extractDrugECI {Rcpi} | R Documentation

## 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 = ∑_{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`.

### Author(s)

Nan Xiao <https://nanx.me>

### 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)

[Package Rcpi version 1.30.0 Index]