In silico simulations of STAT1 and STAT3 inhibitors predict SH2 domain cross-binding specificity
Signal transducers and activators of transcription (STATs) comprise a family of transcription factors that are structurally related and which participate in signaling pathways activated by cytokines, growth factors and pathogens. Activation of STAT proteins is mediated by the highly conserved Src ho...
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Veröffentlicht in: | European journal of pharmacology 2013-11, Vol.720 (1-3), p.38-48 |
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description | Signal transducers and activators of transcription (STATs) comprise a family of transcription factors that are structurally related and which participate in signaling pathways activated by cytokines, growth factors and pathogens. Activation of STAT proteins is mediated by the highly conserved Src homology 2 (SH2) domain, which interacts with phosphotyrosine motifs for specific contacts between STATs and receptors and for STAT dimerization. By generating new models for human (h)STAT1, hSTAT2 and hSTAT3 we applied comparative in silico docking to determine SH2-binding specificity of the STAT3 inhibitor stattic, and of fludarabine (STAT1 inhibitor). Thus, we provide evidence that by primarily targeting the highly conserved phosphotyrosine (pY+0) SH2 binding pocket stattic is not a specific hSTAT3 inhibitor, but is equally effective towards hSTAT1 and hSTAT2. This was confirmed in Human Micro-vascular Endothelial Cells (HMECs) in vitro, in which stattic inhibited interferon-α-induced phosphorylation of all three STATs. Likewise, fludarabine inhibits both hSTAT1 and hSTAT3 phosphorylation, but not hSTAT2, by competing with the highly conserved pY+0 and pY-X binding sites, which are less well-preserved in hSTAT2. Moreover we observed that in HMECs in vitro fludarabine inhibits cytokine and lipopolysaccharide-induced phosphorylation of hSTAT1 and hSTAT3 but does not affect hSTAT2. Finally, multiple sequence alignment of STAT-SH2 domain sequences confirmed high conservation between hSTAT1 and hSTAT3, but not hSTAT2, with respect to stattic and fludarabine binding sites. Together our data offer a molecular basis that explains STAT cross-binding specificity of stattic and fludarabine, thereby questioning the present selection strategies of SH2 domain-based competitive small inhibitors.
High conservation of small-inhibitor binding sites – pY+0, pY+1 and pY-X in the SH2 domain of STAT1 determines STAT cross-binding specificity. [Display omitted] |
doi_str_mv | 10.1016/j.ejphar.2013.10.055 |
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High conservation of small-inhibitor binding sites – pY+0, pY+1 and pY-X in the SH2 domain of STAT1 determines STAT cross-binding specificity. [Display omitted]</description><identifier>ISSN: 0014-2999</identifier><identifier>EISSN: 1879-0712</identifier><identifier>DOI: 10.1016/j.ejphar.2013.10.055</identifier><identifier>PMID: 24211327</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Amino Acid Sequence ; Binding Sites ; Binding specificity ; Cells, Cultured ; Computer Simulation ; Cyclic S-Oxides - pharmacology ; cytokines ; dimerization ; Drug validation ; endothelial cells ; Endothelial Cells - drug effects ; Endothelial Cells - metabolism ; growth factors ; Humans ; Interferon-alpha - pharmacology ; Interferon-gamma - pharmacology ; Molecular Docking Simulation ; Molecular Sequence Data ; pathogens ; pharmacology ; phosphorylation ; Phosphorylation - drug effects ; Protein Binding ; receptors ; Sequence Alignment ; signal transduction ; src Homology Domains ; STAT-SH2 inhibitors ; STAT-SH2 modeling ; STAT1 Transcription Factor - antagonists & inhibitors ; STAT1 Transcription Factor - metabolism ; STAT2 Transcription Factor - antagonists & inhibitors ; STAT2 Transcription Factor - metabolism ; STAT3 Transcription Factor - antagonists & inhibitors ; STAT3 Transcription Factor - metabolism ; transcription factors ; Vidarabine - analogs & derivatives ; Vidarabine - pharmacology</subject><ispartof>European journal of pharmacology, 2013-11, Vol.720 (1-3), p.38-48</ispartof><rights>2013 Elsevier B.V.