Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A1 Adenosine Receptor Antagonists
G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs...
Gespeichert in:
Veröffentlicht in: | PloS one 2012-11, Vol.7 (11), p.e49910 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 11 |
container_start_page | e49910 |
container_title | PloS one |
container_volume | 7 |
creator | Kolb, Peter Phan, Khai Gao, Zhan-Guo Marko, Adam C. Sali, Andrej Jacobson, Kenneth A. |
description | G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs have a known structure, receptor homology modeling remains necessary. In order to investigate the usability of homology models and the inherent selectivity of a particular model in relation to close homologs, we constructed multiple homology models for the A1 adenosine receptor (A1AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A1AR as well as the close homologs A2AAR and A3AR. While the screen yielded numerous potent and novel ligands (hit rate 21% and highest affinity of 400 nM), it delivered few selective compounds. Moreover, most compounds appeared in the top ranks of only one model. These findings have implications for future screens. |
doi_str_mv | 10.1371/journal.pone.0049910 |
format | Article |
fullrecord | <record><control><sourceid>proquest_plos_</sourceid><recordid>TN_cdi_plos_journals_1326748615</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2944528951</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3190-52a9fac7a5314ab9ab92d3f666cc671f66320f09fbf9cd5d5f3fcdad78ec39063</originalsourceid><addsrcrecordid>eNp1UdtKAzEQDaJovfyBYMDn1lx2sxsfhFKvUBGsPoc0l5q6TWqSFvr3dnEVfRAGZphz5hyYA8ApRgNMK3wxD6voZTNYBm8GCBWcY7QDephT0mcE0d1f8wE4TGmOUElrxvbBAaG4Loua9IAfu4XLCQYLx24mvYYT0xiV3drlDbQxLOB1UO_Oz2AO8DFo06RL-ODhxDVOBThR0RjfwjZEOMRwqI0PyXkDn40yy9xufZaz4F3K6RjsWdkkc9L1I_B6e_Myuu-Pn-4eRsNxX1HMUb8kklupKllSXMgp3xbR1DLGlGIV3g6UIIu4nVqudKlLS63SUle1UZQjRo_A2ZfusglJdK9KAlPCqqJmuNwyrjrGarowWhmfo2zEMrqFjBsRpBN_Ee_exCysBS0RrUlrcd4JxPCxMin_Y1N8sVQMKUVjfxwwEm2O31eizVF0OdJPlO2TyA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1326748615</pqid></control><display><type>article</type><title>Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A1 Adenosine Receptor Antagonists</title><source>PMC (PubMed Central)</source><source>Public Library of Science</source><source>Directory of Open Access Journals</source><source>Free Full-Text Journals in Chemistry</source><source>EZB Electronic Journals Library</source><creator>Kolb, Peter ; Phan, Khai ; Gao, Zhan-Guo ; Marko, Adam C. ; Sali, Andrej ; Jacobson, Kenneth A.</creator><contributor>Seifert, Roland</contributor><creatorcontrib>Kolb, Peter ; Phan, Khai ; Gao, Zhan-Guo ; Marko, Adam C. ; Sali, Andrej ; Jacobson, Kenneth A. ; Seifert, Roland</creatorcontrib><description>G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs have a known structure, receptor homology modeling remains necessary. In order to investigate the usability of homology models and the inherent selectivity of a particular model in relation to close homologs, we constructed multiple homology models for the A1 adenosine receptor (A1AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A1AR as well as the close homologs A2AAR and A3AR. While the screen yielded numerous potent and novel ligands (hit rate 21% and highest affinity of 400 nM), it delivered few selective compounds. Moreover, most compounds appeared in the top ranks of only one model. These findings have implications for future screens.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0049910</identifier><identifier>PMID: 23185482</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Adenosine ; Bioengineering ; Biology ; Chemistry ; Chemokines ; Computer applications ; Computer Science ; Diabetes ; Docking ; G protein-coupled receptors ; Homology ; Identification methods ; Kidney diseases ; Laboratories ; Ligands ; Medical screening ; Medicine ; Pharmaceuticals ; Physics ; Proteins ; Receptors ; Selectivity</subject><ispartof>PloS one, 2012-11, Vol.7 (11), p.e49910</ispartof><rights>2012. This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2012</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3190-52a9fac7a5314ab9ab92d3f666cc671f66320f09fbf9cd5d5f3fcdad78ec39063</citedby><cites>FETCH-LOGICAL-c3190-52a9fac7a5314ab9ab92d3f666cc671f66320f09fbf9cd5d5f3fcdad78ec39063</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3503826/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3503826/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2915,23847,27905,27906,53772,53774,79349,79350</link.rule.ids></links><search><contributor>Seifert, Roland</contributor><creatorcontrib>Kolb, Peter</creatorcontrib><creatorcontrib>Phan, Khai</creatorcontrib><creatorcontrib>Gao, Zhan-Guo</creatorcontrib><creatorcontrib>Marko, Adam C.</creatorcontrib><creatorcontrib>Sali, Andrej</creatorcontrib><creatorcontrib>Jacobson, Kenneth A.</creatorcontrib><title>Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A1 Adenosine Receptor Antagonists</title><title>PloS one</title><description>G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs have a known structure, receptor homology modeling remains necessary. In order to investigate the usability of homology models and the inherent selectivity of a particular model in relation to close homologs, we constructed multiple homology models for the A1 adenosine receptor (A1AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A1AR as well as the close homologs A2AAR and A3AR. While the screen yielded numerous potent and novel ligands (hit rate 21% and highest affinity of 400 nM), it delivered few selective compounds. Moreover, most compounds appeared in the top ranks of only one model. These findings have implications for future screens.