir: data/ligands/budget_efficiency_benchmark_A
109
+ target_size: 10000
110
+ shuffle_seed: 334455
111
+ reuse_existing: true
112
+ min_similarity_keep: 0.00
113
+ pubchem_max_records: 12000
114
+ pubchem_thresholds: [80]
115
+ chembl_target_id: CHEMBL203
116
+ chembl_max_rows: 0
117
+ allow_generated_fallback: true
118
+
119
+ dataset_B:
120
+ name: dataset_B
121
+ protein_name: ABL1
122
+ target_id: abl1_budget
123
+ docking_reference_pdb: "1IEP"
124
+ docking_target_path: data/targets/budget_efficiency_benchmark_B/abl1_1iep.pdb
125
+ reference_id: ref_imatinib
126
+ pdb_id: "1IEP"
127
+ ligand_comp_id: "STI"
128
+ reference_name: Imatinib
129
+ reference_smiles: "CC1=C(C=C(C=C1)NC(=O)C2=CC=C(C=C2)CN3CCN(CC3)C)NC4=NC=CC(=N4)C5=CN=CC=C5"
130
+ benchmark_dataset:
131
+ output_dir: data/ligands/budget_efficiency_benchmark_B
132
+ target_size: 10000
133
+ shuffle_seed: 556677
134
+ reuse_existing: true
135
+ min_similarity_keep: 0.00
136
+ pubchem_max_records: 12000
137
+ pubchem_thresholds: [80]
138
+ chembl_target_id: CHEMBL1862
139
+ chembl_max_rows: 0
140
+ allow_generated_fallback: true
configs/default.yaml ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ run:
2
+ name: default
3
+ output_dir: results/demo_run
4
+ max_batches: 5
5
+ random_seed: 42
6
+
7
+ data:
8
+ target_id: mdm2
9
+ target_path: data/targets/mdm2_1ycr_excerpt.pdb
10
+ ligand_table: data/ligands/mdm2_ligands_demo.csv
11
+ benchmark_metadata: data/benchmarks/mdm2_demo_metadata.json
12
+
13
+ backend:
14
+ type: rdock
15
+ allow_mock_if_missing: false
16
+ require_real_backend: true
17
+ n_runs: 5
18
+ mapper_radius: 6.0
19
+ pocket_mode: reference_complex_pocket
20
+ pocket_reference_ligand_id: ""
21
+ pocket_relaxation_margin: 0.0
22
+
23
+ encoding:
24
+ fingerprint_radius: 2
25
+ fingerprint_bits: 1024
26
+ generate_3d: true
27
+
28
+ clustering:
29
+ butina_cutoff: 0.35
30
+ n_hyperclusters: 4
31
+
32
+ scheduler:
33
+ batch_size: 8
34
+ init_coverage_fraction: 0.25
35
+ conservative_deprioritize: true
36
+
37
+ scoring:
38
+ interface_weight: 1.0
configs/demo_mdm2.yaml ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: demo_mdm2
3
+ output_dir: results/demo_run
4
+ max_batches: 6
5
+ random_seed: 42
6
+
7
+ data:
8
+ target_id: mdm2
9
+ target_path: data/targets/mdm2_1ycr_excerpt.pdb
10
+ ligand_table: data/ligands/mdm2_ligands_demo.csv
11
+ benchmark_metadata: data/benchmarks/mdm2_demo_metadata.json
12
+
13
+ backend:
14
+ type: rdock
15
+ allow_mock_if_missing: false
16
+ require_real_backend: true
17
+ n_runs: 5
18
+ mapper_radius: 6.0
19
+
20
+ encoding:
21
+ fingerprint_radius: 2
22
+ fingerprint_bits: 1024
23
+ generate_3d: true
24
+
25
+ clustering:
26
+ butina_cutoff: 0.35
27
+ n_hyperclusters: 4
28
+
29
+ scheduler:
30
+ batch_size: 8
31
+ init_coverage_fraction: 0.25
32
+ conservative_deprioritize: true
33
+
34
+ scoring:
35
+ interface_weight: 1.0
configs/discovery_benchmark.yaml ADDED
@@ -0,0 +1,100 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: discovery_benchmark
3
+ output_dir: results/discovery_benchmark
4
+ random_seed: 20260415
5
+ batch_size: 32
6
+ adaptive_budget: 50000
7
+ baseline_budget: 50000
8
+ max_batches: 2000
9
+ allow_resume: true
10
+ enable_adaptive_early_stop: true
11
+
12
+ target:
13
+ protein_name: MDM2
14
+ target_id: mdm2_discovery
15
+ docking_reference_pdb: "4HG7"
16
+ docking_target_path: data/targets/discovery_benchmark/mdm2_4hg7.pdb
17
+
18
+ reference:
19
+ reference_id: ref_nutlin3a
20
+ pdb_id: "4HG7"
21
+ ligand_comp_id: "NUT"
22
+
23
+ benchmark_dataset:
24
+ output_dir: data/ligands/discovery_benchmark
25
+ target_size: 50000
26
+ shuffle_seed: 424242
27
+ reuse_existing: true
28
+ min_similarity_keep: 0.08
29
+ pubchem_max_records: 120000
30
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35, 32, 30]
31
+ chembl_target_id: CHEMBL5023
32
+ chembl_max_rows: 120000
33
+ allow_generated_fallback: true
34
+
35
+ backend:
36
+ type: rdock
37
+ require_real_backend: true
38
+ n_runs: 5
39
+ mapper_radius: 6.0
40
+ command_timeout_seconds: 300
41
+ parallel_jobs: auto-minus-4
42
+
43
+ encoding:
44
+ fingerprint_radius: 2
45
+ fingerprint_bits: 1024
46
+ generate_3d: false
47
+
48
+ feature_extraction:
49
+ compute_partial_charges: false
50
+ compute_sasa: false
51
+
52
+ clustering:
53
+ butina_cutoff: 0.35
54
+ n_hyperclusters: 50
55
+
56
+ scheduler:
57
+ init_coverage_fraction: 0.35
58
+ conservative_deprioritize: true
59
+ surrogate:
60
+ prefer_xgboost: true
61
+ n_estimators: 250
62
+ min_train_samples: 20
63
+ max_depth_small: 3
64
+ max_depth_large: 6
65
+ model_weight_schedule:
66
+ sample_knots: [20, 50, 100, 200, 500]
67
+ weight_knots: [0.1, 0.3, 0.5, 0.7, 0.9]
68
+ max_weight: 0.9
69
+ min_weight: 0.05
70
+ instability_threshold: 2.0
