Predict a structure-aware adduct search space from SMILES

This function applies the same functional-group and ion-mode logic used by BuildMZAnnotationIndex() before any observed m/z is supplied. It is useful for auditing which protonation, deprotonation, alkali-binding, or reactive matrix hypotheses SpaMTP will retain for a structure.

Usage

PredictAdductsFromSMILES(
  smiles,
  polarity = NULL,
  maldi_matrix = NULL,
  rules = NULL,
  min_structure_score = 0.05,
  backend = c("auto", "native"),
  workers = getOption("SpaMTP.smiles_workers", 1L)
)

Arguments

smiles

Character vector of SMILES strings.

polarity

"positive", "negative", or "neutral". When NULL, use the matrix-profile default or positive mode.

maldi_matrix

Optional MALDI matrix/reagent profile.

rules

Optional custom rule table. It cannot be combined with maldi_matrix.

min_structure_score

Minimum rule-specific structural prior marked as retained.

backend, workers

Passed to DeconvolveSMILES().

Value

A ranked data frame with one row per structure/rule combination.

Examples

utils::str(formals(PredictAdductsFromSMILES))
#> Dotted pair list of 7
#>  $ smiles             : symbol 
#>  $ polarity           : NULL
#>  $ maldi_matrix       : NULL
#>  $ rules              : NULL
#>  $ min_structure_score: num 0.05
#>  $ backend            : language c("auto", "native")
#>  $ workers            : language getOption("SpaMTP.smiles_workers", 1L)