find-mfs 0.2.2

A Python package for finding molecular formula candidates from a mass and error window

find-mfs: Accurate mass ➜ Molecular Formulae

find-mfs is a simple Python package for finding molecular formulae candidates which fit some given mass (+/- an error window). It implements Böcker & Lipták's algorithm for efficient formula finding, 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:

# For simple queries, one can use this convenience function
from find_mfs import find_chnops

find_chnops(
    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='C*H*N*O*P0S2'      # Element constraints: unlimited C/H/N/O,
                                   # No phosphorous atoms, up to two sulfurs.
)

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

# If processing many masses, it's better to instantiate a FormulaFinder object
from find_mfs import FormulaFinder

finder = FormulaFinder()
finder.find_formulae(
    mass=613.2391,         # Novobiocin [M+H]+ ion; C31H37N2O11+
    charge=1,              
    error_ppm=5.0,         
    # ... etc
)

Jupyter Notebook:

See this Jupyter notebook 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.