| get.exhaustive.fragments {rcdk} | R Documentation |
Generate Bemis-Murcko Fragments
Description
Fragment the input molecule using the Bemis-Murcko scheme
Usage
get.exhaustive.fragments(mols, min.frag.size = 6, as.smiles = TRUE)
Arguments
mols |
A list of 'jobjRef' objects of Java class 'IAtomContainer' |
min.frag.size |
The smallest fragment to consider (in terms of heavy atoms) |
as.smiles |
If 'TRUE' return the fragments as SMILES strings. If not, then fragments are returned as 'jobjRef' objects |
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.
Value
returns a list of length equal to the number of input molecules. Each element is a character vector of SMILES strings or a list of 'jobjRef' objects.
Author(s)
Rajarshi Guha (rajarshi.guha@gmail.com)
See Also
[get.murcko.fragments()]
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)