P K Vinod, Badireenath Konkimalla, Nagasuma Chandra
{"title":"计算机药效学:h2 -抗组胺药不良反应与组胺n-甲基转移酶结合电位的相关性。","authors":"P K Vinod, Badireenath Konkimalla, Nagasuma Chandra","doi":"10.2165/00822942-200605030-00002","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":87049,"journal":{"name":"Applied bioinformatics","volume":"5 3","pages":"141-50"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2165/00822942-200605030-00002","citationCount":"5","resultStr":"{\"title\":\"In-silico pharmacodynamics: correlation of adverse effects of H2-antihistamines with histamine N-methyl transferase binding potential.\",\"authors\":\"P K Vinod, Badireenath Konkimalla, Nagasuma Chandra\",\"doi\":\"10.2165/00822942-200605030-00002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":87049,\"journal\":{\"name\":\"Applied bioinformatics\",\"volume\":\"5 3\",\"pages\":\"141-50\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2165/00822942-200605030-00002\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2165/00822942-200605030-00002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2165/00822942-200605030-00002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In-silico pharmacodynamics: correlation of adverse effects of H2-antihistamines with histamine N-methyl transferase binding potential.
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.