🚨 fix lint

"""

Imports all submodules 

"""

# flake8: noqa

from deepchem.dock.pose_generation import PoseGenerator

from deepchem.dock.pose_generation import VinaPoseGenerator

from deepchem.dock.docking import Docker

"""

Computes putative binding pockets on protein.

"""

import os

import logging

import tempfile

import numpy as np

from subprocess import call

from deepchem.feat.fingerprints import CircularFingerprint

from deepchem.models.sklearn_models import SklearnModel

from deepchem.utils import rdkit_util

from deepchem.utils import coordinate_box_utils as box_utils

from deepchem.utils.fragment_util import get_contact_atom_indices

Docks Molecular Complexes

"""

import logging

import numpy as np

import os

import tempfile

from subprocess import call

from deepchem.data import NumpyDataset

logger = logging.getLogger(__name__)

Generates protein-ligand docked poses.

"""

import platform

import deepchem

import logging

import numpy as np

import os

import tempfile

import tarfile

from deepchem.utils import geometry_utils

from deepchem.utils import vina_utils

from deepchem.utils import download_url

from deepchem.utils import get_data_dir

logger = logging.getLogger(__name__)

      If specified should be an instance of

      `dc.dock.BindingPocketFinder`.

    """

    data_dir = deepchem.utils.get_data_dir()

    data_dir = get_data_dir()

    if platform.system() == 'Linux':

      url = "http://vina.scripps.edu/download/autodock_vina_1_1_2_linux_x86.tgz"

      filename = "autodock_vina_1_1_2_linux_x86.tgz"

def vina_gaussian_first(d):

  """Computes Autodock Vina's first Gaussian interaction term.

  Here, d is the set of surface distances as defined in:

  Jain, Ajay N. "Scoring noncovalent protein-ligand interactions: a continuous differentiable function tuned to compute binding affinities." Journal of computer-aided molecular design 10.5 (1996): 427-440.

  Here, d is the set of surface distances as defined in [1]_

  Parameters

  ----------

  Returns

  -------

  A `(N, M)` array of gaussian interaction terms.

  References

  ----------

  .. [1] Jain, Ajay N. "Scoring noncovalent protein-ligand interactions:

     a continuous differentiable function tuned to compute binding affinities."

     Journal of computer-aided molecular design 10.5 (1996): 427-440.

  """

  out_tensor = np.exp(-(d / 0.5)**2)

  return out_tensor

def vina_gaussian_second(d):

  """Computes Autodock Vina's second Gaussian interaction term.

  Here, d is the set of surface distances as defined in:

  Jain, Ajay N. "Scoring noncovalent protein-ligand interactions: a continuous differentiable function tuned to compute binding affinities." Journal of computer-aided molecular design 10.5 (1996): 427-440.

  Here, d is the set of surface distances as defined in [1]_

  Parameters

  ----------

  Returns

  -------

  A `(N, M)` array of gaussian interaction terms.

  References

  ----------

  .. [1] Jain, Ajay N. "Scoring noncovalent protein-ligand interactions:

     a continuous differentiable function tuned to compute binding affinities."

     Journal of computer-aided molecular design 10.5 (1996): 427-440.

  """

  out_tensor = np.exp(-((d - 3) / 2)**2)

  return out_tensor