Applying Computational Scoring Functions to Assess Biomolecular Interactions in Food Science: Applications to the Estrogen Receptors
During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now cle...
Ausführliche Beschreibung
Autor*in: |
Francesca Spyrakis [verfasserIn] Pietro Cozzini [verfasserIn] Glen Eugene Kellogg [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2016 |
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Übergeordnetes Werk: |
In: Nuclear Receptor Research - KenzPub, 2015, 3(2016), Seite 20 |
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Übergeordnetes Werk: |
volume:3 ; year:2016 ; pages:20 |
Links: |
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DOI / URN: |
10.11131/2016/101202 |
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DOAJ054110289 |
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10.11131/2016/101202 doi (DE-627)DOAJ054110289 (DE-599)DOAJ046dd3920ef94a839a725a081360f33b DE-627 ger DE-627 rakwb eng QD415-436 Francesca Spyrakis verfasserin aut Applying Computational Scoring Functions to Assess Biomolecular Interactions in Food Science: Applications to the Estrogen Receptors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. Docking Scoring Functions Computational Chemistry Nuclear Receptors Estrogen Receptors Food Science Drug Discovery Endocrine Disruptors Binding Free Energy Force Field HINT Science Q Biochemistry Pietro Cozzini verfasserin aut Glen Eugene Kellogg verfasserin aut In Nuclear Receptor Research KenzPub, 2015 3(2016), Seite 20 (DE-627)835236021 (DE-600)2834982-9 23145714 nnns volume:3 year:2016 pages:20 https://doi.org/10.11131/2016/101202 kostenfrei https://doaj.org/article/046dd3920ef94a839a725a081360f33b kostenfrei http://www.kenzpub.com/journals/nurr/2016/101202/ kostenfrei https://doaj.org/toc/2314-5714 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_74 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_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 3 2016 20 |
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10.11131/2016/101202 doi (DE-627)DOAJ054110289 (DE-599)DOAJ046dd3920ef94a839a725a081360f33b DE-627 ger DE-627 rakwb eng QD415-436 Francesca Spyrakis verfasserin aut Applying Computational Scoring Functions to Assess Biomolecular Interactions in Food Science: Applications to the Estrogen Receptors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. Docking Scoring Functions Computational Chemistry Nuclear Receptors Estrogen Receptors Food Science Drug Discovery Endocrine Disruptors Binding Free Energy Force Field HINT Science Q Biochemistry Pietro Cozzini verfasserin aut Glen Eugene Kellogg verfasserin aut In Nuclear Receptor Research KenzPub, 2015 3(2016), Seite 20 (DE-627)835236021 (DE-600)2834982-9 23145714 nnns volume:3 year:2016 pages:20 https://doi.org/10.11131/2016/101202 kostenfrei https://doaj.org/article/046dd3920ef94a839a725a081360f33b kostenfrei http://www.kenzpub.com/journals/nurr/2016/101202/ kostenfrei https://doaj.org/toc/2314-5714 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_74 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_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 3 2016 20 |
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10.11131/2016/101202 doi (DE-627)DOAJ054110289 (DE-599)DOAJ046dd3920ef94a839a725a081360f33b DE-627 ger DE-627 rakwb eng QD415-436 Francesca Spyrakis verfasserin aut Applying Computational Scoring Functions to Assess Biomolecular Interactions in Food Science: Applications to the Estrogen Receptors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. Docking Scoring Functions Computational Chemistry Nuclear Receptors Estrogen Receptors Food Science Drug Discovery Endocrine Disruptors Binding Free Energy Force Field HINT Science Q Biochemistry Pietro Cozzini verfasserin aut Glen Eugene Kellogg verfasserin aut In Nuclear Receptor Research KenzPub, 2015 3(2016), Seite 20 (DE-627)835236021 (DE-600)2834982-9 23145714 nnns volume:3 year:2016 pages:20 https://doi.org/10.11131/2016/101202 kostenfrei https://doaj.org/article/046dd3920ef94a839a725a081360f33b kostenfrei http://www.kenzpub.com/journals/nurr/2016/101202/ kostenfrei https://doaj.org/toc/2314-5714 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_74 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_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 3 2016 20 |
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10.11131/2016/101202 doi (DE-627)DOAJ054110289 (DE-599)DOAJ046dd3920ef94a839a725a081360f33b DE-627 ger DE-627 rakwb eng QD415-436 Francesca Spyrakis verfasserin aut Applying Computational Scoring Functions to Assess Biomolecular Interactions in Food Science: Applications to the Estrogen Receptors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. Docking Scoring Functions Computational Chemistry Nuclear Receptors Estrogen Receptors Food Science Drug Discovery Endocrine Disruptors Binding Free Energy Force Field HINT Science Q Biochemistry Pietro Cozzini verfasserin aut Glen Eugene Kellogg verfasserin aut In Nuclear Receptor Research KenzPub, 2015 3(2016), Seite 20 (DE-627)835236021 (DE-600)2834982-9 23145714 nnns volume:3 year:2016 pages:20 https://doi.org/10.11131/2016/101202 kostenfrei https://doaj.org/article/046dd3920ef94a839a725a081360f33b kostenfrei http://www.kenzpub.com/journals/nurr/2016/101202/ kostenfrei https://doaj.org/toc/2314-5714 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_74 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_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 3 2016 20 |
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abstract |
During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. |
abstractGer |
During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. |
abstract_unstemmed |
During the last decade, computational methods, which were for the most part developed to study protein-ligand interactions and especially to discover, design and develop drugs by and for medicinal chemists, have been successfully applied in a variety of food science applications [1,2]. It is now clear, in fact, that drugs and nutritional molecules behave in the same way when binding to a macromolecular target or receptor, and that many of the approaches used so extensively in medicinal chemistry can be easily transferred to the fields of food science. For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3,4,5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity. We describe here the energetics of binding of biological complexes, providing a survey of the most common and successful algorithms used in evaluating these energetics, and we report case studies in which computational techniques have been applied to food science issues. In particular, we explore a handful of studies involving the estrogen receptors for which we have a long-term interest. |
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