Metadata-Version: 2.1
Name: peptacular
Version: 2.1.0
Summary: A spectacularly simple package for working with peptide sequences.
Author-email: Patrick Garrett <pgarrett@scripps.edu>
License: MIT License
        
        Copyright (c) 2023 Patrick Garrett
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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Project-URL: repository, https://github.com/pgarrett-scripps/peptacular.git
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: regex


# Peptacular

A spectacularly simple package for working with peptide sequences. Now proforma2.0 compliant.

# Warnings

- The internal fragment ion mass calculation may not be accurate. Fairly certain that the ay, by, and cy internal fragments are 
correct since the y fragment is really just a smaller parent ion.
- GNO and RESID mods are disabled for now. I will add them back in later.
- Project is still under development. I will be adding more features and fixing bugs as I find them.

## ReadTheDocs
https://peptacular.readthedocs.io/en/latest/index.html

## Installation

```bash
pip install peptacular
```

### Proforma Notation:
- https://pubs.acs.org/doi/suppl/10.1021/acs.jproteome.1c00771/suppl_file/pr1c00771_si_001.pdf

### Modification Types:
- Modifications can be represented as str, int, or float.
- During parsing, the module automatically identifies the modification type based on its representation.

## Ion Types:
 - Terminal: a, b, c, x, y, z
 - Internal: ax, ay, az, bx, by, bz, cx, cy, cz
 - Immonium: i
 - special: p, n (precursor, none)

## Working with Sequences
```python
import peptacular as pt

# Add mods to sequence
sequence = pt.add_mods('P[1.2345]EPTIDE', {5: 1, 'cterm': 'Amide'})
assert sequence == 'P[1.2345]EPTID[1]E-[Amide]'

# Get mods: mods are returned as a list of Mod objects Mod(value, multiplier)
mods = pt.get_mods(sequence)
assert mods == {'cterm': [pt.Mod('Amide', 1)], 0: [pt.Mod(1.2345, 1)], 5: [pt.Mod(1, 1)]}

# Strip mods
stripped_sequence = pt.strip_mods(sequence)
assert stripped_sequence == 'PEPTIDE'

# Pop mods
stripped_sequence, mods = pt.pop_mods(sequence)
assert stripped_sequence == 'PEPTIDE'
assert mods == {'cterm': [pt.Mod('Amide', 1)], 0: [pt.Mod(1.2345, 1)], 5: [pt.Mod(1, 1)]}

# Reverse sequence
reverse_sequence = pt.reverse(sequence, swap_terms=False)
assert reverse_sequence == 'ED[1]ITPEP[1.2345]-[Amide]'
```

## Calculating mass and m/z

```python
import peptacular as pt

# Calculate mass (monoisotopic)
peptide_mass = pt.mass('PEP[1.0]TIDE-[2.0]', charge=2, precision=3)
assert peptide_mass == 804.375

# Calculate m/z (monoisotopic)
peptide_mz = pt.mz('PEP[1.0]TIDE-[2.0]', charge=2, precision=3)
assert peptide_mz == 402.187

# Calculate m/z (average)
peptide_mz = pt.mz('PEP[1.0]TIDE-[2.0]', charge=2, monoisotopic=False, precision=3)
assert peptide_mz == 402.419

# For a given ion type
peptide_mz = pt.mz('PEP[1.0]TIDE-[2.0]', ion_type='y', charge=2, precision=3)
assert peptide_mz == 402.419
```

## Building Fragment Ions

```python
import peptacular as pt

# Calculate the m/z values for the y+ fragments.
pt.fragment('P[1.0]TIDE-[2.0]', ion_types='y', charges=1, monoisotopic=True)

# Or for multiple ion types and charges.
pt.fragment('P[1.0]EP', ion_types=['y', 'b'], charges=[1, 2], monoisotopic=True)

# Or for internal ions
pt.fragment('P[1.0]EP', ion_types='by', charges=[1, 2], monoisotopic=True)

# Immonium ions
pt.fragment('P[1.0]EP', ion_types='i', charges=1, monoisotopic=True)

# Can also return M/Z values rather than Fragment objects
pt.fragment('P[1.0]EP', ion_types='y', charges=1, monoisotopic=True, return_type='mz')
```