</rights><rights>2013 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c452t-bcaab52aeb22a0979a3067dba9ad99a27c2aa68dd66f0533aff94281bff820a23</citedby><cites>FETCH-LOGICAL-c452t-bcaab52aeb22a0979a3067dba9ad99a27c2aa68dd66f0533aff94281bff820a23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ejphar.2013.10.055$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27911,27912,45982</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24211327$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Szelag, Malgorzata</creatorcontrib><creatorcontrib>Sikorski, Krzysztof</creatorcontrib><creatorcontrib>Czerwoniec, Anna</creatorcontrib><creatorcontrib>Szatkowska, Katarzyna</creatorcontrib><creatorcontrib>Wesoly, Joanna</creatorcontrib><creatorcontrib>Bluyssen, Hans A.R.</creatorcontrib><title>In silico simulations of STAT1 and STAT3 inhibitors predict SH2 domain cross-binding specificity</title><title>European journal of pharmacology</title><addtitle>Eur J Pharmacol</addtitle><description>Signal transducers and activators of transcription (STATs) comprise a family of transcription factors that are structurally related and which participate in signaling pathways activated by cytokines, growth factors and pathogens. Activation of STAT proteins is mediated by the highly conserved Src homology 2 (SH2) domain, which interacts with phosphotyrosine motifs for specific contacts between STATs and receptors and for STAT dimerization. By generating new models for human (h)STAT1, hSTAT2 and hSTAT3 we applied comparative in silico docking to determine SH2-binding specificity of the STAT3 inhibitor stattic, and of fludarabine (STAT1 inhibitor). Thus, we provide evidence that by primarily targeting the highly conserved phosphotyrosine (pY+0) SH2 binding pocket stattic is not a specific hSTAT3 inhibitor, but is equally effective towards hSTAT1 and hSTAT2. This was confirmed in Human Micro-vascular Endothelial Cells (HMECs) in vitro, in which stattic inhibited interferon-α-induced phosphorylation of all three STATs. Likewise, fludarabine inhibits both hSTAT1 and hSTAT3 phosphorylation, but not hSTAT2, by competing with the highly conserved pY+0 and pY-X binding sites, which are less well-preserved in hSTAT2. Moreover we observed that in HMECs in vitro fludarabine inhibits cytokine and lipopolysaccharide-induced phosphorylation of hSTAT1 and hSTAT3 but does not affect hSTAT2. Finally, multiple sequence alignment of STAT-SH2 domain sequences confirmed high conservation between hSTAT1 and hSTAT3, but not hSTAT2, with respect to stattic and fludarabine binding sites. Together our data offer a molecular basis that explains STAT cross-binding specificity of stattic and fludarabine, thereby questioning the present selection strategies of SH2 domain-based competitive small inhibitors.
High conservation of small-inhibitor binding sites – pY+0, pY+1 and pY-X in the SH2 domain of STAT1 determines STAT cross-binding specificity. [Display omitted]</description><subject>Amino Acid Sequence</subject><subject>Binding Sites</subject><subject>Binding specificity</subject><subject>Cells, Cultured</subject><subject>Computer Simulation</subject><subject>Cyclic S-Oxides - pharmacology</subject><subject>cytokines</subject><subject>dimerization</subject><subject>Drug validation</subject><subject>endothelial cells</subject><subject>Endothelial Cells - drug effects</subject><subject>Endothelial Cells - metabolism</subject><subject>growth factors</subject><subject>Humans</subject><subject>Interferon-alpha - pharmacology</subject><subject>Interferon-gamma - pharmacology</subject><subject>Molecular Docking Simulation</subject><subject>Molecular Sequence Data</subject><subject>pathogens</subject><subject>pharmacology</subject><subject>phosphorylation</subject><subject>Phosphorylation - drug