ChemmineR: Cheminformatics Toolkit for R
Authors: Kevin Horan, Yiqun Cao, Tyler Backman, Thomas Girke
Last update: 26 September, 2024
Note: the most recent version of this tutorial can be found here and a short overview slide show here.
Introduction
ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of small molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms.
Figure: ChemmineR environment with its add-on packages and selected functionalities
In addition, ChemmineR offers visualization functions for compound clustering results and chemical structures. The integration of chemoinformatic tools with the R programming environment has many advantages, such as easy access to a wide spectrum of statistical methods, machine learning algorithms and graphic utilities. The first version of this package was published in Cao et al. (2008). Since then many additional utilities and add-on packages have been added to the environment (Figure 2) and many more are under development for future releases (Backman, Cao, and Girke 2011; Wang et al. 2013).
Recently Added Features
Improved SMILES support via new
SMIsetobject class and SMILES import/export functionsIntegration of a subset of OpenBabel functionalities via new
ChemmineOBadd-on package (Cao et al. 2008)Streaming functionality for processing millions of molecules on a laptop
Mismatch tolerant maximum common substructure (MCS) search algorithm
Fast and memory efficient fingerprint search support using atom pair or PubChem fingerprints
Getting Started
Installation
The R software for running ChemmineR can be downloaded from CRAN (http://cran.at.r-project.org/). The ChemmineR package can be installed from R with:
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("ChemmineR")Loading the Package and Documentation
library("ChemmineR") # Loads the package library(help="ChemmineR") # Lists all functions and classes
vignette("ChemmineR") # Opens this PDF manual from R Five Minute Tutorial
The following code gives an overview of the most important functionalities provided by ChemmineR. Copy and paste of the commands into the R console will demonstrate their utilities.
Create Instances of SDFset class:
data(sdfsample)
sdfset <- sdfsample
sdfset # Returns summary of SDFset ## An instance of "SDFset" with 100 molecules sdfset[1:4] # Subsetting of object## An instance of "SDFset" with 4 molecules sdfset[[1]] # Returns summarized content of one SDF## An instance of "SDF"
