A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule

A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule

Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular de...

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Main Authors: Hamza Hentabli, Faisal Saeed, Ammar Abdo, Naomie Salim
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/286974
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spelling doaj-875a6de8c3a7448f90c0819f821541c92020-11-24T21:30:36ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/286974286974A New Graph-Based Molecular Descriptor Using the Canonical Representation of the MoleculeHamza Hentabli0Faisal Saeed1Ammar Abdo2Naomie Salim3Faculty of Computing, University Technology of Malaysia, 81310 Skudai, Johor, MalaysiaFaculty of Computing, University Technology of Malaysia, 81310 Skudai, Johor, MalaysiaComputer Science Department, Hodeidah University, Hodeidah, YemenFaculty of Computing, University Technology of Malaysia, 81310 Skudai, Johor, MalaysiaMolecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD) is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE) using the Tanimoto coefficient (TAN) and the basic local alignment search tool (BLAST) when searches were carried.http://dx.doi.org/10.1155/2014/286974
collection DOAJ
language English
format Article
sources DOAJ
author Hamza Hentabli
Faisal Saeed
Ammar Abdo
Naomie Salim
spellingShingle Hamza Hentabli
Faisal Saeed
Ammar Abdo
Naomie Salim
A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule
The Scientific World Journal
author_facet Hamza Hentabli
Faisal Saeed
Ammar Abdo
Naomie Salim
author_sort Hamza Hentabli
title A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule
title_short A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule
title_full A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule
title_fullStr A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule
title_full_unstemmed A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule
title_sort new graph-based molecular descriptor using the canonical representation of the molecule
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD) is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE) using the Tanimoto coefficient (TAN) and the basic local alignment search tool (BLAST) when searches were carried.
url http://dx.doi.org/10.1155/2014/286974
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