Building Chimeras¶
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class
builder.builder.Builder(hit: protlego.database.data.Hit)[source]¶ Graph constructor and visualizer
Examples
myhit= fetch_id(‘10002347’) a=Builder(myhit) aln=a.get_alignment(myhit.query,myhit.no) qPDB, sPDB = a.superimpose_structures(aln,partial_alignment=True) chimeras=a.build_chimeras(partial_alignment=True)
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build_chimeras(partial_alignment: bool = False, cutoff_distance: float = 1) → Dict[str, protlego.builder.chimera.Chimera][source]¶ Build all possible chimeras between the two proteins that fulfill these two criteria: 1) That the distance between the fusion points is below the cutoff distance 2) That the resulting chimera does not present any backbone clashes
- Returns
A dictionary with all the possible chimeras
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static
find_nonstandards(pdb: moleculekit.molecule.Molecule) → list[source]¶ Finds non-standard aminoacids :param pdb: Molecule or Chimera object where to find non-standard aminoacids. :return: list of non-standard residues
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get_alignment(query: str, no: str) → csb.bio.hmm.HHpredHitAlignment[source]¶ Obtain the HHS alignment ‘no’ for query ‘query’. Only the alignment from the fragment region is retrieved. This implies that when the fragment is not located in the N-terminus hit.q_start and the position in the output won’t be the same. For example, if q_start = 20, that aminoacid is in position 0 in aln.query.
- Parameters
query – str. Domain query
no – int. Specifies the position in the file (alignment with subject)
- Returns
HHpredHitAlignment. Alignment between query and subject for the fragment region.
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static
mutate_nonstandards(pdb: moleculekit.molecule.Molecule) → moleculekit.molecule.Molecule[source]¶ - Parameters
pdb – The pdb to mutate the residues to
- Returns
The pdb with the mutated residues -if there are any-
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plot_curves(query: str)[source]¶ Plots the distance between the alpha carbons in the structure for the fragment region along with the number of backbone clashes of the resulting chimera for each position
- Parameters
dst – np.ndarray: an array containign the distance for each fragment position
bbContacts1 – an array containing the number of bb contacts for each fragment position for the resulting chimera of combination query-subject
bbContacts2 – an array containing the number of bb contacts for each fragment position for the resulting chimera of combination subject - query
- Returns
a matplotlib.pyplot figure.
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static
remove_residue(pdb: moleculekit.molecule.Molecule, resid)[source]¶ Removes a specific residue by its name :param pdb: The pdb to mutate the residues to :param resid: :return: The pdb with the filtered residues
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seq2pdbaln(sequence: str, pdb: moleculekit.molecule.Molecule) → List[source]¶ Obtains the resid (positions in the PDB) of the aminoacids involved in the fragment.
- Parameters
sequence – str. sequence of the fragment
pdb – Molecule. PDB from where to obtain the residues
- Returns
mapping. The the PDB Positions of the fragment. A List of tuples of the form: (sequence aminoacid, pdb resid)
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superimpose_structures(aln: csb.bio.hmm.HHpredHitAlignment, partial_alignment: bool = False)[source]¶ - Moves the two molecules to the origin of coordinates.
Aligns the full structures according the fragment and obtains RMSDs and distances.
- Parameters
qpairs – List of CA to be aligned in the query structure
spairs – List of CA to be aligned in the subject structure
- Returns
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Chimera Class¶
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class
builder.chimera.Chimera(filename=None, name=None, **kwargs)[source]¶ -
calc_resid_dist(resid1: int, resid2: int) → numpy.core.multiarray.array[source]¶ Returns the distance between the alpha carbons of two residues” :param resid1:index of residue 1 in the PDB structure :param resid2:index of residue 2 in the PDB structure
- Returns
np.array.
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compute_hydrogen_networks(sidechain_only: bool = True)[source]¶ Analyzes the hydrogen bonds following the Baker Hubbard algorithm and clusters them. (Two residues are in the same cluster if there’s a path of hydrogen networks between them). This function adds protons to the protein. between them :param sidechain_only: The whole residue or sidechain only. Note: Computing networks including backbone leads to very large clusters harder to visualize.
- Returns
A representation for each network
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compute_hydrophobic_clusters(chain: str = 'A', sel: str = 'protein and not backbone and noh and resname ILE VAL LEU', cutoff_area: float = 10)[source]¶ - Parameters
chain – Chain in the PDB to compute the hydrophobic clusters. Examples: “A”, “A B C”. Default: “A”
sel – VMD selection on which to compute the clusters. Default is every sidechain heavy atom ILE, VAL and LEU residues. “protein and not backbone and noh and resname ILE VAL LEU”
- Returns
A representation for each cluster
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