find-mfs 0.1.0

A Python package implementing Bocker & Liptak's algorithm for finding molecular formulae from a given mass, as well as Kind and Fiehn's heuristics

find-mfs: Accurate mass ➜ Molecular Formulae

find-mfs is a Python implementation of Böcker & Lipták's algorithm for efficiently finding molecular formulae candidates which fit some given mass (+/- an error window), as implemented in SIRIUS. find-mfs also implements other methods for filtering the MF candidate lists:

• Octet rule
• Ring/double bond equivalents (RDBE's)
• Predicted isotope envelopes, generated using using Łącki and Startek's algorithm as implemented in IsoSpecPy

Motivation:

I needed to perform mass decomposition and, shockingly, I could not find a Python library for it (despite being a routine process). find-mfs is intended to be used by anyone looking to incorporate molecular formula finding into their Python project.

Installation

pip install find_mfs

Example Usage:

from find_mfs import FormulaFinder

finder = FormulaFinder()
finder.find_formulae(
    mass=613.2391,         # Novobiocin [M+H]+ ion; C31H37N2O11+
    charge=1,              # Charge should be specified - electron mass matters
    error_ppm=5.0,         # Can also specify error_da instead
                           # --- FORMULA FILTERS ----
    check_octet=True,      # Candidates must obey the octet rule
    filter_rdbe=(0, 20),   # Candidates must have 0 to 20 ring/double-bond equivalents
    max_counts={
        'P': 0,            # Candidates must not have any phosphorous atoms
        'S': 2,            # Candidates can have up to two sulfur atoms
    },
)

Output:

FormulaSearchResults(query_mass=613.2391, n_results=38)

Formula                   Error (ppm)     Error (Da)      RDBE      
----------------------------------------------------------------------
[C6H25N30O4S]+               -0.12          0.000073       9.5
[C31H37N2O11]+                0.14          0.000086      14.5
[C14H29N24OS2]+               0.18          0.000110      12.5
[C16H41N10O11S2]+             0.20          0.000121       1.5
[C29H33N12S2]+               -0.64          0.000392      19.5
... and 33 more

See basic_usage.ipynb for more thorough examples/demonstrations

---

If you use this package, make sure to cite:

• Böcker & Lipták, 2007 - this package uses their algorithm for formula finding...
  • ...as implemented in SIRIUS: Böcker et. al., 2008
• Łącki, Valkenborg & Startek 2020 - this package uses IsoSpecPy to quickly simulate isotope envelopes
• Gohlke, 2025 - this package uses molmass, which provides very convenient methods for handling chemical formulae

Contributing

Contributions are welcome. Here's a list of features I feel should be implemented eventually:

• Statistics-based isotope envelope fitting
• Fragmentation constraints
• Element ratio constraints
• GUI app

License

This project is distributed under the GPL-3 license.