effects</subject><subject>Protein Binding</subject><subject>receptors</subject><subject>Sequence Alignment</subject><subject>signal transduction</subject><subject>src Homology Domains</subject><subject>STAT-SH2 inhibitors</subject><subject>STAT-SH2 modeling</subject><subject>STAT1 Transcription Factor - antagonists & inhibitors</subject><subject>STAT1 Transcription Factor - metabolism</subject><subject>STAT2 Transcription Factor - antagonists & inhibitors</subject><subject>STAT2 Transcription Factor - metabolism</subject><subject>STAT3 Transcription Factor - antagonists & inhibitors</subject><subject>STAT3 Transcription Factor - metabolism</subject><subject>transcription factors</subject><subject>Vidarabine - analogs & derivatives</subject><subject>Vidarabine - pharmacology</subject><issn>0014-2999</issn><issn>1879-0712</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1v1DAQhi0EotvCP0DgI5cstmMn8QWpqqCtVInDbs9m4o92Vkkc7CxS_z3epnDkNKPRMzOvHkI-cLbljDdfDlt_mB8hbQXjdRltmVKvyIZ3ra5Yy8VrsmGMy0porc_Iec4HxpjSQr0lZ0IKzmvRbsjP24lmHNDGUsbjAAvGKdMY6G5_uecUJvfc1RSnR-xxiSnTOXmHdqG7G0FdHAEnalPMuepxcjg90Dx7iwEtLk_vyJsAQ_bvX-oFuf_-bX91U939uL69uryrrFRiqXoL0CsBvhcCmG411KxpXQ8anNYgWisAms65pglM1TWEoKXoeB9CJxiI-oJ8Xu_OKf46-ryYEbP1wwCTj8dsuGyk1IJ3qqByRZ9DJx_MnHCE9GQ4Mye35mBWt-bk9jQtbsvax5cPx3707t_SX5kF-LQCAaKBh4TZ3O_KBVXES962XSG-roQvJn6jTyZb9JMtOpO3i3ER_5_hD9xGlZg</recordid><startdate>20131115</startdate><enddate>20131115</enddate><creator>Szelag, Malgorzata</creator><creator>Sikorski, Krzysztof</creator><creator>Czerwoniec, Anna</creator><creator>Szatkowska, Katarzyna</creator><creator>Wesoly, Joanna</creator><creator>Bluyssen, Hans A.R.</creator><general>Elsevier B.V</general><scope>FBQ</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>20131115</creationdate><title>In silico simulations of STAT1 and STAT3 inhibitors predict SH2 domain cross-binding specificity</title><author>Szelag, Malgorzata ; Sikorski, Krzysztof ; Czerwoniec, Anna ; Szatkowska, Katarzyna ; Wesoly, Joanna ; Bluyssen, Hans A.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c452t-bcaab52aeb22a0979a3067dba9ad99a27c2aa68dd66f0533aff94281bff820a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Amino Acid Sequence</topic><topic>Binding Sites</topic><topic>Binding specificity</topic><topic>Cells, Cultured</topic><topic>Computer Simulation</topic><topic>Cyclic S-Oxides - pharmacology</topic><topic>cytokines</topic><topic>dimerization</topic><topic>Drug validation</topic><topic>endothelial cells</topic><topic>Endothelial Cells - drug effects</topic><topic>Endothelial Cells - metabolism</topic><topic>growth factors</topic><topic>Humans</topic><topic>Interferon-alpha - pharmacology</topic><topic>Interferon-gamma - pharmacology</topic><topic>Molecular Docking Simulation</topic><topic>Molecular Sequence Data</topic><topic>pathogens</topic><topic>pharmacology</topic><topic>phosphorylation</topic><topic>Phosphorylation - drug effects</topic><topic>Protein Binding</topic><topic>receptors</topic><topic>Sequence Alignment</topic><topic>signal transduction</topic><topic>src Homology Domains</topic><topic>STAT-SH2 inhibitors</topic><topic>STAT-SH2 modeling</topic><topic>STAT1 Transcription Factor - antagonists & inhibitors</topic><topic>STAT1 Transcription Factor - metabolism</topic><topic>STAT2 Transcription Factor - antagonists & inhibitors</topic><topic>STAT2 Transcription Factor - metabolism</topic><topic>STAT3 Transcription Factor - antagonists & inhibitors</topic><topic>STAT3 Transcription Factor - metabolism</topic><topic>transcription factors</topic><topic>Vidarabine - analogs & derivatives</topic><topic>Vidarabine - pharmacology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Szelag, Malgorzata</creatorcontrib><creatorcontrib>Sikorski, Krzysztof</creatorcontrib><creatorcontrib>Czerwoniec, Anna</creatorcontrib><creatorcontrib>Szatkowska, Katarzyna</creatorcontrib><creatorcontrib>Wesoly, Joanna</creatorcontrib><creatorcontrib>Bluyssen, Hans A.R.