Shape-based two dimensional descriptor for searching molecular database

Biological functions of compounds can be predicted from similarity of their chemical structures to discover new compounds for drug development. Molecular similarity can also be used to infer unknown functions and side effects of existing drugs. A multitude of molecular similarity methods based on di...

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Main Author:	Hamza, Hentabli
Format:	Thesis
Language:	English
Published:	2014
Subjects:	QA76 Computer software
Online Access:	http://eprints.utm.my/id/eprint/48607/1/HentabliHamzaMFC2014.pdf
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spelling	my-utm-ep.486072020-03-02T02:34:53Z Shape-based two dimensional descriptor for searching molecular database 2014 Hamza, Hentabli QA76 Computer software Biological functions of compounds can be predicted from similarity of their chemical structures to discover new compounds for drug development. Molecular similarity can also be used to infer unknown functions and side effects of existing drugs. A multitude of molecular similarity methods based on different molecular representations have been used to perform virtual screenings. The molecules are transformed into descriptors to create a chemical database which allows mathematical manipulation and searching of the chemical information contained in the molecules. In this research, a new Shape based Descriptor of Molecule (SBDM) was developed based on the 2-dimensional shape of a chemical compound. The outline shape of a molecule is split into parts that are related in graph connectivity. The first atom in the molecule is determined using the Morgan algorithm. The molecular features, such as atom name, bond type, angle and rings are represented using specific symbols based on some specification rules. Subsequent atoms are scanned in a clockwise direction with respect to the first atom. The scan is repeated until the first atom is reached again. Two similarity measures were used to evaluate the performance of the molecular descriptors, which are the Basic Local Alignment Search Tool (BLAST) and the Tanimoto coefficient. The performance of the SBDM is compared with six standard molecular descriptors. Simulation of virtual screening experiments with the MDL Drug Data Report database show the superiority of the shape-based descriptor, with 19.32 % and 34.13 % in terms of average recall rates for the top of 1 % and 5 % retrieved molecules, respectively, compared to the six standard descriptors mentioned earlier. 2014 Thesis http://eprints.utm.my/id/eprint/48607/ http://eprints.utm.my/id/eprint/48607/1/HentabliHamzaMFC2014.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:85425?queryType=vitalDismax&query=Shape-based+two+dimensional+descriptor+for+searching+molecular+database&public=true masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Hamza, Hentabli Shape-based two dimensional descriptor for searching molecular database
description	Biological functions of compounds can be predicted from similarity of their chemical structures to discover new compounds for drug development. Molecular similarity can also be used to infer unknown functions and side effects of existing drugs. A multitude of molecular similarity methods based on different molecular representations have been used to perform virtual screenings. The molecules are transformed into descriptors to create a chemical database which allows mathematical manipulation and searching of the chemical information contained in the molecules. In this research, a new Shape based Descriptor of Molecule (SBDM) was developed based on the 2-dimensional shape of a chemical compound. The outline shape of a molecule is split into parts that are related in graph connectivity. The first atom in the molecule is determined using the Morgan algorithm. The molecular features, such as atom name, bond type, angle and rings are represented using specific symbols based on some specification rules. Subsequent atoms are scanned in a clockwise direction with respect to the first atom. The scan is repeated until the first atom is reached again. Two similarity measures were used to evaluate the performance of the molecular descriptors, which are the Basic Local Alignment Search Tool (BLAST) and the Tanimoto coefficient. The performance of the SBDM is compared with six standard molecular descriptors. Simulation of virtual screening experiments with the MDL Drug Data Report database show the superiority of the shape-based descriptor, with 19.32 % and 34.13 % in terms of average recall rates for the top of 1 % and 5 % retrieved molecules, respectively, compared to the six standard descriptors mentioned earlier.
format	Thesis
qualification_level	Master's degree
author	Hamza, Hentabli
author_facet	Hamza, Hentabli
author_sort	Hamza, Hentabli
title	Shape-based two dimensional descriptor for searching molecular database
title_short	Shape-based two dimensional descriptor for searching molecular database
title_full	Shape-based two dimensional descriptor for searching molecular database
title_fullStr	Shape-based two dimensional descriptor for searching molecular database
title_full_unstemmed	Shape-based two dimensional descriptor for searching molecular database
title_sort	shape-based two dimensional descriptor for searching molecular database
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2014
url	http://eprints.utm.my/id/eprint/48607/1/HentabliHamzaMFC2014.pdf
_version_	1747817431714234368

Shape-based two dimensional descriptor for searching molecular database

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