In-Silico Pharmacodynamics
Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study...
Ausführliche Beschreibung
Autor*in: |
Vinod, P. K. [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2006 |
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Schlagwörter: |
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Anmerkung: |
© Adis Data Information BV 2006 |
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Übergeordnetes Werk: |
Enthalten in: Applied Bioinformatics - Springer International Publishing, 2004, 5(2006), 3 vom: Sept., Seite 141-150 |
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Übergeordnetes Werk: |
volume:5 ; year:2006 ; number:3 ; month:09 ; pages:141-150 |
Links: |
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DOI / URN: |
10.2165/00822942-200605030-00002 |
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10.2165/00822942-200605030-00002 doi (DE-627)SPR035648627 (SPR)00822942-200605030-00002-e DE-627 ger DE-627 rakwb eng Vinod, P. K. verfasserin aut In-Silico Pharmacodynamics 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Adis Data Information BV 2006 Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. Histamine (dpeaa)DE-He213 Cimetidine (dpeaa)DE-He213 Single Nucleotide Polymorphism (dpeaa)DE-He213 Famotidine (dpeaa)DE-He213 Quinacrine (dpeaa)DE-He213 Konkimalla, Badireenath aut Chandra, Nagasuma aut Enthalten in Applied Bioinformatics Springer International Publishing, 2004 5(2006), 3 vom: Sept., Seite 141-150 (DE-627)SPR035647698 nnns volume:5 year:2006 number:3 month:09 pages:141-150 https://dx.doi.org/10.2165/00822942-200605030-00002 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA AR 5 2006 3 09 141-150 |
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10.2165/00822942-200605030-00002 doi (DE-627)SPR035648627 (SPR)00822942-200605030-00002-e DE-627 ger DE-627 rakwb eng Vinod, P. K. verfasserin aut In-Silico Pharmacodynamics 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Adis Data Information BV 2006 Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. Histamine (dpeaa)DE-He213 Cimetidine (dpeaa)DE-He213 Single Nucleotide Polymorphism (dpeaa)DE-He213 Famotidine (dpeaa)DE-He213 Quinacrine (dpeaa)DE-He213 Konkimalla, Badireenath aut Chandra, Nagasuma aut Enthalten in Applied Bioinformatics Springer International Publishing, 2004 5(2006), 3 vom: Sept., Seite 141-150 (DE-627)SPR035647698 nnns volume:5 year:2006 number:3 month:09 pages:141-150 https://dx.doi.org/10.2165/00822942-200605030-00002 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA AR 5 2006 3 09 141-150 |
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10.2165/00822942-200605030-00002 doi (DE-627)SPR035648627 (SPR)00822942-200605030-00002-e DE-627 ger DE-627 rakwb eng Vinod, P. K. verfasserin aut In-Silico Pharmacodynamics 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Adis Data Information BV 2006 Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. Histamine (dpeaa)DE-He213 Cimetidine (dpeaa)DE-He213 Single Nucleotide Polymorphism (dpeaa)DE-He213 Famotidine (dpeaa)DE-He213 Quinacrine (dpeaa)DE-He213 Konkimalla, Badireenath aut Chandra, Nagasuma aut Enthalten in Applied Bioinformatics Springer International Publishing, 2004 5(2006), 3 vom: Sept., Seite 141-150 (DE-627)SPR035647698 nnns volume:5 year:2006 number:3 month:09 pages:141-150 https://dx.doi.org/10.2165/00822942-200605030-00002 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA AR 5 2006 3 09 141-150 |
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10.2165/00822942-200605030-00002 doi (DE-627)SPR035648627 (SPR)00822942-200605030-00002-e DE-627 ger DE-627 rakwb eng Vinod, P. K. verfasserin aut In-Silico Pharmacodynamics 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Adis Data Information BV 2006 Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. Histamine (dpeaa)DE-He213 Cimetidine (dpeaa)DE-He213 Single Nucleotide Polymorphism (dpeaa)DE-He213 Famotidine (dpeaa)DE-He213 Quinacrine (dpeaa)DE-He213 Konkimalla, Badireenath aut Chandra, Nagasuma aut Enthalten in Applied Bioinformatics Springer International Publishing, 2004 5(2006), 3 vom: Sept., Seite 141-150 (DE-627)SPR035647698 nnns volume:5 year:2006 number:3 month:09 pages:141-150 https://dx.doi.org/10.2165/00822942-200605030-00002 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA AR 5 2006 3 09 141-150 |
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10.2165/00822942-200605030-00002 doi (DE-627)SPR035648627 (SPR)00822942-200605030-00002-e DE-627 ger DE-627 rakwb eng Vinod, P. K. verfasserin aut In-Silico Pharmacodynamics 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Adis Data Information BV 2006 Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. Histamine (dpeaa)DE-He213 Cimetidine (dpeaa)DE-He213 Single Nucleotide Polymorphism (dpeaa)DE-He213 Famotidine (dpeaa)DE-He213 Quinacrine (dpeaa)DE-He213 Konkimalla, Badireenath aut Chandra, Nagasuma aut Enthalten in Applied Bioinformatics Springer International Publishing, 2004 5(2006), 3 vom: Sept., Seite 141-150 (DE-627)SPR035647698 nnns volume:5 year:2006 number:3 month:09 pages:141-150 https://dx.doi.org/10.2165/00822942-200605030-00002 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA AR 5 2006 3 09 141-150 |
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Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. © Adis Data Information BV 2006 |
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Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. © Adis Data Information BV 2006 |
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Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. The method reported here has the potential for application as a general strategy in understanding drug effects. © Adis Data Information BV 2006 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR035648627</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230519112251.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2006 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.2165/00822942-200605030-00002</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR035648627</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)00822942-200605030-00002-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Vinod, P. K.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">In-Silico Pharmacodynamics</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2006</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Adis Data Information BV 2006</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Adverse effects are exhibited by most drugs in current clinical practice, the causes for which are often not known. In this post genomic era, bioinformatics has the potential to address several issues in understanding the mechanism of drug action and in designing improved drugs. This study describes the analysis of the possible pharmacodynamic behaviour of antihistamines blocking the histamine $ H_{2} $ receptor ($ H_{2} $-antihistamines), by adopting the basic tenets of a systems biology approach. The different components that could form an appropriate sub-system are identified, thus providing a system landscape. Docking and analysis of the chosen antihistamines into each of these components resulted in identifying histamine N-methyl transferase (HNMT) as a potential unintended target for $ H_{2} $-antihistamines. Correlation with experimental data available from the literature indicates the inhibition of HNMT to be a possible cause for the adverse effects exhibited by these drugs. Implications for design of safer $ H_{2} $-antihistamines are discussed. 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