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      Limits of Ligand Selectivity from Docking to Models: In Silico Screening for A 1 Adenosine Receptor Antagonists

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          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 A 1 adenosine receptor (A 1AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A 1AR as well as the close homologs A 2AAR and A 3AR. 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.

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          Most cited references 26

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          Structures of the CXCR4 chemokine GPCR with small-molecule and cyclic peptide antagonists.

          Chemokine receptors are critical regulators of cell migration in the context of immune surveillance, inflammation, and development. The G protein-coupled chemokine receptor CXCR4 is specifically implicated in cancer metastasis and HIV-1 infection. Here we report five independent crystal structures of CXCR4 bound to an antagonist small molecule IT1t and a cyclic peptide CVX15 at 2.5 to 3.2 angstrom resolution. All structures reveal a consistent homodimer with an interface including helices V and VI that may be involved in regulating signaling. The location and shape of the ligand-binding sites differ from other G protein-coupled receptors and are closer to the extracellular surface. These structures provide new clues about the interactions between CXCR4 and its natural ligand CXCL12, and with the HIV-1 glycoprotein gp120.
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            Adenosine receptors as therapeutic targets.

            Adenosine receptors are major targets of caffeine, the most commonly consumed drug in the world. There is growing evidence that they could also be promising therapeutic targets in a wide range of conditions, including cerebral and cardiac ischaemic diseases, sleep disorders, immune and inflammatory disorders and cancer. After more than three decades of medicinal chemistry research, a considerable number of selective agonists and antagonists of adenosine receptors have been discovered, and some have been clinically evaluated, although none has yet received regulatory approval. However, recent advances in the understanding of the roles of the various adenosine receptor subtypes, and in the development of selective and potent ligands, as discussed in this review, have brought the goal of therapeutic application of adenosine receptor modulators considerably closer.
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              A geometric approach to macromolecule-ligand interactions.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                21 November 2012
                : 7
                : 11
                Affiliations
                [1 ]Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
                [2 ]Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
                [3 ]Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States of America
                Medical School of Hannover, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PK AS KAJ. Performed the experiments: PK KP ZG ACM. Analyzed the data: PK ACM KAJ. Wrote the paper: PK ACM AS KAJ.

                [¤a]

                Current address: Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany

                [¤b]

                Current address: Asuragen Inc., Austin, Texas, United States of America

                Article
                PONE-D-12-24176
                10.1371/journal.pone.0049910
                3503826
                23185482

                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.

                Page count
                Pages: 9
                Funding
                Funding came from a DFG Emmy-Noether Fellowship KO 4095/1-1 to PK ( www.dfg.de), a National Institutes of Health/National Institute of General Medical Sciences R01 GM083960 grant to AS ( www.nigms.nih.gov), and a National Institute of Diabetes and Digestive and Kidney Diseases Intramural Research Program (1ZIADK031117-24) to KAJ ( http://www2.niddk.nih.gov/NIDDKLabs/NIDDKLabsAbout.htm). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Biochemistry Simulations
                Biomacromolecule-Ligand Interactions
                Drug Discovery
                Biophysics
                Biophysics Simulations
                Computational Biology
                Biochemical Simulations
                Biophysic Al Simulations
                Chemistry
                Medicinal Chemistry
                Computer Science
                Computer Applications
                Computer-Aided Design
                Medicine
                Drugs and Devices
                Drug Research and Development
                Drug Discovery
                Physics
                Biophysics
                Biomacromolecule-Ligand Interactions

                Uncategorized

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