Adduct ion mass calculation

adduct-ion-mass-calculation

Summary

Calculate m/z values for derivatized metabolite adduct ions beyond common [M+H]+ and [M-H]- forms, with explicit support for matrix-specific ions like those produced by FMP-10 derivatizing agents. This skill automates adduct enumeration for high-throughput metabolite identification in mass spectrometry imaging.

When to use

When you have derivatized metabolite structures (SMILES or mol format) and need to predict their ionization products in MS imaging, particularly when the derivatizing matrix produces non-standard adducts (e.g., FMP-10-tagged ions, [M+Na]+, [M+K]+, or matrix-specific ion forms) rather than the common [M+H]+ and [M-H]- ions. Use this skill to generate a searchable list of expected m/z values for spectral matching and compound identification.

When NOT to use

• Input metabolites are not derivatized; use standard adduct enumeration for underivatized compounds ([M+H]+, [M-H]-, etc.).
• Derivatizing matrix chemistry rules are not defined or unknown; this skill requires explicit reaction scheme input.
• You are analyzing raw MS spectra directly; this skill produces expected m/z predictions and must be paired with spectral matching or peak detection downstream.

Inputs

• metabolite structures in SMILES or mol file format
• derivatizing matrix chemistry rules (reaction scheme definition)
• metabolite molecular weights (computed from input structures)

Outputs

• adduct ion enumeration list with m/z values
• ion type annotations (e.g., [M+H]+, [M+Na]+, [M+FMP-10]+)
• charge state assignments for each adduct

How to apply

Parse input metabolite structures using RDKit to obtain molecular graphs. Load the derivatizing matrix chemistry rules (e.g., FMP-10 reaction scheme) and apply the derivatization transformation to each metabolite structure using RDKit chemistry operations. Compute the molecular weight of the derivatized product. Enumerate matrix-specific adduct forms (including [M+derivatization_tag]+, [M+Na]+, [M+K]+, and any other known ionization products for that matrix) and calculate their m/z values by dividing the mass by charge state. Annotate each adduct ion with its type, calculated m/z, and charge state. Output the adduct ion list for use in spectral library matching and metabolite annotation workflows.

Related tools

• RDKit (Parse metabolite structures, apply derivatization transformations, and compute molecular weights of derivatized products) — https://www.rdkit.org/
• Met-ID (Software platform that integrates adduct ion enumeration for FMP-10 derivatized metabolites with MS2 spectral matching for automated metabolite identification in mass spectrometry imaging) — https://github.com/pbjarterot/Met-ID

Evaluation signals

• All enumerated m/z values are numeric, positive, and within the expected instrument range (typically 50–2000 m/z for small-molecule metabolomics).
• Charge states match the ionization mode (e.g., +1 for positive-mode adducts, −1 for negative-mode); no mixed charges in a single adduct list.
• Adduct ion annotations include the matrix-specific tag or derivatization marker (e.g., 'FMP-10' appears in ion type labels for matrix-specific ions).
• m/z values differ consistently between adduct types (e.g., [M+Na]+ is ~22 Da higher than [M+H]+ after derivatization); monotonic spacing validates mass shift logic.
• Enumerated adducts match observed peaks in authentic MS spectra when compared to standards with known FMP-10 derivatization.

Limitations

• Derivatization chemistry rules must be manually defined or loaded from a curated database; incorrect or incomplete reaction schemes will produce incorrect adduct predictions.
• FMP-10 is the primary implemented matrix in Met-ID; extensibility to other derivatizing matrices requires local version changes and manual chemistry rule entry.
• The skill does not account for in-source fragmentation, neutral loss, or multimeric adducts; it assumes a single intact derivatized molecule ionizes to a single adduct.
• macOS has known functional group addition issues in Met-ID (documented in README), which may affect derivatization rule application on that platform.

Evidence

• [readme] Met-ID has a particular focus on derivatizing matrices leading to other ions than the common [M+H]+ in positive mode and [M-H]- in negative mode: "Met-ID has a particular focus on derivatizing matrices leading to other ions than the common [M+H]+ in positive mode and [M-H]- in negative mode"
• [other] Apply derivatization transformation to each metabolite structure using RDKit chemistry operations. Compute molecular weight of derivatized product. Enumerate derivatization-specific adduct ions (e.g., [M+derivatization_tag]+, [M+Na]+, [M+K]+, or matrix-specific ions) and calculate their m/z values.: "Apply derivatization transformation to each metabolite structure using RDKit chemistry operations. Compute molecular weight of derivatized product. Enumerate derivatization-specific adduct ions"
• [readme] As [FMP-10] was developed in house, it features heavily in the software, however, this is mostly to show the point at which to start as Met-ID is extendable to use any derivatizing matrix: "As [FMP-10] was developed in house, it features heavily in the software, however, this is mostly to show the point at which to start as Met-ID is extendable to use any derivatizing matrix"
• [other] Parse input metabolite structures (SMILES or mol format) using RDKit. Identify the derivatizing matrix type and load its derivatization chemistry rules: "Parse input metabolite structures (SMILES or mol format) using RDKit. Identify the derivatizing matrix type and load its derivatization chemistry rules"
• [other] Output adduct ion list with m/z, charge, and ion type annotation.: "Output adduct ion list with m/z, charge, and ion type annotation"