</creatorcontrib><collection>AGRIS</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>European journal of pharmacology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Szelag, Malgorzata</au><au>Sikorski, Krzysztof</au><au>Czerwoniec, Anna</au><au>Szatkowska, Katarzyna</au><au>Wesoly, Joanna</au><au>Bluyssen, Hans A.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>In silico simulations of STAT1 and STAT3 inhibitors predict SH2 domain cross-binding specificity</atitle><jtitle>European journal of pharmacology</jtitle><addtitle>Eur J Pharmacol</addtitle><date>2013-11-15</date><risdate>2013</risdate><volume>720</volume><issue>1-3</issue><spage>38</spage><epage>48</epage><pages>38-48</pages><issn>0014-2999</issn><eissn>1879-0712</eissn><abstract>Signal transducers and activators of transcription (STATs) comprise a family of transcription factors that are structurally related and which participate in signaling pathways activated by cytokines, growth factors and pathogens. Activation of STAT proteins is mediated by the highly conserved Src homology 2 (SH2) domain, which interacts with phosphotyrosine motifs for specific contacts between STATs and receptors and for STAT dimerization. By generating new models for human (h)STAT1, hSTAT2 and hSTAT3 we applied comparative in silico docking to determine SH2-binding specificity of the STAT3 inhibitor stattic, and of fludarabine (STAT1 inhibitor). Thus, we provide evidence that by primarily targeting the highly conserved phosphotyrosine (pY+0) SH2 binding pocket stattic is not a specific hSTAT3 inhibitor, but is equally effective towards hSTAT1 and hSTAT2. This was confirmed in Human Micro-vascular Endothelial Cells (HMECs) in vitro, in which stattic inhibited interferon-α-induced phosphorylation of all three STATs. Likewise, fludarabine inhibits both hSTAT1 and hSTAT3 phosphorylation, but not hSTAT2, by competing with the highly conserved pY+0 and pY-X binding sites, which are less well-preserved in hSTAT2. Moreover we observed that in HMECs in vitro fludarabine inhibits cytokine and lipopolysaccharide-induced phosphorylation of hSTAT1 and hSTAT3 but does not affect hSTAT2. Finally, multiple sequence alignment of STAT-SH2 domain sequences confirmed high conservation between hSTAT1 and hSTAT3, but not hSTAT2, with respect to stattic and fludarabine binding sites. Together our data offer a molecular basis that explains STAT cross-binding specificity of stattic and fludarabine, thereby questioning the present selection strategies of SH2 domain-based competitive small inhibitors.
High conservation of small-inhibitor binding sites – pY+0, pY+1 and pY-X in the SH2 domain of STAT1 determines STAT cross-binding specificity. [Display omitted]</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>24211327</pmid><doi>10.1016/j.ejphar.2013.10.055</doi><tpages>11</tpages></addata></record> |
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subjects | Amino Acid Sequence Binding Sites Binding specificity Cells, Cultured Computer Simulation Cyclic S-Oxides - pharmacology cytokines dimerization Drug validation endothelial cells Endothelial Cells - drug effects Endothelial Cells - metabolism growth factors Humans Interferon-alpha - pharmacology Interferon-gamma - pharmacology Molecular Docking Simulation Molecular Sequence Data pathogens pharmacology phosphorylation Phosphorylation - drug effects Protein Binding receptors Sequence Alignment signal transduction src Homology Domains STAT-SH2 inhibitors STAT-SH2 modeling STAT1 Transcription Factor - antagonists & inhibitors STAT1 Transcription Factor - metabolism STAT2 Transcription Factor - antagonists & inhibitors STAT2 Transcription Factor - metabolism STAT3 Transcription Factor - antagonists & inhibitors STAT3 Transcription Factor - metabolism transcription factors Vidarabine - analogs & derivatives Vidarabine - pharmacology |
title | In silico simulations of STAT1 and STAT3 inhibitors predict SH2 domain cross-binding specificity |
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