RxnSim-package: Functions to compute chemical reaction and molecular...

RxnSim-packageR Documentation

Functions to compute chemical reaction and molecular similarity

Description

RxnSim provides methods to compute molecular and reaction similarity. It uses rCDK package (R Interface to the CDK Libraries) and fingerprints package for chemoinformatic routines.

Details

RxnSim provides methods to compute chemical similarity between two or more reactions and molecules. Molecular similarity is computed based on structural features. Reaction similarity is a function of similarities of participating molecules. The package provides multiple methods to extract structural features as fingerprints (or feature vectors) and similarity metrics. It additionally provides functionality to mask chemical substructures for weighted similarity computations. It uses rCDK and fingerprint packages for cheminformatics functionality.

User functions:

rs.compute

computes similarity between two reactions.

rs.compute.list

computes similarity between all pairs of reactions from two lists.

rs.compute.sim.matrix

computes pairwise similarity between all reactions in a list.

rs.compute.DB

computes similarity of a reaction to those in a reaction database (DB) object read from a text file.

rs.makeDB

reads a text file containing EC Numbers, Reaction Names and Reaction SMILES and converts it into a reaction DB object.

ms.compute

computes similarity between two molecules.

ms.compute.sim.matrix

computes pairwise similarity between all molecules in a list.

rs.clearCache

clears fingerprint cache.

rs.mask

substitutes given sub-structure in the molecules of a reaction by a user defined mask.

ms.mask

substitutes given sub-structure in a molecule by a user defined mask.

Author(s)

Varun Giri varungiri@gmail.com

Maintainer: Varun Giri

See Also

rs.compute, ms.compute

Examples

# Reaction similarity
rs.compute('CCCO>>CCC=O', 'CC(O)C>>CC(=O)C')

# Metabolite similarity
ms.compute('CCC=O', 'CC(O)C')

RxnSim documentation built on July 26, 2023, 5:41 p.m.