71
+ instability_decay: 0.25
72
+
73
+ matrix:
74
+ naive_random_seeds: [11, 22, 33, 44, 55]
75
+ cluster_naive_seeds: [101, 202, 303, 404, 505]
76
+ include_adaptive_top1_variant: true
77
+ include_adaptive: true
78
+ include_naive_random: true
79
+ include_cluster_naive: true
80
+ modes: [docking_only, full_feature]
81
+
82
+ analysis:
83
+ analog_similarity_threshold: 0.65
84
+ rolling_window: 200
85
+ replicate_subset_size_top: 20
86
+ replicate_subset_size_borderline: 20
87
+ replicate_subset_size_clusters: 20
88
+ replicate_runs: 2
89
+
90
+ early_stop:
91
+ min_evaluated: 3000
92
+ patience_rounds: 12
93
+ min_model_weight: 0.4
94
+ quantile: 0.15
95
+ uncertainty_weight: 0.2
96
+ min_improvement: 0.015
97
+ exploration_margin: 0.45
98
+ exploitation_margin: 0.1
99
+ reference_evaluations: 50000
100
+
configs/discovery_benchmark_reduced.yaml ADDED
@@ -0,0 +1,100 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: discovery_benchmark_reduced
3
+ output_dir: results/discovery_benchmark
4
+ random_seed: 20260415
5
+ batch_size: 32
6
+ adaptive_budget: 7500
7
+ baseline_budget: 7500
8
+ max_batches: 500
9
+ allow_resume: true
10
+ enable_adaptive_early_stop: true
11
+
12
+ target:
13
+ protein_name: MDM2
14
+ target_id: mdm2_discovery
15
+ docking_reference_pdb: "4HG7"
16
+ docking_target_path: data/targets/large_benchmark/mdm2_4hg7.pdb
17
+
18
+ reference:
19
+ reference_id: ref_nutlin3a
20
+ pdb_id: "4HG7"
21
+ ligand_comp_id: "NUT"
22
+
23
+ benchmark_dataset:
24
+ output_dir: data/ligands/discovery_benchmark
25
+ target_size: 7500
26
+ shuffle_seed: 424242
27
+ reuse_existing: true
28
+ min_similarity_keep: 0.12
29
+ pubchem_max_records: 20000
30
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
31
+ chembl_target_id: CHEMBL5023
32
+ chembl_max_rows: 40000
33
+ allow_generated_fallback: true
34
+
35
+ backend:
36
+ type: rdock
37
+ require_real_backend: true
38
+ n_runs: 5
39
+ mapper_radius: 6.0
40
+ command_timeout_seconds: 300
41
+ parallel_jobs: auto-minus-4
42
+
43
+ encoding:
44
+ fingerprint_radius: 2
45
+ fingerprint_bits: 1024
46
+ generate_3d: false
47
+
48
+ feature_extraction:
49
+ compute_partial_charges: false
50
+ compute_sasa: false
51
+
52
+ clustering:
53
+ butina_cutoff: 0.35
54
+ n_hyperclusters: 30
55
+
56
+ scheduler:
57
+ init_coverage_fraction: 0.35
58
+ conservative_deprioritize: true
59
+ surrogate:
60
+ prefer_xgboost: true
61
+ n_estimators: 250
62
+ min_train_samples: 20
63
+ max_depth_small: 3
64
+ max_depth_large: 6
65
+ model_weight_schedule:
66
+ sample_knots: [20, 50, 100, 200, 500]
67
+ weight_knots: [0.1, 0.3, 0.5, 0.7, 0.9]
68
+ max_weight: 0.9
69
+ min_weight: 0.05
70
+ instability_threshold: 2.0
71
+ instability_decay: 0.25
72
+
73
+ matrix:
74
+ naive_random_seeds: [11, 22, 33, 44, 55]
75
+ cluster_naive_seeds: [101, 202, 303, 404, 505]
76
+ include_adaptive_top1_variant: true
77
+ include_adaptive: true
78
+ include_naive_random: true
79
+ include_cluster_naive: true
80
+ modes: [docking_only, full_feature]
81
+
82
+ analysis:
83
+ analog_similarity_threshold: 0.65
84
+ rolling_window: 200
85
+ replicate_subset_size_top: 20
86
+ replicate_subset_size_borderline: 20
87
+ replicate_subset_size_clusters: 20
88
+ replicate_runs: 2
89
+
90
+ early_stop:
91
+ min_evaluated: 600
92
+ patience_rounds: 8
93
+ min_model_weight: 0.35
94
+ quantile: 0.15
95
+ uncertainty_weight: 0.2
96
+ min_improvement: 0.02
97
+ exploration_margin: 0.45
98
+ exploitation_margin: 0.1
99
+ reference_evaluations: 7500
100
+
configs/epsilon_regret_benchmark.yaml ADDED
@@ -0,0 +1,64 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: epsilon_regret_benchmark
3
+ output_dir: results/epsilon_regret_benchmark
4
+ random_seed: 20260416
5
+ budgets: [100, 250, 500, 1000]
6
+ time_importance: 0.5
7
+ allow_resume: true
8
+
9
+ epsilon_regret:
10
+ epsilon_quality: 0.10
11
+ acceptable_regret: 0.10
12
+ min_budget: 250
13
+ max_budget: 1000
14
+ min_model_weight: 0.25
15
+ patience_rounds: 6
16
+ min_improvement: 0.02
17
+ uncertainty_multiplier: 0.50
18
+ min_cluster_coverage: 0.20
19
+ min_hypercluster_coverage: 0.20
20
+
21
+ backend:
22
+ primary: rdock
23
+ secondary: haddock
24
+ require_real_backend: true
25
+ rdock:
26
+ n_runs: 1
27
+ mapper_radius: 6.0
28
+ command_timeout_seconds: 240
29
+ parallel_jobs: auto-minus-4
30
+ haddock:
31
+ command_timeout_seconds: 240
32
+ haddock_env_bin_dir: .venv_haddock/bin
33
+ calibration_subset_size: 24
34
+
35
+ runtime:
36
+ estimated_seconds_per_docking: 0.5
37
+
38
+ datasets:
39
+ - name: dataset_A
40
+ target_name: EGFR
41
+ target_path: data/targets/budget_efficiency_benchmark_A/egfr_4wkq.pdb
42
+ shared_library_path: data/ligands/budget_efficiency_benchmark_A/shared_library_shuffled.csv
43