##
## <<header>>
## Molecule_Name Source
## "650001" " -OEChem-07071010512D"
## Comment Counts_Line
## "" " 61 64 0 0 0 0 0 0 0999 V2000"
##
## <<atomblock>>
## C1 C2 C3 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16
## O_1 7.0468 0.0839 0 0 0 0 0 0 0 0 0 0 0 0 0
## O_2 12.2708 1.0492 0 0 0 0 0 0 0 0 0 0 0 0 0
## ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
## H_60 1.8411 -1.5985 0 0 0 0 0 0 0 0 0 0 0 0 0
## H_61 2.6597 -1.2843 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## <<bondblock>>
## C1 C2 C3 C4 C5 C6 C7
## 1 1 16 2 0 0 0 0
## 2 2 23 1 0 0 0 0
## ... ... ... ... ... ... ... ...
## 63 33 60 1 0 0 0 0
## 64 33 61 1 0 0 0 0
##
## <<datablock>> (33 data items)
## PUBCHEM_COMPOUND_CID PUBCHEM_COMPOUND_CANONICALIZED PUBCHEM_CACTVS_COMPLEXITY
## "650001" "1" "700"
## PUBCHEM_CACTVS_HBOND_ACCEPTOR
## "7" "..." view(sdfset[1:4]) # Returns summarized content of many SDFs, not printed here
as(sdfset[1:4], "list") # Returns complete content of many SDFs, not printed here An SDFset is created during the import of an SD file:
sdfset <- read.SDFset("http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/Samples/sdfsample.sdf") Miscellaneous accessor methods for SDFset container:
header(sdfset[1:4]) # Not printed here header(sdfset[[1]])## Molecule_Name Source
## "650001" " -OEChem-07071010512D"
## Comment Counts_Line
## "" " 61 64 0 0 0 0 0 0 0999 V2000" atomblock(sdfset[1:4]) # Not printed here atomblock(sdfset[[1]])[1:4,] ## C1 C2 C3 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16
## O_1 7.0468 0.0839 0 0 0 0 0 0 0 0 0 0 0 0 0
## O_2 12.2708 1.0492 0 0 0 0 0 0 0 0 0 0 0 0 0
## O_3 12.2708 3.1186 0 0 0 0 0 0 0 0 0 0 0 0 0
## O_4 7.9128 2.5839 0 0 0 0 0 0 0 0 0 0 0 0 0bondblock(sdfset[1:4]) # Not printed here bondblock(sdfset[[1]])[1:4,] ## C1 C2 C3 C4 C5 C6 C7
## 1 1 16 2 0 0 0 0
## 2 2 23 1 0 0 0 0
## 3 2 27 1 0 0 0 0
## 4 3 25 1 0 0 0 0 datablock(sdfset[1:4]) # Not printed here datablock(sdfset[[1]])[1:4] ## PUBCHEM_COMPOUND_CID PUBCHEM_COMPOUND_CANONICALIZED PUBCHEM_CACTVS_COMPLEXITY
## "650001" "1" "700"
## PUBCHEM_CACTVS_HBOND_ACCEPTOR
## "7"Assigning compound IDs and keeping them unique:
cid(sdfset)[1:4] # Returns IDs from SDFset object## [1] "CMP1" "CMP2" "CMP3" "CMP4" sdfid(sdfset)[1:4] # Returns IDs from SD file header block## [1] "650001" "650002" "650003" "650004" unique_ids <- makeUnique(sdfid(sdfset))## [1] "No duplicates detected!" cid(sdfset) <- unique_ids Converting the data blocks in an SDFset to a matrix:
blockmatrix <- datablock2ma(datablocklist=datablock(sdfset)) # Converts data block to matrix
numchar <- splitNumChar(blockmatrix=blockmatrix) # Splits to numeric and character matrix
numchar[[1]][1:2,1:2] # Slice of numeric matrix ## PUBCHEM_COMPOUND_CID PUBCHEM_COMPOUND_CANONICALIZED
## 650001 650001 1
## 650002 650002 1 numchar[[2]][1:2,10:11] # Slice of character matrix ## PUBCHEM_MOLECULAR_FORMULA PUBCHEM_OPENEYE_CAN_SMILES
## 650001 "C23H28N4O6" "CC1=CC(=NO1)NC(=O)CCC(=O)N(CC(=O)NC2CCCC2)C3=CC4=C(C=C3)OCCO4"
## 650002 "C18H23N5O3" "CN1C2=C(C(=O)NC1=O)N(C(=N2)NCCCO)CCCC3=CC=CC=C3"Compute atom frequency matrix, molecular weight and formula:
propma <- data.frame(MF=MF(sdfset), MW=MW(sdfset), atomcountMA(sdfset))
propma[1:4, ] ## MF MW C H N O S F Cl
## 650001 C23H28N4O6 456.4916 23 28 4 6 0 0 0
## 650002 C18H23N5O3 357.4069 18 23 5 3 0 0 0
## 650003 C18H18N4O3S 370.4255 18 18 4 3 1 0 0
## 650004 C21H27N5O5S 461.5346 21 27 5 5 1 0 0Assign matrix data to data block:
datablock(sdfset) <- propma
datablock(sdfset[1]) ## $`650001`
## MF MW C H N O S
## "C23H28N4O6" "456.4916" "23" "28" "4" "6" "0"
## F Cl
## "0" "0"String searching in SDFset:
grepSDFset("650001", sdfset, field="datablock", mode="subset") # Returns summary view of matches. Not printed here. grepSDFset("650001", sdfset, field="datablock", mode="index") ## 1 1 1 1 1 1 1 1 1
## 1 2 3 4 5 6 7 8 9Export SDFset to SD file:
write.SDF(sdfset[1:4], file="sub.sdf", sig=TRUE) Plot molecule structure of one or many SDFs:
plot(sdfset[1:4], print=FALSE) # Plots structures to R graphics device