In Silico Prediction of Cytochrome P450 2D6 and 3A4 Inhibition Using Gaussian Kernel Weighted k-Nearest Neighbor and Extended Connectivity Fingerprints, Including Structural Fragment Analysis of Inhibitors versus Noninhibitors
Inhibition of cytochrome P450 (CYP) enzymes is unwanted because of the risk of severe side effects due to drug−drug interactions. We present two in silico Gaussian kernel weighted k-nearest neighbor models based on extended connectivity fingerprints that classify CYP2D6 and CYP3A4 inhibition. Data u...
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| Veröffentlicht in: | Journal of medicinal chemistry 2007-02, Vol.50 (3), p.501-511 |
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| creator | Jensen, Berith F Vind, Christian Brockhoff, Per B Refsgaard, Hanne H. F |
| description | Inhibition of cytochrome P450 (CYP) enzymes is unwanted because of the risk of severe side effects due to drug−drug interactions. We present two in silico Gaussian kernel weighted k-nearest neighbor models based on extended connectivity fingerprints that classify CYP2D6 and CYP3A4 inhibition. Data used for modeling consisted of diverse sets of 1153 and 1382 drug candidates tested for CYP2D6 and CYP3A4 inhibition in human liver microsomes. For CYP2D6, 82% of the classified test set compounds were predicted to the correct class. For CYP3A4, 88% of the classified compounds were correctly classified. CYP2D6 and CYP3A4 inhibition were additionally classified for an external test set on 14 drugs, and multidimensional scaling plots showed that the drugs in the external test set were in the periphery of the training sets. Furthermore, fragment analyses were performed and structural fragments frequent in CYP2D6 and CYP3A4 inhibitors and noninhibitors are presented. |
| doi_str_mv | 10.1021/jm060333s |
| format | Article |
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Furthermore, fragment analyses were performed and structural fragments frequent in CYP2D6 and CYP3A4 inhibitors and noninhibitors are presented.</description><identifier>ISSN: 0022-2623</identifier><identifier>EISSN: 1520-4804</identifier><identifier>DOI: 10.1021/jm060333s</identifier><identifier>PMID: 17266202</identifier><identifier>CODEN: JMCMAR</identifier><language>eng</language><publisher>Washington, DC: American Chemical Society</publisher><subject>Biological and medical sciences ; Cluster Analysis ; Cytochrome P-450 CYP2D6 - chemistry ; Cytochrome P-450 CYP2D6 Inhibitors ; Cytochrome P-450 CYP3A ; Cytochrome P-450 Enzyme Inhibitors ; Cytochrome P-450 Enzyme System - chemistry ; Databases, Factual ; Enzyme Inhibitors - chemistry ; Humans ; In Vitro Techniques ; Medical sciences ; Microsomes, Liver - drug effects ; Microsomes, Liver - enzymology ; Miscellaneous ; Models, Molecular ; Pharmaceutical Preparations - chemistry ; Pharmacology. 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F</creatorcontrib><title>In Silico Prediction of Cytochrome P450 2D6 and 3A4 Inhibition Using Gaussian Kernel Weighted k-Nearest Neighbor and Extended Connectivity Fingerprints, Including Structural Fragment Analysis of Inhibitors versus Noninhibitors</title><title>Journal of medicinal chemistry</title><addtitle>J. Med. Chem</addtitle><description>Inhibition of cytochrome P450 (CYP) enzymes is unwanted because of the risk of severe side effects due to drug−drug interactions. We present two in silico Gaussian kernel weighted k-nearest neighbor models based on extended connectivity fingerprints that classify CYP2D6 and CYP3A4 inhibition. Data used for modeling consisted of diverse sets of 1153 and 1382 drug candidates tested for CYP2D6 and CYP3A4 inhibition in human liver microsomes. For CYP2D6, 82% of the classified test set compounds were predicted to the correct class. For CYP3A4, 88% of the classified compounds were correctly classified. CYP2D6 and CYP3A4 inhibition were additionally classified for an external test set on 14 drugs, and multidimensional scaling plots showed that the drugs in the external test set were in the periphery of the training sets. Furthermore, fragment analyses were performed and structural fragments frequent in CYP2D6 and CYP3A4 inhibitors and noninhibitors are presented.