Exemple #1
0
def test_masked_superimposition(seed):
    """
    Take two models of the same structure and superimpose based on a
    single, randomly chosen atom.
    Since two atoms can be superimposed perfectly, the distance between
    the atom in both models should be 0.
    """

    path = join(data_dir, "1l2y.mmtf")
    fixed = strucio.load_structure(path, model=1)
    mobile = strucio.load_structure(path, model=2)

    # Create random mask for a single atom
    np.random.seed(seed)
    mask = np.full(fixed.array_length(), False)
    mask[np.random.randint(fixed.array_length())] = True

    # The distance between the atom in both models should not be
    # already 0 prior to superimposition
    assert struc.distance(fixed[mask], mobile[mask])[0] \
        != pytest.approx(0, abs=5e-4)

    fitted, transformation = struc.superimpose(fixed, mobile, mask)

    assert struc.distance(fixed[mask], fitted[mask])[0] \
        == pytest.approx(0, abs=5e-4)

    fitted = struc.superimpose_apply(mobile, transformation)

    struc.distance(fixed[mask], fitted[mask])[0] \
        == pytest.approx(0, abs=5e-4)
Exemple #2
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def test_superimposition_array(path):
    pdbx_file = pdbx.PDBxFile()
    pdbx_file.read(path)
    fixed = pdbx.get_structure(pdbx_file, model=1)
    mobile = fixed.copy()
    mobile = struc.rotate(mobile, (1, 2, 3))
    mobile = struc.translate(mobile, (1, 2, 3))
    fitted, transformation = struc.superimpose(fixed, mobile,
                                               (mobile.atom_name == "CA"))
    assert struc.rmsd(fixed, fitted) == pytest.approx(0)
    fitted = struc.superimpose_apply(mobile, transformation)
    assert struc.rmsd(fixed, fitted) == pytest.approx(0)
Exemple #3
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def test_superimposition_array(path):
    """
    Take a structure and rotate and translate a copy of it, so that they
    are not superimposed anymore.
    Then superimpose these structure onto each other and expect an
    almost perfect match.
    """
    fixed = strucio.load_structure(path, model=1)

    mobile = fixed.copy()
    mobile = struc.rotate(mobile, (1, 2, 3))
    mobile = struc.translate(mobile, (1, 2, 3))

    fitted, transformation = struc.superimpose(fixed, mobile)

    assert struc.rmsd(fixed, fitted) == pytest.approx(0, abs=6e-4)

    fitted = struc.superimpose_apply(mobile, transformation)

    assert struc.rmsd(fixed, fitted) == pytest.approx(0, abs=6e-4)
ku_file = biotite.temp_file("ku.cif")

# Download and parse structure files
file = rcsb.fetch("1JEY", "mmtf", biotite.temp_dir())
ku_dna = strucio.load_structure(file)
file = rcsb.fetch("1JEQ", "mmtf", biotite.temp_dir())
ku = strucio.load_structure(file)
# Remove DNA and water
ku_dna = ku_dna[(ku_dna.chain_id == "A") | (ku_dna.chain_id == "B")]
ku_dna = ku_dna[~struc.filter_solvent(ku_dna)]
ku = ku[~struc.filter_solvent(ku)]
# The structures have a differing amount of atoms missing
# at the the start and end of the structure
# -> Find common structure
ku_dna_common = ku_dna[struc.filter_intersection(ku_dna, ku)]
ku_common = ku[struc.filter_intersection(ku, ku_dna)]
# Superimpose
ku_superimposed, transformation = struc.superimpose(
    ku_dna_common, ku_common, (ku_common.atom_name == "CA"))
# We do not want the cropped structures
# -> apply superimposition on structures before intersection filtering
ku_superimposed = struc.superimpose_apply(ku, transformation)
# Write PDBx files as input for PyMOL
cif_file = pdbx.PDBxFile()
pdbx.set_structure(cif_file, ku_dna, data_block="ku_dna")
cif_file.write(ku_dna_file)
cif_file = pdbx.PDBxFile()
pdbx.set_structure(cif_file, ku_superimposed, data_block="ku")
cif_file.write(ku_file)
# Visualization with PyMOL...
# biotite_static_image = ku_superimposition.png
def assemble_peptide(sequence):
    res_names = [seq.ProteinSequence.convert_letter_1to3(r) for r in sequence]
    peptide = struc.AtomArray(length=0)

    for res_id, res_name, connect_angle in zip(
            np.arange(1,
                      len(res_names) + 1), res_names,
            itertools.cycle([120, -120])):
        # Create backbone
        atom_n = struc.Atom([0.0, 0.0, 0.0], atom_name="N", element="N")

        atom_ca = struc.Atom([0.0, N_CA_LENGTH, 0.0],
                             atom_name="CA",
                             element="C")

        coord_c = calculate_atom_coord_by_z_rotation(atom_ca.coord,
                                                     atom_n.coord, 120,
                                                     CA_C_LENGTH)
        atom_c = struc.Atom(coord_c, atom_name="C", element="C")

        coord_o = calculate_atom_coord_by_z_rotation(atom_c.coord,
                                                     atom_ca.coord, 120,
                                                     C_O_DOUBLE_LENGTH)
        atom_o = struc.Atom(coord_o, atom_name="O", element="O")

        coord_h = calculate_atom_coord_by_z_rotation(atom_n.coord,
                                                     atom_ca.coord, -120,
                                                     N_H_LENGTH)
        atom_h = struc.Atom(coord_h, atom_name="H", element="H")

        backbone = struc.array([atom_n, atom_ca, atom_c, atom_o, atom_h])
        backbone.res_id[:] = res_id
        backbone.res_name[:] = res_name

