schrodinger.protein.align module

class schrodinger.protein.align.ASLResult(ref_ok, other_ok, other_skips)

Bases: tuple

__contains__

Return key in self.

__init__

Initialize self. See help(type(self)) for accurate signature.

__len__

Return len(self).

count(value) → integer -- return number of occurrences of value
index(value[, start[, stop]]) → integer -- return first index of value.

Raises ValueError if the value is not present.

other_ok

Alias for field number 1

other_skips

Alias for field number 2

ref_ok

Alias for field number 0

exception schrodinger.protein.align.CantAlignException

Bases: Exception

Exception raised when an aligner cannot start e.g. due to not enough seqs

__init__

Initialize self. See help(type(self)) for accurate signature.

args
with_traceback()

Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

class schrodinger.protein.align.AbstractAligner

Bases: object

Base class of objects that can perform an alignment

run(aln)

Aligns the sequences in an alignment using the parameters supplied on init

Subclasses need to override this default implementation.

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
__init__

Initialize self. See help(type(self)) for accurate signature.

class schrodinger.protein.align.RescodeAligner

Bases: schrodinger.protein.align.AbstractAligner

Aligns sequences by rescode

run(aln)

Aligns the sequences in an alignment using the parameters supplied on init

Subclasses need to override this default implementation.

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
__init__

Initialize self. See help(type(self)) for accurate signature.

class schrodinger.protein.align.AbstractPairwiseAligner(merge_all=False)

Bases: schrodinger.protein.align.AbstractAligner

Abstract class for pairwise alignment where gaps can be merged into the entire alignment to preserve relative alignment of all non-reference sequences to the reference sequence.

Subclasses must implement _getPairwiseGaps to align one sequence to the ref seq. Subclasses may override _run to customize aligning (e.g. validation or

setup of additional data needed by _getPairwiseGaps)
__init__(merge_all=False)
Parameters:merge_all (bool) – Whether to merge the sequence with the whole alignment or only up to itself.
run(aln, seqs_to_align=None, **kwargs)

kwargs are additional arguments that will be passed to _run.

Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • seqs_to_align (list(sequence.Sequence)) – The sequences in aln to align against the reference sequence of aln. If None, defaults to the first non-reference sequence in aln (ie aln[1])
Raises:

CantAlignException – If seqs_to_align contains a sequence not found in aln.
class schrodinger.protein.align.AbstractNWPairwiseAligner(merge_all=False, gap_open_penalty=1, gap_extend_penalty=0, sub_matrix=None, direct_scores=False, ss_constraints=False)

Bases: schrodinger.protein.align.AbstractPairwiseAligner

Abstract class for the Needleman-Wunsch global alignment algorithm for pairwise sequence alignment with affine gap penalties.

Variables:
  • CONSTRAINT_SCORE – Reward amount for keeping constrained residues aligned
  • RES_MATCH_BONUS – Reward amount for aligning matching residues. Used by default if a substitution matrix is not specified.
  • RES_MISMATCH_PENALTY – Penalty for aligning differing residues. Used by default if a subtitution matrix is not specified
Ctype CONSTRAINT_SCORE:
 

float
Ctype RES_MATCH_BONUS:
 

float
Ctype RES_MISMATCH_PENALTY:
 

float
CONSTRAINT_SCORE = 10000
RES_MATCH_BONUS = 1.0
RES_MISMATCH_PENALTY = 1.0
__init__(merge_all=False, gap_open_penalty=1, gap_extend_penalty=0, sub_matrix=None, direct_scores=False, ss_constraints=False)
Parameters:
  • merge_all (bool) – Whether to merge the sequence with the whole alignment or only up to itself.
  • gap_open_penalty (float) – Penalty for opening a gap. Should be >=0.
  • gap_extend_penalty (float) – Penalty for extending a gap. Should be >=0.
  • sub_matrix (2D float array or dict mapping (char, char) to float) – Scoring matrix to be used for the alignment. If no matrix is specified, this method uses residue identity measure.
  • direct_scores (bool) – Use scoring matrix directly as (NxM) where N, M are lengths of both sequences rather than default 20x20 substitution matrix.
  • ss_constraints (bool) – Whether to constrain the alignment so no gaps appear in middle of a secondary structure.
run(aln, seqs_to_align=None, **kwargs)

kwargs are additional arguments that will be passed to _run.

Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • seqs_to_align (list(sequence.Sequence)) – The sequences in aln to align against the reference sequence of aln. If None, defaults to the first non-reference sequence in aln (ie aln[1])
Raises:

CantAlignException – If seqs_to_align contains a sequence not found in aln.
class schrodinger.protein.align.SchrodingerPairwiseAligner(**kwargs)

Bases: schrodinger.protein.align.AbstractNWPairwiseAligner

Implementation of the Needleman-Wunsch global alignment algorithm for pairwise sequence alignment with affine gap penalties.

  1. ability to merge new sequence with existing alignment,
  2. ability to penalize gaps in secondary structure elements,
  3. ability to use custom substitution matrix generated from a family of proteins or provided by the user.
NOTE::
Any residues with variant residue types will have their short codes uppercased. This means they will be treated identically to their standard variant. If a nonstandard residue type has a lowercase short code that doesn’t match its standard variant, or if we need special treatment for variant residues, _getMatrixValue will have to be changed.
__init__(**kwargs)
Parameters:
  • merge_all (bool) – Whether to merge the sequence with the whole alignment or only up to itself.
  • gap_open_penalty (float) – Penalty for opening a gap. Should be >=0.
  • gap_extend_penalty (float) – Penalty for extending a gap. Should be >=0.
  • sub_matrix (2D float array or dict mapping (char, char) to float) – Scoring matrix to be used for the alignment. If no matrix is specified, this method uses residue identity measure.
  • direct_scores (bool) – Use scoring matrix directly as (NxM) where N, M are lengths of both sequences rather than default 20x20 substitution matrix.
  • ss_constraints (bool) – Whether to constrain the alignment so no gaps appear in middle of a secondary structure.
getAlignmentScore()

Get the score of the alignment. Found by taking the highest value in the scoring matrix.

Returns:Score of the pairwise alignment.
Return type:float
CONSTRAINT_SCORE = 10000
RES_MATCH_BONUS = 1.0
RES_MISMATCH_PENALTY = 1.0
run(aln, seqs_to_align=None, **kwargs)

kwargs are additional arguments that will be passed to _run.

Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • seqs_to_align (list(sequence.Sequence)) – The sequences in aln to align against the reference sequence of aln. If None, defaults to the first non-reference sequence in aln (ie aln[1])
Raises:

CantAlignException – If seqs_to_align contains a sequence not found in aln.
class schrodinger.protein.align.BiopythonPairwiseAligner(*args, **kwargs)

Bases: schrodinger.protein.align.AbstractNWPairwiseAligner

Pairwise alignment using Biopython.

NOTE::
Any residues with variant residue types will have their short codes uppercased. This means they will be treated identically to their standard variant. If a nonstandard residue type has a lowercase short code that doesn’t match its standard variant, or if we need special treatment for variant residues, _getMatrixValue will have to be changed.
__init__(*args, **kwargs)
Parameters:
  • merge_all (bool) – Whether to merge the sequence with the whole alignment or only up to itself.
  • gap_open_penalty (float) – Penalty for opening a gap. Should be >=0.
  • gap_extend_penalty (float) – Penalty for extending a gap. Should be >=0.
  • sub_matrix (2D float array or dict mapping (char, char) to float) – Scoring matrix to be used for the alignment. If no matrix is specified, this method uses residue identity measure.
  • direct_scores (bool) – Use scoring matrix directly as (NxM) where N, M are lengths of both sequences rather than default 20x20 substitution matrix.
  • ss_constraints (bool) – Whether to constrain the alignment so no gaps appear in middle of a secondary structure.
getAlignmentScore()

Get the score of the alignment. Found by taking the highest value in the scoring matrix.

Returns:Score of the pairwise alignment.
Return type:float
CONSTRAINT_SCORE = 10000
RES_MATCH_BONUS = 1.0
RES_MISMATCH_PENALTY = 1.0
run(aln, seqs_to_align=None, **kwargs)

kwargs are additional arguments that will be passed to _run.

Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • seqs_to_align (list(sequence.Sequence)) – The sequences in aln to align against the reference sequence of aln. If None, defaults to the first non-reference sequence in aln (ie aln[1])
Raises:

CantAlignException – If seqs_to_align contains a sequence not found in aln.
class schrodinger.protein.align.PrimeSTAAligner(protein_family=None)

Bases: schrodinger.protein.align.AbstractAligner

Sequence alignment using $SCHRODINGER/sta

__init__(protein_family=None)
Parameters:protein_family (str or NoneType) – ‘GPCR’ for specialized alignment or None for default templates.
run(aln, structured_seq=None, constraints=None)
Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • structured_seq (sequence.ProteinSequence or NoneType) – Structured sequence to use as reference. If None, the first non-reference seq will be aligned.
  • constraints (list(tuple(residue.Residue, residue.Residue)) or NoneType) – Pairs of (reference_seq, structured_seq) residues to constrain
class schrodinger.protein.align.ClustalAligner

Bases: schrodinger.protein.align.AbstractAligner

Aligns sequences using the Clustal alignment algorithm.

run(aln)

Aligns the sequences in an alignment

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
__init__

Initialize self. See help(type(self)) for accurate signature.

class schrodinger.protein.align.SuperpositionAligner(gap_open_penalty=None, gap_extend_penalty=None)

Bases: schrodinger.protein.align.BiopythonPairwiseAligner

Align structured sequences based on their superposition.

__init__(gap_open_penalty=None, gap_extend_penalty=None)
Parameters:
  • merge_all (bool) – Whether to merge the sequence with the whole alignment or only up to itself.
  • gap_open_penalty (float) – Penalty for opening a gap. Should be >=0.
  • gap_extend_penalty (float) – Penalty for extending a gap. Should be >=0.
  • sub_matrix (2D float array or dict mapping (char, char) to float) – Scoring matrix to be used for the alignment. If no matrix is specified, this method uses residue identity measure.
  • direct_scores (bool) – Use scoring matrix directly as (NxM) where N, M are lengths of both sequences rather than default 20x20 substitution matrix.
  • ss_constraints (bool) – Whether to constrain the alignment so no gaps appear in middle of a secondary structure.
CONSTRAINT_SCORE = 10000
RES_MATCH_BONUS = 1.0
RES_MISMATCH_PENALTY = 1.0
getAlignmentScore()

Get the score of the alignment. Found by taking the highest value in the scoring matrix.

Returns:Score of the pairwise alignment.
Return type:float
run(aln, seqs_to_align=None, **kwargs)

kwargs are additional arguments that will be passed to _run.

Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • seqs_to_align (list(sequence.Sequence)) – The sequences in aln to align against the reference sequence of aln. If None, defaults to the first non-reference sequence in aln (ie aln[1])
Raises:

CantAlignException – If seqs_to_align contains a sequence not found in aln.
class schrodinger.protein.align.AbstractStructureAligner(keywords=None, **kwargs)

Bases: schrodinger.protein.align.AbstractAligner

Subclasses must reimplement run: - Call _setUpSeqs to set up instance attributes for the current alignment - Call _setASLs to validate and store ASLs - Call _getUniqueEidSeqs to get the sequences to align - Call _runStructureAlignment to call the backend

class Result(ref_seq, other_seq, psd, rmsd)

Bases: tuple

__contains__

Return key in self.

__init__

Initialize self. See help(type(self)) for accurate signature.

__len__

Return len(self).

count(value) → integer -- return number of occurrences of value
index(value[, start[, stop]]) → integer -- return first index of value.

Raises ValueError if the value is not present.

other_seq

Alias for field number 1

psd

Alias for field number 2

ref_seq

Alias for field number 0

rmsd

Alias for field number 3

__init__(keywords=None, **kwargs)
Parameters:keywords (dict) – Keywords to pass to the ska backend
getResultSeqs()
run(aln)

Aligns the sequences in an alignment using the parameters supplied on init

Subclasses need to override this default implementation.

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
class schrodinger.protein.align.StructureAligner(keywords=None, **kwargs)

Bases: schrodinger.protein.align.AbstractStructureAligner

Run structure alignment using the specified sequences to create chain ASLs

run(aln, seqs_to_align, **kwargs)

Aligns the sequences in an alignment using the parameters supplied on init

Subclasses need to override this default implementation.

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
class Result(ref_seq, other_seq, psd, rmsd)

Bases: tuple

__contains__

Return key in self.

__init__

Initialize self. See help(type(self)) for accurate signature.

