calcDrugFPSim: Calculate Drug Molecule Similarity Derived by Molecular...

Description Usage Arguments Details Value Author(s) References Examples

Description

Calculate Drug Molecule Similarity Derived by Molecular Fingerprints

Usage

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calcDrugFPSim(fp1, fp2, fptype = c("compact", "complete"),
  metric = c("tanimoto", "euclidean", "cosine", "dice", "hamming"))

Arguments

fp1

The first molecule's fingerprints, could be extracted by extractDrugMACCS(), extractDrugMACCSComplete() etc.

fp2

The second molecule's fingerprints.

fptype

The fingerprint type, must be one of "compact" or "complete".

metric

The similarity metric, one of "tanimoto", "euclidean", "cosine", "dice" and "hamming".

Details

This function calculate drug molecule fingerprints similarity. Define a as the features of object A, b is the features of object B, c is the number of common features to A and B:

Value

The numeric similarity value.

Author(s)

Min-feng Zhu <wind2zhu@163.com>, Nan Xiao <http://r2s.name>

References

Gasteiger, Johann, and Thomas Engel, eds. Chemoinformatics. Wiley.com, 2006.

Examples

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mols = readMolFromSDF(system.file('compseq/tyrphostin.sdf', package = 'BioMedR'))

fp1 = extrDrugEstate(mols[[1]])
fp2 = extrDrugEstate(mols[[2]])
calcDrugFPSim(fp1, fp2, fptype = 'compact', metric = 'tanimoto')

BioMedR documentation built on July 5, 2019, 9:03 a.m.