extractDrugECI: Calculate the Eccentric Connectivity Index Descriptor

In nanxstats/Rcpi: Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery

Calculate the Eccentric Connectivity Index Descriptor

Description

Calculate the Eccentric Connectivity Index Descriptor

Usage

extractDrugECI(molecules, silent = TRUE)

Arguments

molecules	Parsed molucule object.
silent	Logical. Whether the calculating process should be shown or not, default is TRUE.

Details

Eccentric Connectivity Index (ECI) is a topological descriptor combining distance and adjacency information. This descriptor is described by Sharma et al. and has been shown to correlate well with a number of physical properties. The descriptor is also reported to have good discriminatory ability. The eccentric connectivity index for a hydrogen supressed molecular graph is given by

x_i^c = \sum_{i = 1}^{n} E(i) V(i)

where E(i) is the eccentricity of the i-th atom (path length from the i-th atom to the atom farthest from it) and V(i) is the vertex degree of the i-th atom.

Value

A data frame, each row represents one of the molecules, each column represents one feature. This function returns one column named ECCEN.

References

Sharma, V. and Goswami, R. and Madan, A.K. (1997), Eccentric Connectivity Index: A Novel Highly Discriminating Topological Descriptor for Structure-Property and Structure-Activity Studies, Journal of Chemical Information and Computer Sciences, 37:273-282

Examples

smi = system.file('vignettedata/FDAMDD.smi', package = 'Rcpi')

mol = readMolFromSmi(smi, type = 'mol')
dat = extractDrugECI(mol)
head(dat)

nanxstats/Rcpi documentation built on July 6, 2023, 9:57 a.m.