+ predock_master_path: results/budget_efficiency_benchmark/dataset_A/bootstrap/predock/parsed_scores_master.csv
44
+ adaptive_no_stop_run_path: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__adaptive_no_stop__ti0.50__evaluated.csv
45
+ adaptive_model_events_path: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__adaptive_no_stop__ti0.50__model.csv
46
+ naive_glob: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__naive_random_s*__evaluated.csv
47
+ cluster_glob: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__cluster_naive_s*__evaluated.csv
48
+ source_summary_path: results/budget_efficiency_benchmark/dataset_A_target_selection.md
49
+
50
+ - name: dataset_B
51
+ target_name: ABL1
52
+ target_path: data/targets/budget_efficiency_benchmark_B/abl1_1iep.pdb
53
+ shared_library_path: data/ligands/budget_efficiency_benchmark_B/shared_library_shuffled.csv
54
+ predock_master_path: results/budget_efficiency_benchmark/dataset_B/bootstrap/predock/parsed_scores_master.csv
55
+ adaptive_no_stop_run_path: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__adaptive_no_stop__ti0.50__evaluated.csv
56
+ adaptive_model_events_path: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__adaptive_no_stop__ti0.50__model.csv
57
+ naive_glob: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__naive_random_s*__evaluated.csv
58
+ cluster_glob: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__cluster_naive_s*__evaluated.csv
59
+ source_summary_path: results/budget_efficiency_benchmark/dataset_B_target_selection.md
60
+
61
+ disk_guard:
62
+ min_free_gb: 10.0
63
+ projected_output_gb: 1.2
64
+ keep_raw_batches: 4
configs/experimental_benchmark.yaml ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: experimental_benchmark
3
+ output_dir: results/experimental_benchmark
4
+ random_seed: 42
5
+ max_batches: 15
6
+ batch_size: 10
7
+ adaptive_budget: 150
8
+ baseline_budget: 150
9
+ resume: true
10
+
11
+ target:
12
+ protein_name: MDM2
13
+ target_id: mdm2_experimental
14
+ docking_reference_pdb: 4HG7
15
+ docking_target_path: data/targets/experimental_benchmark/mdm2_4hg7.pdb
16
+
17
+ references:
18
+ complexes:
19
+ - pdb_id: 4HG7
20
+ ligand_comp_id: NUT
21
+ reference_id: ref_nutlin3a
22
+ - pdb_id: 4J7D
23
+ ligand_comp_id: I31
24
+ reference_id: ref_ro5045331
25
+ - pdb_id: 4LWU
26
+ ligand_comp_id: 20U
27
+ reference_id: ref_ro5499252
28
+
29
+ benchmark_dataset:
30
+ output_dir: data/ligands/experimental_benchmark
31
+ reuse_existing: true
32
+ per_reference_target: 1500
33
+ pubchem_similarity_threshold: 80
34
+ pubchem_max_records: 2200
35
+ min_similarity_keep: 0.2
36
+
37
+ backend:
38
+ require_real_backend: true
39
+ allow_mock_if_missing: false
40
+ n_runs: 1
41
+ mapper_radius: 6.0
42
+ command_timeout_seconds: 180
43
+
44
+ encoding:
45
+ fingerprint_radius: 2
46
+ fingerprint_bits: 1024
47
+ generate_3d: false
48
+
49
+ clustering:
50
+ butina_cutoff: 0.35
51
+ n_hyperclusters: 20
52
+
53
+ scheduler:
54
+ init_coverage_fraction: 0.35
55
+ conservative_deprioritize: true
56
+ model_weight_schedule:
57
+ sample_knots: [20, 50, 100, 200]
58
+ weight_knots: [0.1, 0.3, 0.5, 0.8]
59
+ max_weight: 0.9
60
+ min_weight: 0.05
61
+ instability_threshold: 2.0
62
+ instability_decay: 0.25
63
+ surrogate:
64
+ prefer_xgboost: true
65
+ n_estimators: 200
66
+ min_train_samples: 12
67
+ max_depth_small: 3
68
+ max_depth_large: 6
69
+
70
+ analysis:
71
+ analog_similarity_threshold: 0.65
72
+ topk_values: [10, 25, 50, 100]
configs/experimental_benchmark_single_library.yaml ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: experimental_benchmark_single_library
3
+ output_dir: results/experimental_benchmark_single_library
4
+ random_seed: 42
5
+ adaptive_budget: 1500
6
+ baseline_budget: 1500
7
+ batch_size: 10
8
+ max_batches: 200
9
+
10
+ target:
11
+ protein_name: MDM2
12
+ target_id: mdm2_experimental_single_library
13
+ docking_reference_pdb: 4HG7
14
+ docking_target_path: data/targets/experimental_benchmark_single_library/mdm2_4hg7.pdb
15
+
16
+ references:
17
+ complexes:
18
+ - pdb_id: 4HG7
19
+ ligand_comp_id: NUT
20
+ reference_id: ref_nutlin3a
21
+ - pdb_id: 4J7D
22
+ ligand_comp_id: I31
23
+ reference_id: ref_ro5045331
24
+ - pdb_id: 4LWU
25
+ ligand_comp_id: 20U
26
+ reference_id: ref_ro5499252
27
+
28
+ benchmark_dataset:
29
+ output_dir: data/ligands/experimental_benchmark_single_library
30
+ reuse_existing: true
31
+ per_reference_target: 1300
32
+ pubchem_similarity_threshold: 80
33
+ pubchem_max_records: 2500
34
+ min_similarity_keep: 0.2
35
+ shared_library_target_size: 1500
36
+ analog_similarity_threshold: 0.65
37
+
38
+ backend:
39
+ require_real_backend: true
40
+ allow_mock_if_missing: false
41
+ n_runs: 1
42
+ mapper_radius: 6.0
43
+ command_timeout_seconds: 180
