Spaces:
Running
Running
OleinikovasV
commited on
Commit
•
4a15a26
1
Parent(s):
5b72455
Update inference_app.py
Browse files- inference_app.py +2 -8
inference_app.py
CHANGED
@@ -18,7 +18,6 @@ def generate_input_conformer(
|
|
18 |
addHs: bool = False,
|
19 |
minimize_maxIters: int = -1,
|
20 |
) -> Chem.Mol:
|
21 |
-
|
22 |
_mol = Chem.MolFromSmiles(ligand_smiles)
|
23 |
# need to add Hs to generate sensible conformers
|
24 |
_mol = Chem.AddHs(_mol)
|
@@ -55,24 +54,19 @@ def generate_input_conformer(
|
|
55 |
|
56 |
|
57 |
def optimize_coordinate(points, bound_buffer=15, dmin=6.05):
|
58 |
-
|
59 |
bounds = list(
|
60 |
zip(
|
61 |
np.average(points, axis=0) - [bound_buffer]*3,
|
62 |
np.average(points, axis=0) + [bound_buffer]*3
|
63 |
)
|
64 |
)
|
65 |
-
|
66 |
# Define the constraint function (ensure dmin distance)
|
67 |
con = NonlinearConstraint(lambda x: np.min(np.linalg.norm(points - x, axis=1)), dmin, 8)
|
68 |
-
|
69 |
# Define the objective function (minimize pairwise distance)
|
70 |
def objective(x):
|
71 |
return np.sum(np.linalg.norm(points - x, axis=1))
|
72 |
-
|
73 |
# Perform differential evolution to find the optimal coordinate
|
74 |
result = differential_evolution(objective, bounds, constraints=con)
|
75 |
-
|
76 |
return result.x, result.fun
|
77 |
|
78 |
|
@@ -96,12 +90,12 @@ def optimize_decoy_coordinate(points, bound_buffer=15, dmin=6.05, decoy_min=4.0,
|
|
96 |
|
97 |
def add_decoy_atom(structure, decoy_pos):
|
98 |
decoy = AtomArrayStack(length=1, depth=1)
|
99 |
-
decoy.coord = np.ones_like(
|
100 |
decoy.chain_id = ["q"]
|
101 |
decoy.element = ["C"]
|
102 |
decoy.atom_name = ["C"]
|
103 |
decoy.res_name = ["GLY"]
|
104 |
-
return structure +
|
105 |
|
106 |
|
107 |
def set_protein_to_new_coord_plus_decoy_atom(input_pdb_file, new_coord, decoy_coord, output_file):
|
|
|
18 |
addHs: bool = False,
|
19 |
minimize_maxIters: int = -1,
|
20 |
) -> Chem.Mol:
|
|
|
21 |
_mol = Chem.MolFromSmiles(ligand_smiles)
|
22 |
# need to add Hs to generate sensible conformers
|
23 |
_mol = Chem.AddHs(_mol)
|
|
|
54 |
|
55 |
|
56 |
def optimize_coordinate(points, bound_buffer=15, dmin=6.05):
|
|
|
57 |
bounds = list(
|
58 |
zip(
|
59 |
np.average(points, axis=0) - [bound_buffer]*3,
|
60 |
np.average(points, axis=0) + [bound_buffer]*3
|
61 |
)
|
62 |
)
|
|
|
63 |
# Define the constraint function (ensure dmin distance)
|
64 |
con = NonlinearConstraint(lambda x: np.min(np.linalg.norm(points - x, axis=1)), dmin, 8)
|
|
|
65 |
# Define the objective function (minimize pairwise distance)
|
66 |
def objective(x):
|
67 |
return np.sum(np.linalg.norm(points - x, axis=1))
|
|
|
68 |
# Perform differential evolution to find the optimal coordinate
|
69 |
result = differential_evolution(objective, bounds, constraints=con)
|
|
|
70 |
return result.x, result.fun
|
71 |
|
72 |
|
|
|
90 |
|
91 |
def add_decoy_atom(structure, decoy_pos):
|
92 |
decoy = AtomArrayStack(length=1, depth=1)
|
93 |
+
decoy.coord = np.ones_like(decoy.coord) * decoy_pos
|
94 |
decoy.chain_id = ["q"]
|
95 |
decoy.element = ["C"]
|
96 |
decoy.atom_name = ["C"]
|
97 |
decoy.res_name = ["GLY"]
|
98 |
+
return structure + decoy
|
99 |
|
100 |
|
101 |
def set_protein_to_new_coord_plus_decoy_atom(input_pdb_file, new_coord, decoy_coord, output_file):
|