</description><subject>Adenosine</subject><subject>Bioengineering</subject><subject>Biology</subject><subject>Chemistry</subject><subject>Chemokines</subject><subject>Computer applications</subject><subject>Computer Science</subject><subject>Diabetes</subject><subject>Docking</subject><subject>G protein-coupled receptors</subject><subject>Homology</subject><subject>Identification methods</subject><subject>Kidney diseases</subject><subject>Laboratories</subject><subject>Ligands</subject><subject>Medical screening</subject><subject>Medicine</subject><subject>Pharmaceuticals</subject><subject>Physics</subject><subject>Proteins</subject><subject>Receptors</subject><subject>Selectivity</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1UdtKAzEQDaJovfyBYMDn1lx2sxsfhFKvUBGsPoc0l5q6TWqSFvr3dnEVfRAGZphz5hyYA8ApRgNMK3wxD6voZTNYBm8GCBWcY7QDephT0mcE0d1f8wE4TGmOUElrxvbBAaG4Loua9IAfu4XLCQYLx24mvYYT0xiV3drlDbQxLOB1UO_Oz2AO8DFo06RL-ODhxDVOBThR0RjfwjZEOMRwqI0PyXkDn40yy9xufZaz4F3K6RjsWdkkc9L1I_B6e_Myuu-Pn-4eRsNxX1HMUb8kklupKllSXMgp3xbR1DLGlGIV3g6UIIu4nVqudKlLS63SUle1UZQjRo_A2ZfusglJdK9KAlPCqqJmuNwyrjrGarowWhmfo2zEMrqFjBsRpBN_Ee_exCysBS0RrUlrcd4JxPCxMin_Y1N8sVQMKUVjfxwwEm2O31eizVF0OdJPlO2TyA</recordid><startdate>20121121</startdate><enddate>20121121</enddate><creator>Kolb, Peter</creator><creator>Phan, Khai</creator><creator>Gao, Zhan-Guo</creator><creator>Marko, Adam C.</creator><creator>Sali, Andrej</creator><creator>Jacobson, Kenneth A.</creator><general>Public Library of Science</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>5PM</scope></search><sort><creationdate>20121121</creationdate><title>Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A1 Adenosine Receptor Antagonists</title><author>Kolb, Peter ; Phan, Khai ; Gao, Zhan-Guo ; Marko, Adam C. ; Sali, Andrej ; Jacobson, Kenneth A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3190-52a9fac7a5314ab9ab92d3f666cc671f66320f09fbf9cd5d5f3fcdad78ec39063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Adenosine</topic><topic>Bioengineering</topic><topic>Biology</topic><topic>Chemistry</topic><topic>Chemokines</topic><topic>Computer applications</topic><topic>Computer Science</topic><topic>Diabetes</topic><topic>Docking</topic><topic>G protein-coupled receptors</topic><topic>Homology</topic><topic>Identification methods</topic><topic>Kidney diseases</topic><topic>Laboratories</topic><topic>Ligands</topic><topic>Medical screening</topic><topic>Medicine</topic><topic>Pharmaceuticals</topic><topic>Physics</topic><topic>Proteins</topic><topic>Receptors</topic><topic>Selectivity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kolb, Peter</creatorcontrib><creatorcontrib>Phan, Khai</creatorcontrib><creatorcontrib>Gao, Zhan-Guo</creatorcontrib><creatorcontrib>Marko, Adam C.</creatorcontrib><creatorcontrib>Sali, Andrej</creatorcontrib><creatorcontrib>Jacobson, Kenneth A.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing and Allied Health Journals</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>Biological Sciences</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>ProQuest Biological Science Journals</collection><collection>ProQuest Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials science collection</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kolb, Peter</au><au>Phan, Khai</au><au>Gao, Zhan-Guo</au><au>Marko, Adam C.</au><au>Sali, Andrej</au><au>Jacobson, Kenneth A.</au><au>Seifert, Roland</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A1 Adenosine Receptor Antagonists</atitle><jtitle>PloS one</jtitle><date>2012-11-21</date><risdate>2012</risdate><volume>7</volume><issue>11</issue><spage>e49910</spage><pages>e49910-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs have a known structure, receptor homology modeling remains necessary. In order to investigate the usability of homology models and the inherent selectivity of a particular model in relation to close homologs, we constructed multiple homology models for the A1 adenosine receptor (A1AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A1AR as well as the close homologs A2AAR and A3AR. While the screen yielded numerous potent and novel ligands (hit rate 21% and highest affinity of 400 nM), it delivered few selective compounds. Moreover, most compounds appeared in the top ranks of only one model. These findings have implications for future screens.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>23185482</pmid><doi>10.1371/journal.pone.0049910</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2012-11, Vol.7 (11), p.e49910 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_1326748615 |
source | PMC (PubMed Central); Public Library of Science; Directory of Open Access Journals; Free Full-Text Journals in Chemistry; EZB Electronic Journals Library |
subjects | Adenosine Bioengineering Biology Chemistry Chemokines Computer applications Computer Science Diabetes Docking G protein-coupled receptors Homology Identification methods Kidney diseases Laboratories Ligands Medical screening Medicine Pharmaceuticals Physics Proteins Receptors Selectivity |
title | Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A1 Adenosine Receptor Antagonists |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T15%3A43%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Limits%20of%20Ligand%20Selectivity%20from%20Docking%20to%20Models:%20In%20Silico%20Screening%20for%20A1%20Adenosine%20Receptor%20Antagonists&rft.jtitle=PloS%20one&rft.au=Kolb,%20Peter&rft.date=2012-11-21&rft.volume=7&rft.issue=11&rft.spage=e49910&rft.pages=e49910-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0049910&rft_dat=%3Cproquest_plos_%3E2944528951%3C/proquest_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1326748615&rft_id=info:pmid/23185482&rfr_iscdi=true |