</description><subject>Biological and medical sciences</subject><subject>Cluster Analysis</subject><subject>Cytochrome P-450 CYP2D6 - chemistry</subject><subject>Cytochrome P-450 CYP2D6 Inhibitors</subject><subject>Cytochrome P-450 CYP3A</subject><subject>Cytochrome P-450 Enzyme Inhibitors</subject><subject>Cytochrome P-450 Enzyme System - chemistry</subject><subject>Databases, Factual</subject><subject>Enzyme Inhibitors - chemistry</subject><subject>Humans</subject><subject>In Vitro Techniques</subject><subject>Medical sciences</subject><subject>Microsomes, Liver - drug effects</subject><subject>Microsomes, Liver - enzymology</subject><subject>Miscellaneous</subject><subject>Models, Molecular</subject><subject>Pharmaceutical Preparations - chemistry</subject><subject>Pharmacology. Drug treatments</subject><subject>Quantitative Structure-Activity Relationship</subject><issn>0022-2623</issn><issn>1520-4804</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkV9v0zAUxSMEYmXwwBdAfgEJiYD_xUkeu24tFVUpdBOPkePctO4Se9jOtH5dPgnJWnUvSLzY0r0_nXPsE0VvCf5MMCVfdi0WmDHmn0UjklAc8wzz59EIY0pjKig7i155v8MYM0LZy-iMpFQIiuko-jM3aK0brSxaOai0CtoaZGs02Qerts62gFY8wYheCiRNhdiYo7nZ6lI_kjdemw2ayc57LQ36Bs5Ag36B3mwDVOg2XoJ04ANaDqPSukeRq4cApur3E2sM9J73OuzRtJcCd-e0Cf5Tb6KarhrU18F1KnRONmjq5KYFE9DYyGbvtR-iHuNY59E9ON95tLRGn4avoxe1bDy8Od7n0c306nryNV58n80n40UseZqFWCREVRgIV0wAplApTrDIs7qsUp7VLJdlSbGoJMtpkmbDCYLUmUw4BZCcnUcfDrp3zv7u-jcXrfYKmkYasJ0vRJYLnojsvyDJ04SSZAA_HkDlrPcO6qL_nFa6fUFwMTRfnJrv2XdH0a5soXoij1X3wPsjIL2STe2kUdo_cdngyUXPxQdO-wAPp710t4VIWZoU16t18eMy-blYX-TF7ElXKl_sbOf6Zvw_Av4FevnUWg</recordid><startdate>20070208</startdate><enddate>20070208</enddate><creator>Jensen, Berith F</creator><creator>Vind, Christian</creator><creator>Brockhoff, Per B</creator><creator>Refsgaard, Hanne H. F</creator><general>American Chemical Society</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20070208</creationdate><title>In Silico Prediction of Cytochrome P450 2D6 and 3A4 Inhibition Using Gaussian Kernel Weighted k-Nearest Neighbor and Extended Connectivity Fingerprints, Including Structural Fragment Analysis of Inhibitors versus Noninhibitors</title><author>Jensen, Berith F ; Vind, Christian ; Brockhoff, Per B ; Refsgaard, Hanne H. F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a478t-651cd0e14c36e02edc410698fbd748f39abb206da3925783925e61f8a542eea43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Biological and medical sciences</topic><topic>Cluster Analysis</topic><topic>Cytochrome P-450 CYP2D6 - chemistry</topic><topic>Cytochrome P-450 CYP2D6 Inhibitors</topic><topic>Cytochrome P-450 CYP3A</topic><topic>Cytochrome P-450 Enzyme Inhibitors</topic><topic>Cytochrome P-450 Enzyme System - chemistry</topic><topic>Databases, Factual</topic><topic>Enzyme Inhibitors - chemistry</topic><topic>Humans</topic><topic>In Vitro Techniques</topic><topic>Medical sciences</topic><topic>Microsomes, Liver - drug effects</topic><topic>Microsomes, Liver - enzymology</topic><topic>Miscellaneous</topic><topic>Models, Molecular</topic><topic>Pharmaceutical Preparations - chemistry</topic><topic>Pharmacology. Drug treatments</topic><topic>Quantitative Structure-Activity Relationship</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jensen, Berith F</creatorcontrib><creatorcontrib>Vind, Christian</creatorcontrib><creatorcontrib>Brockhoff, Per B</creatorcontrib><creatorcontrib>Refsgaard, Hanne H. 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| subjects | Biological and medical sciences Cluster Analysis Cytochrome P-450 CYP2D6 - chemistry Cytochrome P-450 CYP2D6 Inhibitors Cytochrome P-450 CYP3A Cytochrome P-450 Enzyme Inhibitors Cytochrome P-450 Enzyme System - chemistry Databases, Factual Enzyme Inhibitors - chemistry Humans In Vitro Techniques Medical sciences Microsomes, Liver - drug effects Microsomes, Liver - enzymology Miscellaneous Models, Molecular Pharmaceutical Preparations - chemistry Pharmacology. Drug treatments Quantitative Structure-Activity Relationship |
| title | In Silico Prediction of Cytochrome P450 2D6 and 3A4 Inhibition Using Gaussian Kernel Weighted k-Nearest Neighbor and Extended Connectivity Fingerprints, Including Structural Fragment Analysis of Inhibitors versus Noninhibitors |
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