Structure-based molecular modeling in SAR analysis and lead optimization

In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, wit...
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Autor*in:	Veronika Temml [verfasserIn] Zsofia Kutil [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Docking Pharmacophore modeling Lead optimization Structure-activity relationship Molecular modeling

Übergeordnetes Werk:	In: Computational and Structural Biotechnology Journal - Elsevier, 2013, 19(2021), Seite 1431-1444
Übergeordnetes Werk:	volume:19 ; year:2021 ; pages:1431-1444

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.csbj.2021.02.018

Katalog-ID:	DOAJ019083874

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spelling	10.1016/j.csbj.2021.02.018 doi (DE-627)DOAJ019083874 (DE-599)DOAJ346555cb4758458f84fa0a4695b3e93c DE-627 ger DE-627 rakwb eng TP248.13-248.65 Veronika Temml verfasserin aut Structure-based molecular modeling in SAR analysis and lead optimization 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose. Docking Pharmacophore modeling Lead optimization Structure-activity relationship Molecular modeling Biotechnology Zsofia Kutil verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 19(2021), Seite 1431-1444 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:19 year:2021 pages:1431-1444 https://doi.org/10.1016/j.csbj.2021.02.018 kostenfrei https://doaj.org/article/346555cb4758458f84fa0a4695b3e93c kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037021000696 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2021 1431-1444
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allfieldsGer	10.1016/j.csbj.2021.02.018 doi (DE-627)DOAJ019083874 (DE-599)DOAJ346555cb4758458f84fa0a4695b3e93c DE-627 ger DE-627 rakwb eng TP248.13-248.65 Veronika Temml verfasserin aut Structure-based molecular modeling in SAR analysis and lead optimization 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose. Docking Pharmacophore modeling Lead optimization Structure-activity relationship Molecular modeling Biotechnology Zsofia Kutil verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 19(2021), Seite 1431-1444 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:19 year:2021 pages:1431-1444 https://doi.org/10.1016/j.csbj.2021.02.018 kostenfrei https://doaj.org/article/346555cb4758458f84fa0a4695b3e93c kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037021000696 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2021 1431-1444
allfieldsSound	10.1016/j.csbj.2021.02.018 doi (DE-627)DOAJ019083874 (DE-599)DOAJ346555cb4758458f84fa0a4695b3e93c DE-627 ger DE-627 rakwb eng TP248.13-248.65 Veronika Temml verfasserin aut Structure-based molecular modeling in SAR analysis and lead optimization 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose. Docking Pharmacophore modeling Lead optimization Structure-activity relationship Molecular modeling Biotechnology Zsofia Kutil verfasserin aut In Computational and Structural Biotechnology Journal Elsevier, 2013 19(2021), Seite 1431-1444 (DE-627)731890086 (DE-600)2694435-2 20010370 nnns volume:19 year:2021 pages:1431-1444 https://doi.org/10.1016/j.csbj.2021.02.018 kostenfrei https://doaj.org/article/346555cb4758458f84fa0a4695b3e93c kostenfrei http://www.sciencedirect.com/science/article/pii/S2001037021000696 kostenfrei https://doaj.org/toc/2001-0370 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2021 1431-1444
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source	In Computational and Structural Biotechnology Journal 19(2021), Seite 1431-1444 volume:19 year:2021 pages:1431-1444
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topic_facet	Docking Pharmacophore modeling Lead optimization Structure-activity relationship Molecular modeling Biotechnology
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callnumber-first	T - Technology
author	Veronika Temml
spellingShingle	Veronika Temml misc TP248.13-248.65 misc Docking misc Pharmacophore modeling misc Lead optimization misc Structure-activity relationship misc Molecular modeling misc Biotechnology Structure-based molecular modeling in SAR analysis and lead optimization
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topic_title	TP248.13-248.65 Structure-based molecular modeling in SAR analysis and lead optimization Docking Pharmacophore modeling Lead optimization Structure-activity relationship Molecular modeling
topic	misc TP248.13-248.65 misc Docking misc Pharmacophore modeling misc Lead optimization misc Structure-activity relationship misc Molecular modeling misc Biotechnology
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title	Structure-based molecular modeling in SAR analysis and lead optimization
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title_full	Structure-based molecular modeling in SAR analysis and lead optimization
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title_sort	structure-based molecular modeling in sar analysis and lead optimization
callnumber	TP248.13-248.65
title_auth	Structure-based molecular modeling in SAR analysis and lead optimization
abstract	In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose.
abstractGer	In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose.
abstract_unstemmed	In silico methods like molecular docking and pharmacophore modeling are established strategies in lead identification. Their successful application for finding new active molecules for a target is reported by a plethora of studies. However, once a potential lead is identified, lead optimization, with the focus on improving potency, selectivity, or pharmacokinetic parameters of a parent compound, is a much more complex task. Even though in silico molecular modeling methods could contribute a lot of time and cost-saving by rationally filtering synthetic optimization options, they are employed less widely in this stage of research. In this review, we highlight studies that have successfully used computer-aided SAR analysis in lead optimization and want to showcase sound methodology and easily accessible in silico tools for this purpose.
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up_date	2024-07-03T21:41:45.306Z
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