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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/frags.R
\name{get.murcko.fragments}
\alias{get.murcko.fragments}
\title{Generate Bemis-Murcko Fragments}
\usage{
get.murcko.fragments(
mols,
min.frag.size = 6,
as.smiles = TRUE,
single.framework = FALSE
)
}
\arguments{
\item{mols}{A list of `jobjRef` objects of Java class `IAtomContainer`}
\item{min.frag.size}{The smallest fragment to consider (in terms of heavy atoms)}
\item{as.smiles}{If `TRUE` return the fragments as SMILES strings. If not, then fragments
are returned as `jobjRef` objects}
\item{single.framework}{If `TRUE`, then a single framework (i.e., the framework consisting of the
union of all ring systems and linkers) is returned for each molecule. Otherwise, all combinations
of ring systems and linkers are returned}
}
\value{
Returns a list with each element being a list with two elements: `rings` and
`frameworks`. Each of these elements is either a character vector of SMILES strings or a list of
`IAtomContainer` objects.
}
\description{
Fragment the input molecule using the Bemis-Murcko scheme
}
\details{
A variety of methods for fragmenting molecules are available ranging from
exhaustive, rings to more specific methods such as Murcko frameworks. Fragmenting a
collection of molecules can be a useful for a variety of analyses. In addition
fragment based analysis can be a useful and faster alternative to traditional
clustering of the whole collection, especially when it is large.
Note that exhaustive fragmentation of large molecules (with many single bonds) can become
time consuming.
}
\examples{
mol <- parse.smiles('c1ccc(cc1)CN(c2cc(ccc2[N+](=O)[O-])c3c(nc(nc3CC)N)N)C')[[1]]
mf1 <- get.murcko.fragments(mol, as.smiles=TRUE, single.framework=TRUE)
mf1 <- get.murcko.fragments(mol, as.smiles=TRUE, single.framework=FALSE)
}
\seealso{
[get.exhuastive.fragments()]
}
\author{
Rajarshi Guha (\email{rajarshi.guha@gmail.com})
}
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