ForMileS: A Python Open-Source Program to Generate Molecular Structures for Tandem Mass Spectrometry Fragment Ions

Tandem mass spectrometry is a central analytical tool in chemistry, yet the fragmentation mechanisms underlying collision-induced dissociation remain incompletely understood. A key challenge is predicting fragment ion structures while preserving the essential structural features of the precursor ion. This paper introduces ForMileS (Formation of Mass SMILES), a streamlined Python open-source workflow for generating fragment ion structures with precursor-specific constraints from tandem mass spectrometry data. ForMileS employs a simplified branch-and-bound algorithm, accepting molecular formula, charge state, exact mass, and a base scaffold in SMILES format as input, along with parameters for branching, cyclicity, and bond types, via a graphical user interface. We demonstrate its application to the three main fragments of Polypropylene Glycol Octamer (PPG8), discussing the critical role of the base molecular scaffold (BMS) in the final structure set. Relative energy calculations using Density Functional Theory confirm the presence of expected structures, highlighting the lowest energy conformers. When applied to the smallest fragment of dipropylene glycol dimethyl ether (DGDE), ForMileS reveals that only linear double-bonded or cyclic structures are plausible, with the former being energetically favored. While successfully generating plausible structures, the exhaustive combinatorial charge generation step and the unrefined branch-and-bound method limit ForMileS's performance, restricting its applicability to small molecules like C₆O₃H₁₉. This highlights the importance of future performance optimization through heuristics and energetic filters.