44
+
45
+ encoding:
46
+ fingerprint_radius: 2
47
+ fingerprint_bits: 1024
48
+ generate_3d: false
49
+
50
+ clustering:
51
+ butina_cutoff: 0.35
52
+ n_hyperclusters: 20
53
+
54
+ scheduler:
55
+ init_coverage_fraction: 0.35
56
+ conservative_deprioritize: true
57
+ model_weight_schedule:
58
+ sample_knots: [20, 50, 100, 200]
59
+ weight_knots: [0.1, 0.3, 0.5, 0.8]
60
+ max_weight: 0.9
61
+ min_weight: 0.05
62
+ instability_threshold: 2.0
63
+ instability_decay: 0.25
64
+ surrogate:
65
+ prefer_xgboost: true
66
+ n_estimators: 200
67
+ min_train_samples: 12
68
+ max_depth_small: 3
69
+ max_depth_large: 6
70
+
71
+ analysis:
72
+ rolling_window: 100
73
+ analog_similarity_threshold: 0.65
configs/experimental_validation.yaml ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: experimental_validation
3
+ output_dir: results/experimental_validation_strict
4
+ max_batches: 2
5
+ random_seed: 42
6
+
7
+ data:
8
+ target_id: mdm2_pocket_excerpt
9
+ target_path: data/targets/mdm2_1ycr_pocket_excerpt.pdb
10
+ ligand_table: data/ligands/mdm2_ligands_validation_strict.csv
11
+ benchmark_metadata: data/benchmarks/mdm2_validation_metadata.json
12
+
13
+ backend:
14
+ type: rdock
15
+ allow_mock_if_missing: false
16
+ require_real_backend: true
17
+ n_runs: 1
18
+ mapper_radius: 6.0
19
+ command_timeout_seconds: 60
20
+
21
+ encoding:
22
+ fingerprint_radius: 2
23
+ fingerprint_bits: 1024
24
+ generate_3d: true
25
+
26
+ clustering:
27
+ butina_cutoff: 0.35
28
+ n_hyperclusters: 4
29
+
30
+ scheduler:
31
+ batch_size: 6
32
+ init_coverage_fraction: 0.34
33
+ conservative_deprioritize: true
34
+
35
+ scoring:
36
+ interface_weight: 1.0
configs/large_benchmark.yaml ADDED
@@ -0,0 +1,87 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: large_benchmark
3
+ output_dir: results/large_benchmark
4
+ random_seed: 20260415
5
+ batch_size: 32
6
+ adaptive_budget: 7500
7
+ baseline_budget: 7500
8
+ max_batches: 500
9
+ allow_resume: true
10
+
11
+ target:
12
+ protein_name: MDM2
13
+ target_id: mdm2_large
14
+ docking_reference_pdb: "4HG7"
15
+ docking_target_path: data/targets/large_benchmark/mdm2_4hg7.pdb
16
+
17
+ reference:
18
+ reference_id: ref_nutlin3a
19
+ pdb_id: "4HG7"
20
+ ligand_comp_id: "NUT"
21
+
22
+ benchmark_dataset:
23
+ output_dir: data/ligands/large_benchmark
24
+ target_size: 7500
25
+ shuffle_seed: 424242
26
+ reuse_existing: true
27
+ min_similarity_keep: 0.12
28
+ pubchem_max_records: 20000
29
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
30
+ chembl_target_id: CHEMBL5023
31
+ chembl_max_rows: 40000
32
+ allow_generated_fallback: true
33
+
34
+ backend:
35
+ type: rdock
36
+ require_real_backend: true
37
+ n_runs: 5
38
+ mapper_radius: 6.0
39
+ command_timeout_seconds: 300
40
+ parallel_jobs: auto-minus-4
41
+ pocket_mode: reference_complex_pocket
42
+ pocket_reference_ligand_id: NUT
43
+ pocket_relaxation_margin: 0.0
44
+
45
+ encoding:
46
+ fingerprint_radius: 2
47
+ fingerprint_bits: 1024
48
+ generate_3d: false
49
+
50
+ feature_extraction:
51
+ compute_partial_charges: false
52
+ compute_sasa: false
53
+
54
+ clustering:
55
+ butina_cutoff: 0.35
56
+ n_hyperclusters: 30
57
+
58
+ scheduler:
59
+ init_coverage_fraction: 0.35
60
+ conservative_deprioritize: true
61
+ surrogate:
62
+ prefer_xgboost: true
63
+ n_estimators: 250
64
+ min_train_samples: 20
65
+ max_depth_small: 3
66
+ max_depth_large: 6
67
+ model_weight_schedule:
68
+ sample_knots: [20, 50, 100, 200, 500]
69
+ weight_knots: [0.1, 0.3, 0.5, 0.7, 0.9]
70
+ max_weight: 0.9
71
+ min_weight: 0.05
72
+ instability_threshold: 2.0
73
+ instability_decay: 0.25
74
+
75
+ matrix:
76
+ naive_random_seeds: [11, 22, 33, 44, 55]
77
+ cluster_naive_seeds: [101, 202, 303, 404, 505]
78
+ include_adaptive_top1_variant: true
79
+ modes: [docking_only, full_feature]
80
+
81
+ analysis:
82
+ analog_similarity_threshold: 0.65
83
+ rolling_window: 200
84
+ replicate_subset_size_top: 20
85
+ replicate_subset_size_borderline: 20
86
+ replicate_subset_size_clusters: 20
87
+ replicate_runs: 2
configs/multifidelity_regularized.yaml ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: multifidelity_regularized
3
+ output_dir: results/multifidelity_regularized
4
+ random_seed: 20260416
5
+ budgets: [50, 100, 150, 200, 250, 300, 400, 500, 750, 1000, 1500, 2000, 2500, 5000, 10000]
6
+ haddock_budgets: [250]
7
+ dynamic_predock_batch_size: 256
8
+ dynamic_predock_max_batches: 4
9
+ dynamic_predock_flush_every_batches: 1
10
+ wall_time_per_dock: 0.5
11
+ max_wall_time_seconds: 7200
12
+ n_baseline_seeds: 3
13
+ allow_resume: true
14
+
15
+ parameters:
16
+ max_budget: 10000
17
+ min_budget: 100
18
+ epsilon_quality_target: 0.10
19
+ time_importance: 0.6
20
+ shortlist_fraction: 0.35
21
+ haddock_shortlist_size: 4
22
+
