Predicting Human Serum Albumin Affinity of Interleukin-8 (CXCL8) Inhibitors by 3D-QSPR Approach
A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of huma...
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Veröffentlicht in: | Journal of medicinal chemistry 2005-04, Vol.48 (7), p.2469-2479 |
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container_title | Journal of medicinal chemistry |
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creator | Aureli, Loretta Cruciani, Gabriele Cesta, Maria Candida Anacardio, Roberto De Simone, Lucio Moriconi, Alessio |
description | A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure−property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K i) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds. |
doi_str_mv | 10.1021/jm049227l |
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These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure−property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K i) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.</description><identifier>ISSN: 0022-2623</identifier><identifier>EISSN: 1520-4804</identifier><identifier>DOI: 10.1021/jm049227l</identifier><identifier>PMID: 15801837</identifier><identifier>CODEN: JMCMAR</identifier><language>eng</language><publisher>Washington, DC: American Chemical Society</publisher><subject>Anti-Inflammatory Agents, Non-Steroidal - chemistry ; Binding Sites ; Biological and medical sciences ; Bones, joints and connective tissue. Antiinflammatory agents ; Chemical Phenomena ; Chemistry, Physical ; Humans ; In Vitro Techniques ; Interleukin-8 - antagonists & inhibitors ; Interleukin-8 - chemistry ; Medical sciences ; Models, Molecular ; Pharmacology. Drug treatments ; Phenylpropionates - blood ; Phenylpropionates - chemistry ; Protein Binding ; Quantitative Structure-Activity Relationship ; Serum Albumin - chemistry ; Serum Albumin - metabolism ; Stereoisomerism</subject><ispartof>Journal of medicinal chemistry, 2005-04, Vol.48 (7), p.2469-2479</ispartof><rights>Copyright © 2005 American Chemical Society</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a447t-597f95c4e588a5be3d1181af5590686b74ffc65776e3e1fffcab44373d2860503</citedby><cites>FETCH-LOGICAL-a447t-597f95c4e588a5be3d1181af5590686b74ffc65776e3e1fffcab44373d2860503</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/jm049227l$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/jm049227l$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,776,780,2752,27053,27901,27902,56713,56763</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16680593$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15801837$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Aureli, Loretta</creatorcontrib><creatorcontrib>Cruciani, Gabriele</creatorcontrib><creatorcontrib>Cesta, Maria Candida</creatorcontrib><creatorcontrib>Anacardio, Roberto</creatorcontrib><creatorcontrib>De Simone, Lucio</creatorcontrib><creatorcontrib>Moriconi, Alessio</creatorcontrib><title>Predicting Human Serum Albumin Affinity of Interleukin-8 (CXCL8) Inhibitors by 3D-QSPR Approach</title><title>Journal of medicinal chemistry</title><addtitle>J. Med. Chem</addtitle><description>A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure−property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K i) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.</description><subject>Anti-Inflammatory Agents, Non-Steroidal - chemistry</subject><subject>Binding Sites</subject><subject>Biological and medical sciences</subject><subject>Bones, joints and connective tissue. Antiinflammatory agents</subject><subject>Chemical Phenomena</subject><subject>Chemistry, Physical</subject><subject>Humans</subject><subject>In Vitro Techniques</subject><subject>Interleukin-8 - antagonists & inhibitors</subject><subject>Interleukin-8 - chemistry</subject><subject>Medical sciences</subject><subject>Models, Molecular</subject><subject>Pharmacology. Drug treatments</subject><subject>Phenylpropionates - blood</subject><subject>Phenylpropionates - chemistry</subject><subject>Protein Binding</subject><subject>Quantitative Structure-Activity Relationship</subject><subject>Serum Albumin - chemistry</subject><subject>Serum Albumin - metabolism</subject><subject>Stereoisomerism</subject><issn>0022-2623</issn><issn>1520-4804</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpt0M1qGzEUBWBRWhon7SIvULRpSRbT6F-apXFbJ2CoU7uQndDIUiNnRuNKMxC_fRVs4k1XQrofR5cDwCVGXzEi-GbbIVYTIts3YII5QRVTiL0FE4QIqYgg9Ayc57xFCFFM6HtwhrlCWFE5AXqZ3CbYIcQ_8HbsTIQrl8YOTttm7EKEU-9DDMMe9h7excGl1o1PIVYKXs0eZgt1XV4fQxOGPmXY7CH9Vt2vlr_gdLdLvbGPH8A7b9rsPh7PC_D7x_f17LZa_JzfzaaLyjAmh4rX0tfcMseVMrxxdIOxwsZzXiOhRCOZ91ZwKYWjDvtyMQ1jVNINUQJxRC_Al0Nu-fbv6PKgu5Cta1sTXT9mLSSXRBJR4PUB2tTnnJzXuxQ6k_YaI_3Spn5ts9hPx9Cx6dzmJI_1FfD5CEy2pvXJRBvyyQmhEK9pcdXBhTy459e5SU9lMSq5Xi9Xek6QYnQ91-KUa2zW235MsXT3nwX_Ae1nlNQ</recordid><startdate>20050407</startdate><enddate>20050407</enddate><creator>Aureli, Loretta</creator><creator>Cruciani, Gabriele</creator><creator>Cesta, Maria Candida</creator><creator>Anacardio, Roberto</creator><creator>De Simone, Lucio</creator><creator>Moriconi, Alessio</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>7X8</scope></search><sort><creationdate>20050407</creationdate><title>Predicting Human Serum Albumin Affinity of Interleukin-8 (CXCL8) Inhibitors by 3D-QSPR Approach</title><author>Aureli, Loretta ; Cruciani, Gabriele ; Cesta, Maria Candida ; Anacardio, Roberto ; De Simone, Lucio ; Moriconi, Alessio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a447t-597f95c4e588a5be3d1181af5590686b74ffc65776e3e1fffcab44373d2860503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Anti-Inflammatory Agents, Non-Steroidal - chemistry</topic><topic>Binding Sites</topic><topic>Biological and medical sciences</topic><topic>Bones, joints and connective tissue. Antiinflammatory agents</topic><topic>Chemical Phenomena</topic><topic>Chemistry, Physical</topic><topic>Humans</topic><topic>In Vitro Techniques</topic><topic>Interleukin-8 - antagonists & inhibitors</topic><topic>Interleukin-8 - chemistry</topic><topic>Medical sciences</topic><topic>Models, Molecular</topic><topic>Pharmacology. Drug treatments</topic><topic>Phenylpropionates - blood</topic><topic>Phenylpropionates - chemistry</topic><topic>Protein Binding</topic><topic>Quantitative Structure-Activity Relationship</topic><topic>Serum Albumin - chemistry</topic><topic>Serum Albumin - metabolism</topic><topic>Stereoisomerism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aureli, Loretta</creatorcontrib><creatorcontrib>Cruciani, Gabriele</creatorcontrib><creatorcontrib>Cesta, Maria Candida</creatorcontrib><creatorcontrib>Anacardio, Roberto</creatorcontrib><creatorcontrib>De Simone, Lucio</creatorcontrib><creatorcontrib>Moriconi, Alessio</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of medicinal chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aureli, Loretta</au><au>Cruciani, Gabriele</au><au>Cesta, Maria Candida</au><au>Anacardio, Roberto</au><au>De Simone, Lucio</au><au>Moriconi, Alessio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting Human Serum Albumin Affinity of Interleukin-8 (CXCL8) Inhibitors by 3D-QSPR Approach</atitle><jtitle>Journal of medicinal chemistry</jtitle><addtitle>J. Med. Chem</addtitle><date>2005-04-07</date><risdate>2005</risdate><volume>48</volume><issue>7</issue><spage>2469</spage><epage>2479</epage><pages>2469-2479</pages><issn>0022-2623</issn><eissn>1520-4804</eissn><coden>JMCMAR</coden><abstract>A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure−property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K i) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.</abstract><cop>Washington, DC</cop><pub>American Chemical Society</pub><pmid>15801837</pmid><doi>10.1021/jm049227l</doi><tpages>11</tpages></addata></record> |
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subjects | Anti-Inflammatory Agents, Non-Steroidal - chemistry Binding Sites Biological and medical sciences Bones, joints and connective tissue. Antiinflammatory agents Chemical Phenomena Chemistry, Physical Humans In Vitro Techniques Interleukin-8 - antagonists & inhibitors Interleukin-8 - chemistry Medical sciences Models, Molecular Pharmacology. Drug treatments Phenylpropionates - blood Phenylpropionates - chemistry Protein Binding Quantitative Structure-Activity Relationship Serum Albumin - chemistry Serum Albumin - metabolism Stereoisomerism |
title | Predicting Human Serum Albumin Affinity of Interleukin-8 (CXCL8) Inhibitors by 3D-QSPR Approach |
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