Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics

Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with th...
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Autor*in:	Tamra C. Blue [verfasserIn] Katherine M. Davis [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	radical SAM enzymes dynamics computational DFT MD docking

Übergeordnetes Werk:	In: Molecules - MDPI AG, 2003, 26(2021), 9, p 2590
Übergeordnetes Werk:	volume:26 ; year:2021 ; number:9, p 2590

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/molecules26092590

Katalog-ID:	DOAJ073718998

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520			\|a Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover.
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allfields	10.3390/molecules26092590 doi (DE-627)DOAJ073718998 (DE-599)DOAJ47228fd706b14115926848a283541626 DE-627 ger DE-627 rakwb eng QD241-441 Tamra C. Blue verfasserin aut Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover. radical SAM enzymes dynamics computational DFT MD docking Organic chemistry Katherine M. Davis verfasserin aut In Molecules MDPI AG, 2003 26(2021), 9, p 2590 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:9, p 2590 https://doi.org/10.3390/molecules26092590 kostenfrei https://doaj.org/article/47228fd706b14115926848a283541626 kostenfrei https://www.mdpi.com/1420-3049/26/9/2590 kostenfrei https://doaj.org/toc/1420-3049 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_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 26 2021 9, p 2590
spelling	10.3390/molecules26092590 doi (DE-627)DOAJ073718998 (DE-599)DOAJ47228fd706b14115926848a283541626 DE-627 ger DE-627 rakwb eng QD241-441 Tamra C. Blue verfasserin aut Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover. radical SAM enzymes dynamics computational DFT MD docking Organic chemistry Katherine M. Davis verfasserin aut In Molecules MDPI AG, 2003 26(2021), 9, p 2590 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:9, p 2590 https://doi.org/10.3390/molecules26092590 kostenfrei https://doaj.org/article/47228fd706b14115926848a283541626 kostenfrei https://www.mdpi.com/1420-3049/26/9/2590 kostenfrei https://doaj.org/toc/1420-3049 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_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 26 2021 9, p 2590
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allfieldsGer	10.3390/molecules26092590 doi (DE-627)DOAJ073718998 (DE-599)DOAJ47228fd706b14115926848a283541626 DE-627 ger DE-627 rakwb eng QD241-441 Tamra C. Blue verfasserin aut Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover. radical SAM enzymes dynamics computational DFT MD docking Organic chemistry Katherine M. Davis verfasserin aut In Molecules MDPI AG, 2003 26(2021), 9, p 2590 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:9, p 2590 https://doi.org/10.3390/molecules26092590 kostenfrei https://doaj.org/article/47228fd706b14115926848a283541626 kostenfrei https://www.mdpi.com/1420-3049/26/9/2590 kostenfrei https://doaj.org/toc/1420-3049 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_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 26 2021 9, p 2590
allfieldsSound	10.3390/molecules26092590 doi (DE-627)DOAJ073718998 (DE-599)DOAJ47228fd706b14115926848a283541626 DE-627 ger DE-627 rakwb eng QD241-441 Tamra C. Blue verfasserin aut Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover. radical SAM enzymes dynamics computational DFT MD docking Organic chemistry Katherine M. Davis verfasserin aut In Molecules MDPI AG, 2003 26(2021), 9, p 2590 (DE-627)311313132 (DE-600)2008644-1 14203049 nnns volume:26 year:2021 number:9, p 2590 https://doi.org/10.3390/molecules26092590 kostenfrei https://doaj.org/article/47228fd706b14115926848a283541626 kostenfrei https://www.mdpi.com/1420-3049/26/9/2590 kostenfrei https://doaj.org/toc/1420-3049 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_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 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 26 2021 9, p 2590
language	English
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callnumber-first	Q - Science
author	Tamra C. Blue
spellingShingle	Tamra C. Blue misc QD241-441 misc radical SAM enzymes misc dynamics misc computational misc DFT misc MD misc docking misc Organic chemistry Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
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topic_title	QD241-441 Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics radical SAM enzymes dynamics computational DFT MD docking
topic	misc QD241-441 misc radical SAM enzymes misc dynamics misc computational misc DFT misc MD misc docking misc Organic chemistry
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title	Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
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title_sort	computational approaches: an underutilized tool in the quest to elucidate radical sam dynamics
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title_auth	Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
abstract	Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover.
abstractGer	Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover.
abstract_unstemmed	Enzymes are biological catalysts whose dynamics enable their reactivity. Visualizing conformational changes, in particular, is technically challenging, and little is known about these crucial atomic motions. This is especially problematic for understanding the functional diversity associated with the radical <i<S</i<-adenosyl-L-methionine (SAM) superfamily whose members share a common radical mechanism but ultimately catalyze a broad range of challenging reactions. Computational chemistry approaches provide a readily accessible alternative to exploring the time-resolved behavior of these enzymes that is not limited by experimental logistics. Here, we review the application of molecular docking, molecular dynamics, and density functional theory, as well as hybrid quantum mechanics/molecular mechanics methods to the study of these enzymes, with a focus on understanding the mechanistic dynamics associated with turnover.
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title_short	Computational Approaches: An Underutilized Tool in the Quest to Elucidate Radical SAM Dynamics
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