In each case, the correct formula was ranked as top hit when combining the seven rules with database queries. Last, some exemplary compounds were analyzed by Fourier transform ion cyclotron resonance mass spectrometry and by gas chromatography-time of flight mass spectrometry. The correct formulas were retrieved as top hit at 80–99% probability when assuming data acquisition with complete resolution of unique compounds and 5% absolute isotope ratio deviation and 3 ppm mass accuracy. Thirdly 6,000 pharmaceutical, toxic and natural compounds were selected from DrugBank, TSCA and DNP databases.
Next, the rules were shown to effectively reducing the complement all eight billion theoretically possible C, H, N, S, O, P-formulas up to 2000 Da to only 623 million most probable elemental compositions. Only 0.6% of these compounds did not pass all rules. First, 432,968 formulas covering five million PubChem database entries were checked for consistency. The seven rules were developed on 68,237 existing molecular formulas and were validated in four experiments. Formulas are ranked according to their isotopic patterns and subsequently constrained by presence in public chemical databases. ResultsĪn algorithm for filtering molecular formulas is derived from seven heuristic rules: (1) restrictions for the number of elements, (2) LEWIS and SENIOR chemical rules, (3) isotopic patterns, (4) hydrogen/carbon ratios, (5) element ratio of nitrogen, oxygen, phosphor, and sulphur versus carbon, (6) element ratio probabilities and (7) presence of trimethylsilylated compounds. In order to automatically constrain the thousands of possible candidate structures, rules need to be developed to select the most likely and chemically correct molecular formulas. The first crucial step is to obtain correct elemental compositions. Structure elucidation of unknown small molecules by mass spectrometry is a challenge despite advances in instrumentation.
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