Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat

Quantitative structure-activity relationship (QSAR) approach is one of fields in computational chemistry. There are many successful predictive models developed for various activity predictions. Due to the emergence of new patterns of resistance of bacteria to antibacterial agents, new antibacterial...

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Main Author:	Naemat, Noor Hidayah
Format:	Thesis
Language:	English
Published:	2008
Online Access:	https://ir.uitm.edu.my/id/eprint/102096/1/102096.pdf
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spelling	my-uitm-ir.1020962024-09-12T16:27:01Z Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat 2008 Naemat, Noor Hidayah Quantitative structure-activity relationship (QSAR) approach is one of fields in computational chemistry. There are many successful predictive models developed for various activity predictions. Due to the emergence of new patterns of resistance of bacteria to antibacterial agents, new antibacterial agents are needed. Data of benzamide and oxazolidinone derivatives from previous studies were reanalyzed for their antibacterial activities by using different descriptors generated by DRAGON 5. Two methods of variables selection were used, which are stepwise regression and forward selection procedures available in MINITAB 14 statistical software. Multiple linear regressions (MLR) analysis was used in developing QSAR models to determine whether the descriptors used can give good QSAR model. The QSAR models have been evaluated and validated to determine their stabilities and prediction capabilities. Six QSAR models have been developed and their statistical results were compared with data from the previous studies. Four QSAR models developed have higher correlation coefficient, R2 and cross-validation R2 V values, showing higher stabilities and prediction capabilities. The best QSAR model has R2= 0.93 and R2 V= 0.91 and three descriptors were included in this QSAR model. The R2 V for -log MIC of B. subtilis is 0.912, S. aureus is 0.710, E. coli is 0.766, MIC of A. fwcum is 0.272, A. paraciticus is 0.789, and log (1/C) of S. aureus is 0.692. 2008 Thesis https://ir.uitm.edu.my/id/eprint/102096/ https://ir.uitm.edu.my/id/eprint/102096/1/102096.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Applied Sciences Syed Omar, Sharifah Rohaiza
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Syed Omar, Sharifah Rohaiza
description	Quantitative structure-activity relationship (QSAR) approach is one of fields in computational chemistry. There are many successful predictive models developed for various activity predictions. Due to the emergence of new patterns of resistance of bacteria to antibacterial agents, new antibacterial agents are needed. Data of benzamide and oxazolidinone derivatives from previous studies were reanalyzed for their antibacterial activities by using different descriptors generated by DRAGON 5. Two methods of variables selection were used, which are stepwise regression and forward selection procedures available in MINITAB 14 statistical software. Multiple linear regressions (MLR) analysis was used in developing QSAR models to determine whether the descriptors used can give good QSAR model. The QSAR models have been evaluated and validated to determine their stabilities and prediction capabilities. Six QSAR models have been developed and their statistical results were compared with data from the previous studies. Four QSAR models developed have higher correlation coefficient, R2 and cross-validation R2 V values, showing higher stabilities and prediction capabilities. The best QSAR model has R2= 0.93 and R2 V= 0.91 and three descriptors were included in this QSAR model. The R2 V for -log MIC of B. subtilis is 0.912, S. aureus is 0.710, E. coli is 0.766, MIC of A. fwcum is 0.272, A. paraciticus is 0.789, and log (1/C) of S. aureus is 0.692.
format	Thesis
qualification_level	Bachelor degree
author	Naemat, Noor Hidayah
spellingShingle	Naemat, Noor Hidayah Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat
author_facet	Naemat, Noor Hidayah
author_sort	Naemat, Noor Hidayah
title	Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat
title_short	Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat
title_full	Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat
title_fullStr	Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat
title_full_unstemmed	Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat
title_sort	qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / noor hidayah naemat
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Applied Sciences
publishDate	2008
url	https://ir.uitm.edu.my/id/eprint/102096/1/102096.pdf
_version_	1811769207798366208

Qsar study for antibacterial activity from molecular structures of benzamide and oxazolidinone derivatives / Noor Hidayah Naemat

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