        # Add bonds between backbone atoms
        bonds = struc.BondList(backbone.array_length())
        bonds.add_bond(0, 1, struc.BondType.SINGLE)  # N-CA
        bonds.add_bond(1, 2, struc.BondType.SINGLE)  # CA-C
        bonds.add_bond(2, 3, struc.BondType.DOUBLE)  # C-O
        bonds.add_bond(0, 4, struc.BondType.SINGLE)  # N-H
        backbone.bonds = bonds

        # Get residue from dataset
        residue = info.residue(res_name)
        # Superimpose backbone of residue
        # with backbone created previously
        _, transformation = struc.superimpose(
            backbone[struc.filter_backbone(backbone)],
            residue[struc.filter_backbone(residue)])
        residue = struc.superimpose_apply(residue, transformation)
        # Remove backbone atoms from residue because they are already
        # existing in the backbone created prevoisly
        side_chain = residue[~np.isin(
            residue.
            atom_name, ["N", "CA", "C", "O", "OXT", "H", "H2", "H3", "HXT"])]

        # Assemble backbone with side chain (including HA)
        # and set annotation arrays
        residue = backbone + side_chain
        residue.bonds.add_bond(
            np.where(residue.atom_name == "CA")[0][0],
            np.where(residue.atom_name == "CB")[0][0], struc.BondType.SINGLE)
        residue.bonds.add_bond(
            np.where(residue.atom_name == "CA")[0][0],
            np.where(residue.atom_name == "HA")[0][0], struc.BondType.SINGLE)
        residue.chain_id[:] = "A"
        residue.res_id[:] = res_id
        residue.res_name[:] = res_name
        peptide += residue

        # Connect current residue to existing residues in the chain
        if res_id > 1:
            index_prev_ca = np.where((peptide.res_id == res_id - 1)
                                     & (peptide.atom_name == "CA"))[0][0]
            index_prev_c = np.where((peptide.res_id == res_id - 1)
                                    & (peptide.atom_name == "C"))[0][0]
            index_curr_n = np.where((peptide.res_id == res_id)
                                    & (peptide.atom_name == "N"))[0][0]
            index_curr_c = np.where((peptide.res_id == res_id)
                                    & (peptide.atom_name == "C"))[0][0]
            curr_residue_mask = peptide.res_id == res_id

            # Adjust geometry
            curr_coord_n = calculate_atom_coord_by_z_rotation(
                peptide.coord[index_prev_c], peptide.coord[index_prev_ca],
                connect_angle, C_N_LENGTH)
            peptide.coord[curr_residue_mask] -= peptide.coord[index_curr_n]
            peptide.coord[curr_residue_mask] += curr_coord_n
            # Adjacent residues should show in opposing directions
            # -> rotate residues with even residue ID by 180 degrees
            if res_id % 2 == 0:
                coord_n = peptide.coord[index_curr_n]
                coord_c = peptide.coord[index_curr_c]
                peptide.coord[curr_residue_mask] = struc.rotate_about_axis(
                    atoms=peptide.coord[curr_residue_mask],
                    axis=coord_c - coord_n,
                    angle=np.deg2rad(180),
                    support=coord_n)

            # Add bond between previous C and current N
            peptide.bonds.add_bond(index_prev_c, index_curr_n,
                                   struc.BondType.SINGLE)

    # Add N-terminal hydrogen
    atom_n = peptide[(peptide.res_id == 1) & (peptide.atom_name == "N")][0]
    atom_h = peptide[(peptide.res_id == 1) & (peptide.atom_name == "H")][0]
    coord_h2 = calculate_atom_coord_by_z_rotation(atom_n.coord, atom_h.coord,
                                                  -120, N_H_LENGTH)
    atom_h2 = struc.Atom(coord_h2,
                         chain_id="A",
                         res_id=1,
                         res_name=atom_h.res_name,
                         atom_name="H2",
                         element="H")
    peptide = struc.array([atom_h2]) + peptide
    peptide.bonds.add_bond(0, 1, struc.BondType.SINGLE)  # H2-N

    # Add C-terminal hydroxyl group
    last_id = len(sequence)
    index_c = np.where((peptide.res_id == last_id)
                       & (peptide.atom_name == "C"))[0][0]
    index_o = np.where((peptide.res_id == last_id)
                       & (peptide.atom_name == "O"))[0][0]
    coord_oxt = calculate_atom_coord_by_z_rotation(peptide.coord[index_c],
                                                   peptide.coord[index_o],
                                                   connect_angle, C_O_LENGTH)
    coord_hxt = calculate_atom_coord_by_z_rotation(coord_oxt,
                                                   peptide.coord[index_c],
                                                   connect_angle, O_H_LENGTH)
    atom_oxt = struc.Atom(coord_oxt,
                          chain_id="A",
                          res_id=last_id,
                          res_name=peptide[index_c].res_name,
                          atom_name="OXT",
                          element="O")
    atom_hxt = struc.Atom(coord_hxt,
                          chain_id="A",
                          res_id=last_id,
                          res_name=peptide[index_c].res_name,
                          atom_name="HXT",
                          element="H")
    peptide = peptide + struc.array([atom_oxt, atom_hxt])
    peptide.bonds.add_bond(index_c, -2, struc.BondType.SINGLE)  # C-OXT
    peptide.bonds.add_bond(-2, -1, struc.BondType.SINGLE)  # OXT-HXT

    return peptide