## Digesting Sequences
```python
import peptacular as pt

# Can use enzyme name from Constants.PROTEASES
peptides = pt.digest('TIDERTIDEKT[1]IDE-[2]', enzyme_regex='trypsin/P', missed_cleavages=2)
assert set(peptides) == {'TIDER', 'TIDERTIDEK', 'TIDERTIDEKT[1]IDE-[2]', 'TIDEK',
                    'TIDEKT[1]IDE-[2]', 'T[1]IDE-[2]'}

# or use a custom regex
peptides = pt.digest('TIDERTIDEKT[1]IDE-[2]', enzyme_regex='([KR])', missed_cleavages=2)
assert set(peptides) == {'TIDER', 'TIDERTIDEK', 'TIDERTIDEKT[1]IDE-[2]', 'TIDEK',
                    'TIDEKT[1]IDE-[2]', 'T[1]IDE-[2]'}

# Also supports semi-enzymatic digestion (might want to use min/max len to filter)
peptides = pt.digest('TIDERTIDEKT[1]IDE-[2]', enzyme_regex='trypsin/P', missed_cleavages=2,
                  semi=True, min_len=10)
assert set(peptides) == {'TIDERTIDEK', 'TIDERTIDEKT[1]IDE-[2]', 'TIDERTIDEKT[1]ID', 'TIDERTIDEKT[1]I',
                    'TIDERTIDEKT[1]', 'IDERTIDEKT[1]IDE-[2]', 'DERTIDEKT[1]IDE-[2]',
                    'ERTIDEKT[1]IDE-[2]', 'RTIDEKT[1]IDE-[2]'}
```

## Static and Variable Modifications

```python
import peptacular as pt

# Apply static modifications
peptide = pt.apply_static_mods('PEPTIDE-[2]', {'P': ['phospho'], '(?<=P)E': [1]})
assert peptide == 'P[phospho]E[1]P[phospho]TIDE-[2]'

# Apply variable modifications
peptides = pt.apply_variable_mods('PEPTIDE-[2]', {'P': [['phospho']], '(?<=P)E': [[1]]}, max_mods=2)
print(peptides)
assert peptides == ['P[phospho]E[1]PTIDE-[2]', 'P[phospho]EP[phospho]TIDE-[2]', 'P[phospho]EPTIDE-[2]',
                    'PE[1]P[phospho]TIDE-[2]', 'PE[1]PTIDE-[2]', 'PEP[phospho]TIDE-[2]', 'PEPTIDE-[2]']

```

## Isotopic Distribution
```python
import peptacular as pt

# 1) Get the isotopic distribution for a chemical composition:
formula = {'C': 12, 'H': 6, 'N': 3}
isotopes = pt.isotopic_distribution(chemical_formula=formula, max_isotopes=3)
assert isotopes == [(192.05617, 1.0), (193.05321, 0.010959894014211729), (193.05952, 0.1297887395127868)]

# 2) Get the isotopic distribution for a peptide sequence:
sequence = 'PEPTIDE'
composition = pt.comp(sequence)
isotopes = pt.isotopic_distribution(chemical_formula=composition, max_isotopes=3)
assert isotopes ==  [(799.35997, 1.0), (800.36332, 0.3677347619528959), (801.36668, 0.06562576793973895)]


# 3) Get the estimated isotopic distribution for a given mass value
mass = 1000.0
composition = pt.estimate_comp(mass)
isotopes = pt.isotopic_distribution(chemical_formula=composition, max_isotopes=3)
assert isotopes == [(1000.0000038305802, 1.0), (1001.0033538305802, 0.47589204488021836),
                     (1002.0067138305802, 0.11066305966308926)]

# 4) By default, the isotopic_distribution function uses the masses of the elements, but it is also possible to use
#    neutron offsets from the monoisotopic peak.
sequence = 'PEPTIDE'
composition = pt.comp(sequence)
isotopes = pt.isotopic_distribution(chemical_formula=composition, max_isotopes=3, use_neutron_count=True)
assert isotopes == [(0, 1.0), (1, 0.4051174337315902), (2, 0.11084816056223826)]
```