23
+ stopping:
24
+ target_rank_percentile: 1.0
25
+ peak_patience: 32
26
+ min_improvement_delta: 0.02
27
+
28
+ exploration:
29
+ stagnation_patience: 20
30
+ diversity_boost_strength: 0.5
31
+ dominant_window: 128
32
+
33
+ uncertainty:
34
+ uncertainty_low_threshold: 0.35
35
+ uncertainty_patience: 32
36
+ expected_gain_threshold: 0.03
37
+
38
+ backend:
39
+ require_real_backend: true
40
+ rdock:
41
+ n_runs: 1
42
+ mapper_radius: 6.0
43
+ command_timeout_seconds: 20
44
+ parallel_jobs: auto-minus-4
45
+ allow_skip_failed_ligands: true
46
+ max_failed_ligands: 3000
47
+ haddock:
48
+ enabled: false
49
+ command_timeout_seconds: 90
50
+ haddock_env_bin_dir: .venv_haddock/bin
51
+
52
+ disk_guard:
53
+ min_free_gb: 10.0
54
+ projected_output_gb: 3.0
55
+ keep_raw_batches: 4
56
+
57
+ datasets:
58
+ A:
59
+ name: dataset_A
60
+ target_name: EGFR
61
+ target_path: data/targets/budget_efficiency_benchmark_A/egfr_4wkq.pdb
62
+ shared_library_path: data/ligands/budget_efficiency_benchmark_A/shared_library_shuffled.csv
63
+ predock_master_path: results/budget_efficiency_benchmark/dataset_A/bootstrap/predock/parsed_scores_master.csv
64
+ adaptive_no_stop_run_path: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__adaptive_no_stop__ti0.50__evaluated.csv
65
+ naive_glob: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__naive_random_s*__evaluated.csv
66
+ cluster_glob: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__cluster_naive_s*__evaluated.csv
67
+
68
+ B:
69
+ name: dataset_B
70
+ target_name: ABL1
71
+ target_path: data/targets/budget_efficiency_benchmark_B/abl1_1iep.pdb
72
+ shared_library_path: data/ligands/budget_efficiency_benchmark_B/shared_library_shuffled.csv
73
+ predock_master_path: results/budget_efficiency_benchmark/dataset_B/bootstrap/predock/parsed_scores_master.csv
74
+ adaptive_no_stop_run_path: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__adaptive_no_stop__ti0.50__evaluated.csv
75
+ naive_glob: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__naive_random_s*__evaluated.csv
76
+ cluster_glob: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__cluster_naive_s*__evaluated.csv
77
+
78
+ C:
79
+ name: dataset_C
80
+ target_name: MDM2
81
+ target_id: mdm2_mf_c
82
+ target_pdb: "4HG7"
83
+ target_path: data/targets/multifidelity_benchmark_C/mdm2_4hg7.pdb
84
+ reference_id: ref_nutlin3a_c
85
+ reference_name: Nutlin-3a
86
+ ligand_comp_id: NUT
87
+ reference_smiles: "CC1=C(C(C)=NN1)C2=CC=C(C=C2)C3=NC(C)(C)C4=CC(Cl)=CC(Cl)=C34"
88
+ benchmark_dataset:
89
+ output_dir: data/ligands/multifidelity_benchmark_C
90
+ target_size: 10000
91
+ shuffle_seed: 909001
92
+ reuse_existing: false
93
+ min_similarity_keep: 0.0
94
+ pubchem_max_records: 20000
95
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
96
+ chembl_target_id: CHEMBL5023
97
+ chembl_max_rows: 40000
98
+ allow_generated_fallback: true
99
+
100
+ D:
101
+ name: dataset_D
102
+ target_name: CDK2
103
+ target_id: cdk2_mf_d
104
+ target_pdb: "1H1Q"
105
+ target_path: data/targets/multifidelity_benchmark_D/cdk2_1h1q.pdb
106
+ reference_id: ref_stauro_d
107
+ reference_name: Staurosporine
108
+ ligand_comp_id: STU
109
+ benchmark_dataset:
110
+ output_dir: data/ligands/multifidelity_benchmark_D
111
+ target_size: 10000
112
+ shuffle_seed: 909101
113
+ reuse_existing: true
114
+ min_similarity_keep: 0.0
115
+ pubchem_max_records: 20000
116
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
117
+ chembl_target_id: CHEMBL301
118
+ chembl_max_rows: 40000
119
+ allow_generated_fallback: true
configs/overnight_stop_model.yaml ADDED
@@ -0,0 +1,175 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: overnight_stop_model
3
+ output_dir: results/overnight_stop_model
4
+ random_seed: 20260417
5
+ budgets: [50, 100, 150, 200, 250, 300, 400, 500, 750, 1000, 1500, 2000, 2500, 5000, 10000]
6
+ include_15000_if_safe: true
7
+ dynamic_predock_batch_size: 192
8
+ dynamic_predock_max_batches: 4
9
+ dynamic_predock_flush_every_batches: 1
10
+ wall_time_per_dock: 0.5
11
+ max_wall_time_seconds: 10800
12
+ allow_resume: true
13
+
14
+ resource:
15
+ min_free_gb: 10.0
16
+ min_free_gb_for_15k: 35.0
17
+ min_ram_gb_for_15k: 24.0
18
+ default_target_size: 10000
19
+ projected_output_gb: 3.5
20
+
21
+ parameters:
22
+ max_budget: 10000
23
+ min_budget: 100
24
+ epsilon_quality_target: 0.10
25
+ time_importance: 0.6
26
+ shortlist_fraction: 0.35
27
+ haddock_shortlist_size: 3
28
+
29
+ stopping:
30
+ target_rank_percentile: 1.0
31
+ peak_patience: 32
32
+ min_improvement_delta: 0.02
33
+
34
+ exploration:
35
+ stagnation_patience: 20
36
+ diversity_boost_strength: 0.5
37
+ dominant_window: 128
38
+
39
+ uncertainty:
40
+ uncertainty_low_threshold: 0.35
41
+ uncertainty_patience: 32
42
+ expected_gain_threshold: 0.03