__len__

Return len(self).

count(value) → integer -- return number of occurrences of value
index(value[, start[, stop]]) → integer -- return first index of value.

Raises ValueError if the value is not present.

other_seq

Alias for field number 1

psd

Alias for field number 2

ref_seq

Alias for field number 0

rmsd

Alias for field number 3

__init__(keywords=None, **kwargs)
Parameters:keywords (dict) – Keywords to pass to the ska backend
getResultSeqs()
class schrodinger.protein.align.CustomASLStructureAligner(keywords=None, ref_asl=None, other_asl=None)

Bases: schrodinger.protein.align.AbstractStructureAligner

Run structure alignment using specified ASLs

SENTINEL = <object object>
__init__(keywords=None, ref_asl=None, other_asl=None)
Parameters:keywords (dict) – Keywords to pass to the ska backend
evaluateASLs(aln, seqs_to_align)

Determine whether the ASLs match any atoms in the sequences’ structures

Parameters:
  • aln – Alignment
  • seqs_to_align – Sequences to align
Return type:

ASLResult
run(aln, seqs_to_align, **kwargs)

Aligns the sequences in an alignment using the parameters supplied on init

Subclasses need to override this default implementation.

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
class Result(ref_seq, other_seq, psd, rmsd)

Bases: tuple

__contains__

Return key in self.

__init__

Initialize self. See help(type(self)) for accurate signature.

__len__

Return len(self).

count(value) → integer -- return number of occurrences of value
index(value[, start[, stop]]) → integer -- return first index of value.

Raises ValueError if the value is not present.

other_seq

Alias for field number 1

psd

Alias for field number 2

ref_seq

Alias for field number 0

rmsd

Alias for field number 3

getResultSeqs()
class schrodinger.protein.align.MaxIdentityAligner

Bases: schrodinger.protein.align.BiopythonPairwiseAligner

Pairwise aligner that maximizes the number of matching residues between two sequences. There are no penalties for mismatches or gaps.

__init__()
Parameters:
  • merge_all (bool) – Whether to merge the sequence with the whole alignment or only up to itself.
  • gap_open_penalty (float) – Penalty for opening a gap. Should be >=0.
  • gap_extend_penalty (float) – Penalty for extending a gap. Should be >=0.
  • sub_matrix (2D float array or dict mapping (char, char) to float) – Scoring matrix to be used for the alignment. If no matrix is specified, this method uses residue identity measure.
  • direct_scores (bool) – Use scoring matrix directly as (NxM) where N, M are lengths of both sequences rather than default 20x20 substitution matrix.
  • ss_constraints (bool) – Whether to constrain the alignment so no gaps appear in middle of a secondary structure.
run(aln)

kwargs are additional arguments that will be passed to _run.

Parameters:
  • aln (alignment.Alignment) – The alignment containing sequences to align.
  • seqs_to_align (list(sequence.Sequence)) – The sequences in aln to align against the reference sequence of aln. If None, defaults to the first non-reference sequence in aln (ie aln[1])
Raises:

CantAlignException – If seqs_to_align contains a sequence not found in aln.
CONSTRAINT_SCORE = 10000
RES_MATCH_BONUS = 1.0
RES_MISMATCH_PENALTY = 1.0
getAlignmentScore()

Get the score of the alignment. Found by taking the highest value in the scoring matrix.

Returns:Score of the pairwise alignment.
Return type:float
class schrodinger.protein.align.StructurelessGapAligner

Bases: schrodinger.protein.align.AbstractAligner

Align all structureless residues with gaps

For example, given the following alignment (where circled letters are structureless residues):

Resnum: 0 1 2 3 4 5 Seq1: Ⓐ Ⓡ Ⓒ A D E Seq2: Ⓒ Ⓐ Ⓝ A D A

The result will be:

Resnum: 0 1 2 3 4 5 6 7 8 Seq1: ~ ~ ~ Ⓐ Ⓡ Ⓒ A D E Seq2: Ⓒ Ⓐ Ⓝ ~ ~ ~ A D A

run(aln, seqs_to_align=None)

Aligns the sequences in an alignment using the parameters supplied on init

Subclasses need to override this default implementation.

Parameters:aln (schrodinger.protein.alignment.BaseAlignment) – The alignment to align
__init__

Initialize self. See help(type(self)) for accurate signature.