EnzymaticDigestion#

class pyopenms.EnzymaticDigestion#

Bases: object

Cython implementation of _EnzymaticDigestion

Original C++ documentation is available here

Class for the enzymatic digestion of proteins

Digestion can be performed using simple regular expressions, e.g. [KR] | [^P] for trypsin. Also missed cleavages can be modeled, i.e. adjacent peptides are not cleaved due to enzyme malfunction/access restrictions. If n missed cleavages are allowed, all possible resulting peptides (cleaved and uncleaved) with up to n missed cleavages are returned. Thus no random selection of just n specific missed cleavage sites is performed.

__init__()#

Overload:

__init__(self) → None

Overload:

__init__(self, in_0: EnzymaticDigestion) → None

Methods

`__init__`	Overload:
`countInternalCleavageSites`(self, sequence)	Returns the number of internal cleavage sites for this sequence.
`digestUnmodified`(self, sequence, output, ...)	Performs the enzymatic digestion of an unmodified sequence
`getEnzymeName`(self)	Returns the enzyme for the digestion
`getMissedCleavages`(self)	Returns the max.
`getSpecificity`(self)	Returns the specificity for the digestion
`getSpecificityByName`(self, name)	Returns the specificity by name.
`isValidProduct`(self, sequence, pos, length, ...)	Boolean operator returns true if the peptide fragment starting at position pos with length length within the sequence sequence generated by the current enzyme
`setEnzyme`(self, enzyme)	Sets the enzyme for the digestion
`setMissedCleavages`(self, missed_cleavages)	Sets the max.
`setSpecificity`(self, spec)	Sets the specificity for the digestion (default is SPEC_FULL)

Specificity#: alias of __Specificity

countInternalCleavageSites(self, sequence: bytes | str | String) → int#: Returns the number of internal cleavage sites for this sequence.

digestUnmodified(self, sequence: StringView, output: List[StringView], min_length: int, max_length: int) → int#

Performs the enzymatic digestion of an unmodified sequence

By returning only references into the original string this is very fast

Parameters:

sequence – Sequence to digest
output – Digestion products
min_length – Minimal length of reported products
max_length – Maximal length of reported products (0 = no restriction)

Returns:

Number of discarded digestion products (which are not matching length restrictions)

getEnzymeName(self) → bytes | str | String#: Returns the enzyme for the digestion

getMissedCleavages(self) → int#: Returns the max. number of allowed missed cleavages for the digestion

getSpecificity(self) → int#: Returns the specificity for the digestion

getSpecificityByName(self, name: bytes | str | String) → int#: Returns the specificity by name. Returns SPEC_UNKNOWN if name is not valid

isValidProduct(self, sequence: bytes | str | String, pos: int, length: int, ignore_missed_cleavages: bool) → bool#

Boolean operator returns true if the peptide fragment starting at position pos with length length within the sequence sequence generated by the current enzyme

Checks if peptide is a valid digestion product of the enzyme, taking into account specificity and the MC flag provided here

Parameters:

protein – Protein sequence
pep_pos – Starting index of potential peptide
pep_length – Length of potential peptide
ignore_missed_cleavages – Do not compare MC’s of potential peptide to the maximum allowed MC’s

Returns:

True if peptide has correct n/c terminals (according to enzyme, specificity and missed cleavages)

setEnzyme(self, enzyme: DigestionEnzyme) → None#: Sets the enzyme for the digestion

setMissedCleavages(self, missed_cleavages: int) → None#: Sets the max. number of allowed missed cleavages for the digestion (default is 0). This setting is ignored when log model is used

setSpecificity(self, spec: int) → None#: Sets the specificity for the digestion (default is SPEC_FULL)