43
+
44
+ stop_models:
45
+ target_percentile: 1.0
46
+ probability_threshold: 0.80
47
+ epsilon_quality: 0.10
48
+ min_budget: 100
49
+ gain_threshold: 0.03
50
+ utility_lambda: 0.001
51
+ utility_threshold: 0.0
52
+ uncertainty_threshold: 0.35
53
+ confirmation_window: 24
54
+ min_improvement_delta: 0.02
55
+
56
+ analysis:
57
+ objective_functions:
58
+ - quality_per_time
59
+ - quality_per_docking
60
+ - rank_percentile_minimization
61
+ - regret_constrained_utility
62
+ - target_percentile_attainment
63
+ - hybrid_objective
64
+ haddock_shortlist_budgets: [250, 1000]
65
+ enable_haddock_shortlist: true
66
+ uncertainty_weight: 0.5
67
+
68
+ backend:
69
+ require_real_backend: true
70
+ rdock:
71
+ n_runs: 1
72
+ mapper_radius: 6.0
73
+ command_timeout_seconds: 20
74
+ parallel_jobs: auto-minus-4
75
+ allow_skip_failed_ligands: true
76
+ max_failed_ligands: 3000
77
+ haddock:
78
+ enabled: true
79
+ command_timeout_seconds: 90
80
+ haddock_env_bin_dir: .venv_haddock/bin
81
+
82
+ disk_guard:
83
+ min_free_gb: 10.0
84
+ projected_output_gb: 3.5
85
+ keep_raw_batches: 4
86
+
87
+ datasets:
88
+ A:
89
+ name: dataset_A
90
+ target_name: EGFR
91
+ target_path: data/targets/budget_efficiency_benchmark_A/egfr_4wkq.pdb
92
+ shared_library_path: data/ligands/budget_efficiency_benchmark_A/shared_library_shuffled.csv
93
+ predock_master_path: results/budget_efficiency_benchmark/dataset_A/bootstrap/predock/parsed_scores_master.csv
94
+ adaptive_no_stop_run_path: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__adaptive_no_stop__ti0.50__evaluated.csv
95
+ naive_glob: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__naive_random_s*__evaluated.csv
96
+ cluster_glob: results/budget_efficiency_benchmark/dataset_A/replay_cache/dataset_A__cluster_naive_s*__evaluated.csv
97
+
98
+ B:
99
+ name: dataset_B
100
+ target_name: ABL1
101
+ target_path: data/targets/budget_efficiency_benchmark_B/abl1_1iep.pdb
102
+ shared_library_path: data/ligands/budget_efficiency_benchmark_B/shared_library_shuffled.csv
103
+ predock_master_path: results/budget_efficiency_benchmark/dataset_B/bootstrap/predock/parsed_scores_master.csv
104
+ adaptive_no_stop_run_path: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__adaptive_no_stop__ti0.50__evaluated.csv
105
+ naive_glob: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__naive_random_s*__evaluated.csv
106
+ cluster_glob: results/budget_efficiency_benchmark/dataset_B/replay_cache/dataset_B__cluster_naive_s*__evaluated.csv
107
+
108
+ C:
109
+ name: dataset_C
110
+ target_name: MDM2
111
+ target_id: mdm2_mf_c
112
+ target_pdb: "4HG7"
113
+ target_path: data/targets/multifidelity_benchmark_C/mdm2_4hg7.pdb
114
+ reference_id: ref_nutlin3a_c
115
+ reference_name: Nutlin-3a
116
+ ligand_comp_id: NUT
117
+ reference_smiles: "CC1=C(C(C)=NN1)C2=CC=C(C=C2)C3=NC(C)(C)C4=CC(Cl)=CC(Cl)=C34"
118
+ reuse_out_dir: results/multifidelity_regularized
119
+ benchmark_dataset:
120
+ output_dir: data/ligands/multifidelity_benchmark_C
121
+ target_size: 10000
122
+ shuffle_seed: 909001
123
+ reuse_existing: true
124
+ min_similarity_keep: 0.0
125
+ pubchem_max_records: 20000
126
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
127
+ chembl_target_id: CHEMBL5023
128
+ chembl_max_rows: 40000
129
+ allow_generated_fallback: true
130
+
131
+ D:
132
+ name: dataset_D
133
+ target_name: CDK2
134
+ target_id: cdk2_mf_d
135
+ target_pdb: "1H1Q"
136
+ target_path: data/targets/multifidelity_benchmark_D/cdk2_1h1q.pdb
137
+ reference_id: ref_stauro_d
138
+ reference_name: Staurosporine
139
+ ligand_comp_id: STU
140
+ reference_smiles: "CN[C@@H]1C[C@H]2O[C@@](C)(N3C=NC4=C3N=CN=C4N)[C@@H]1OC2"
141
+ reuse_out_dir: results/multifidelity_regularized
142
+ benchmark_dataset:
143
+ output_dir: data/ligands/multifidelity_benchmark_D
144
+ target_size: 10000
145
+ shuffle_seed: 909101
146
+ reuse_existing: true
147
+ min_similarity_keep: 0.0
148
+ pubchem_max_records: 20000
149
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
150
+ chembl_target_id: CHEMBL301
151
+ chembl_max_rows: 40000
152
+ allow_generated_fallback: true
153
+
154
+ E:
155
+ name: dataset_E
156
+ target_name: MAPK14
157
+ target_id: mapk14_mf_e
158
+ target_pdb: "1A9U"
159
+ target_path: data/targets/multifidelity_benchmark_E/mapk14_1a9u.pdb
160
+ reference_id: ref_sb203580_e
161
+ reference_name: SB203580
162
+ ligand_comp_id: SB2
163
+ reference_smiles: "CC(C)Oc1ccc(cc1)c2nc(c(cn2)N)c3cnn(c3)C(C)(C)C"
164
+ reuse_out_dir: results/overnight_stop_model
165
+ benchmark_dataset:
166
+ output_dir: data/ligands/multifidelity_benchmark_E
167
+ target_size: 10000
168
+ shuffle_seed: 909201
169
+ reuse_existing: true
170
+ min_similarity_keep: 0.0
171
+ pubchem_max_records: 25000
172
+ pubchem_thresholds: [95, 92, 90, 88, 85, 82, 80, 77, 75, 72, 70, 67, 65, 62, 60, 57, 55, 52, 50, 47, 45, 42, 40, 37, 35]
173
+ chembl_target_id: CHEMBL260
174
+ chembl_max_rows: 50000
175
+ allow_generated_fallback: true
configs/policy_repair_benchmark.yaml ADDED
@@ -0,0 +1,98 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: policy_repair_benchmark
3
+ output_dir: results/policy_repair_benchmark
4
+ random_seed: 20260416
5
+ batch_size: 32
6
+ adaptive_budget: 7500
7
+ baseline_budget: 7500
8
+ max_batches: 500
9
+ allow_resume: true
10
+
11
+ target:
12
+ protein_name: MDM2
13
+ target_id: mdm2_discovery
14
+ docking_reference_pdb: "4HG7"
15
+ docking_target_path: data/targets/large_benchmark/mdm2_4hg7.pdb
16
+
17
+ reference:
18
+ reference_id: ref_nutlin3a
19
+ pdb_id: "4HG7"
20
+ ligand_comp_id: "NUT"
21
+
22
+ inputs:
23
+ source_benchmark_dir: results/discovery_benchmark
24
+ shared_library_path: results/discovery_benchmark/shared_library_shuffled.csv
25
+ predock_master_path: results/discovery_benchmark/predock/parsed_scores_master.csv
26
+ cluster_source_path: results/discovery_benchmark/parsed_scores.csv
27
+ features_values_path: results/discovery_benchmark/features_per_ligand.csv
28
+ features_masks_path: results/discovery_benchmark/feature_masks.csv
29
+ validated_size: 7500
30
+
31
+ backend:
32
+ type: rdock
33
+ require_real_backend: true
34
+ parallel_jobs: auto-minus-4
35
+
36
+ scheduler:
37
+ init_coverage_fraction: 0.35
38
+ conservative_deprioritize: true
39
+ surrogate:
40
+ prefer_xgboost: true
41
+ n_estimators: 180
42
+ min_train_samples: 20
43
+ max_depth_small: 3
44
+ max_depth_large: 6
45
+ model_weight_schedule:
46
+ sample_knots: [20, 50, 100, 200, 500]
47
+ weight_knots: [0.1, 0.3, 0.5, 0.7, 0.9]
48
+ max_weight: 0.9
49
+ min_weight: 0.05
50
+ instability_threshold: 2.0
51
+ instability_decay: 0.25
52
+
53
+ matrix:
54
+ naive_random_seeds: [11, 22, 33, 44, 55]
55
+ cluster_naive_seeds: [101, 202, 303, 404, 505]
56
+
57
+ early_stop:
58
+ min_evaluated: 600
59
+ patience_rounds: 8
60
+ min_model_weight: 0.35
61
+ quantile: 0.15
62
+ uncertainty_weight: 0.2
63
+ min_improvement: 0.02
64
+ exploration_margin: 0.45
65
+ exploitation_margin: 0.1
66
+ reference_evaluations: 7500
67
+
68
+ policies:
69
+ adaptive_hard_stop:
70
+ enabled: true
71
+ adaptive_soft_stop:
72
+ enabled: true
73
+ soft_recovery_batches: 16
74
+ soft_threshold_relax: 0.35
75
+ soft_model_weight_cap: 0.45
76
+ soft_exploration_boost: 0.25
77
+ max_soft_recoveries: 1
78
+ adaptive_no_stop:
79
+ enabled: true
80
+ adaptive_cluster_bootstrap:
81
+ enabled: true
82
+ cluster_bootstrap_rounds: 24
83
+ adaptive_soft_stop_cluster_floor:
84
+ enabled: true
85
+ cluster_bootstrap_rounds: 20
86
+ min_cluster_coverage: 0.60
87
+ min_hypercluster_coverage: 0.55
88
+ soft_recovery_batches: 20
89
+ soft_threshold_relax: 0.40
90
+ soft_model_weight_cap: 0.40
91
+ soft_exploration_boost: 0.30
92
+ pre_floor_model_weight_cap: 0.35
93
+ max_soft_recoveries: 2
94
+
95
+ disk_guard:
96
+ min_free_gb: 10.0
97
+ projected_output_gb: 1.5
98
+ keep_raw_batches: 6
configs/ppi_benchmark.yaml ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: ppi_benchmark
3
+ output_dir: results/ppi_benchmark
4
+ random_seed: 20260415
5
+ batch_size: 8
6
+
7
+ benchmark:
8
+ benchmark_type: peptide_like
9
+
10
+ target:
11
+ protein_name: MDM2
12
+ target_id: mdm2_ppi_benchmark
13
+ docking_target_path: data/targets/ppi_benchmark/mdm2_1ycr.pdb
14
+
15
+ reference:
16
+ reference_pdb_id: "1YCR"
17
+ receptor_chain_id: "A"
18
+ peptide_chain_id: "B"
19
+ n_variants: 50
20
+ min_length: 8
21
+ max_length: 20
22
+
23
+ disk_guard:
24
+ min_free_gb: 8.0
25
+ force_cleanup: true
configs/ppi_sanity_check.yaml ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: ppi_sanity_check
3
+ output_dir: results/ppi_sanity_check
4
+ random_seed: 20260415
5
+ batch_size: 8
6
+
7
+ benchmark:
8
+ benchmark_type: peptide_like
9
+
10
+ target:
11
+ protein_name: MDM2
12
+ target_id: mdm2_ppi_sanity
13
+ docking_target_path: data/targets/ppi_sanity_check/mdm2_1ycr.pdb
14
+
15
+ reference:
16
+ reference_pdb_id: "1YCR"
17
+ receptor_chain_id: "A"
18
+ peptide_chain_id: "B"
19
+ n_variants: 40
20
+ min_length: 8
21
+ max_length: 20
22
+
23
+ disk_guard:
24
+ min_free_gb: 8.0
configs/reference_free_triage_bandit_defaults.yaml ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ strategy: reference_free_triage_bandit_v1
2
+ triage_controller: auto_recall
3
+ triage_model: classifier
4
+ triage_retain_fraction: 0.02
5
+ triage_target_recall: 0.98
6
+ max_retain_fraction_before_not_useful: 0.5
7
+ classifier_threshold_mode: recall_target
8
+ classifier_min_positives: 10
9
+ classifier_holdout_fraction: 0.25
10
+ classifier_fallback: cluster_only
11
+ model_fallback_if_worse: union_with_cluster_only
12
+ survivor_combination_policy: union
13
+ calibration_size: 1000
14
+ calibration_fraction: 0.2
15
+ fidelity_validation_size: 200
16
+ fidelity_levels:
17
+ - 5
18
+ - 10
19
+ - 15
20
+ - 30
21
+ - 50
22
+ promotion_policy: conservative
23
+ rescue_fraction: 0.05
24
+ uncertainty_weight: 0.35
25
+ diversity_weight: 0.75
26
+ outlier_risk_weight: 2.0
27
+ cluster_min_survivors: 1
28
+ cluster_max_survivors: 50
29
+ classifier_top_percentile: 0.05
30
+ max_per_cluster: 50
31
+ final_fidelity_runs: 50
32
+ min_final_ligands: 20
33
+ min_promotion_per_level: 8
34
+ final_survivor_enumerate_variants: false
35
+ variant_stage: none
36
+ enumerate_stereoisomers: none
37
+ max_stereoisomers_per_parent: 2
38
+ enumerate_tautomers: none
39
+ enumerate_protonation: none
40
+ max_conformers_per_variant: 1
41
+ max_total_variants_per_parent: 1
42
+ variant_fairness_policy: cap
configs/smoke_test.yaml ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ run:
2
+ name: smoke_test
3
+ output_dir: results/smoke_test
4
+ max_batches: 2
5
+ random_seed: 7
6
+
7
+ data:
8
+ target_id: smoke_3ptb
9
+ target_path: data/datasets/rdock_3PTB_10k_pubchem/target/rdock_prm/target_raw.pdb
10
+ ligand_table: data/ligands/smoke_ligands.csv
11
+ benchmark_metadata: data/benchmarks/smoke_metadata.json
12
+
13
+ backend:
14
+ type: rdock
15
+ allow_mock_if_missing: false
16
+ require_real_backend: true
17
+ n_runs: 3
18
+ mapper_radius: 6.0
19
+ pocket_mode: user_fixed_pocket
20
+ pocket_center: [-1.7591111111111113, 14.461, 16.915777777777777]
21
+ pocket_radius: 6.0
22
+ pocket_relaxation_margin: 0.0
23
+
24
+ encoding:
25
+ fingerprint_radius: 2
26
+ fingerprint_bits: 512
27
+ generate_3d: false
28
+
29
+ clustering:
30
+ butina_cutoff: 0.4
31
+ n_hyperclusters: 2
32
+
33
+ scheduler:
34
+ batch_size: 4
35
+ init_coverage_fraction: 0.5
36
+ conservative_deprioritize: false
37
+
38
+ scoring:
39
+ interface_weight: 1.0
conftest.py ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from __future__ import annotations
2
+
3
+ import os
4
+ from pathlib import Path
5
+
6
+
7
+ NEW_TEST_FILES = {
8
+ "test_docking_pipeline_adaptive.py",
9
+ "test_docking_pipeline_failures.py",
10
+ "test_docking_pipeline_cli_validation.py",
11
+ "test_docking_pipeline_dud_metrics.py",
12
+ "test_docking_pipeline_metrics.py",
13
+ "test_docking_pipeline_sdf.py",
14
+ "test_docking_pipeline_dataset.py",
15
+ "test_docking_pipeline_bundle.py",
16
+ "test_rdock_validation_smoke.py",
17
+ "test_pdb_benchmark_real.py",
18
+ "test_legacy_collection_policy.py",
19
+ "test_rdock_backend.py",
20
+ "test_rdock_feature_parsing.py",
21
+ "test_rdock_output_parsing_real.py",
22
+ "test_rdock_real_execution.py",
23
+ "test_smoke_pipeline.py",
24
+ }
25
+
26
+
27
+ def pytest_ignore_collect(collection_path, config): # type: ignore[no-untyped-def]
28
+ """Keep default collection operational without optional legacy dependencies.
29
+
30
+ The historical benchmark suite imports pandas/RDKit/matplotlib/yaml/HADDOCK/smina
31
+ modules at collection time. Those tests remain in the tree for reference and can be
32
+ re-enabled in a fully provisioned legacy environment with DOCKING_INCLUDE_LEGACY=1.
33
+ The strict rDock-first tests are collected by default.
34
+ """
35
+ path = Path(str(collection_path))
36
+ if os.environ.get("DOCKING_INCLUDE_LEGACY") == "1":
37
+ return False
38
+ if path.name.startswith("test_") and path.suffix == ".py" and path.parent.name == "tests":
39
+ return path.name not in NEW_TEST_FILES
40
+ if path.name == "run_smoke_test.py" and path.parent.name == "pipeline":
41
+ return True
42
+ return False
data/._.DS_Store ADDED
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data/._.cache ADDED
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data/datasets/._.DS_Store ADDED
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data/datasets/._rdock_3PTB_50k_pubchem_local ADDED
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data/datasets/rdock_3PTB_50k_pubchem_local/._.DS_Store ADDED
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data/datasets/rdock_3PTB_50k_pubchem_local/._dataset_manifest.json ADDED
Binary file (4.1 kB). View file
 
data/datasets/rdock_3PTB_50k_pubchem_local/._ligands ADDED
Binary file (4.1 kB). View file
 
data/datasets/rdock_3PTB_50k_pubchem_local/._logs ADDED
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data/datasets/rdock_3PTB_50k_pubchem_local/._qc ADDED
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data/datasets/rdock_3PTB_50k_pubchem_local/._target ADDED
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data/datasets/rdock_3PTB_50k_pubchem_local/dataset_manifest.json ADDED
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