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      The Chemical Basis of Pharmacology

      review-article
      , ,
      Biochemistry
      American Chemical Society

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          Abstract

          Molecular biology now dominates pharmacology so thoroughly that it is difficult to recall that only a generation ago the field was very different. To understand drug action today, we characterize the targets through which they act and new drug leads are discovered on the basis of target structure and function. Until the mid-1980s the information often flowed in reverse: investigators began with organic molecules and sought targets, relating receptors not by sequence or structure but by their ligands. Recently, investigators have returned to this chemical view of biology, bringing to it systematic and quantitative methods of relating targets by their ligands. This has allowed the discovery of new targets for established drugs, suggested the bases for their side effects, and predicted the molecular targets underlying phenotypic screens. The bases for these new methods, some of their successes and liabilities, and new opportunities for their use are described.

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          Most cited references36

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          A fast flexible docking method using an incremental construction algorithm.

          We present an automatic method for docking organic ligands into protein binding sites. The method can be used in the design process of specific protein ligands. It combines an appropriate model of the physico-chemical properties of the docked molecules with efficient methods for sampling the conformational space of the ligand. If the ligand is flexible, it can adopt a large variety of different conformations. Each such minimum in conformational space presents a potential candidate for the conformation of the ligand in the complexed state. Our docking method samples the conformation space of the ligand on the basis of a discrete model and uses a tree-search technique for placing the ligand incrementally into the active site. For placing the first fragment of the ligand into the protein, we use hashing techniques adapted from computer vision. The incremental construction algorithm is based on a greedy strategy combined with efficient methods for overlap detection and for the search of new interactions. We present results on 19 complexes of which the binding geometry has been crystallographically determined. All considered ligands are docked in at most three minutes on a current workstation. The experimentally observed binding mode of the ligand is reproduced with 0.5 to 1.2 A rms deviation. It is almost always found among the highest-ranking conformations computed.
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            Discovery of drug mode of action and drug repositioning from transcriptional responses.

            A bottleneck in drug discovery is the identification of the molecular targets of a compound (mode of action, MoA) and of its off-target effects. Previous approaches to elucidate drug MoA include analysis of chemical structures, transcriptional responses following treatment, and text mining. Methods based on transcriptional responses require the least amount of information and can be quickly applied to new compounds. Available methods are inefficient and are not able to support network pharmacology. We developed an automatic and robust approach that exploits similarity in gene expression profiles following drug treatment, across multiple cell lines and dosages, to predict similarities in drug effect and MoA. We constructed a "drug network" of 1,302 nodes (drugs) and 41,047 edges (indicating similarities between pair of drugs). We applied network theory, partitioning drugs into groups of densely interconnected nodes (i.e., communities). These communities are significantly enriched for compounds with similar MoA, or acting on the same pathway, and can be used to identify the compound-targeted biological pathways. New compounds can be integrated into the network to predict their therapeutic and off-target effects. Using this network, we correctly predicted the MoA for nine anticancer compounds, and we were able to discover an unreported effect for a well-known drug. We verified an unexpected similarity between cyclin-dependent kinase 2 inhibitors and Topoisomerase inhibitors. We discovered that Fasudil (a Rho-kinase inhibitor) might be "repositioned" as an enhancer of cellular autophagy, potentially applicable to several neurodegenerative disorders. Our approach was implemented in a tool (Mode of Action by NeTwoRk Analysis, MANTRA, http://mantra.tigem.it).
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              GPCR engineering yields high-resolution structural insights into beta2-adrenergic receptor function.

              The beta2-adrenergic receptor (beta2AR) is a well-studied prototype for heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) that respond to diffusible hormones and neurotransmitters. To overcome the structural flexibility of the beta2AR and to facilitate its crystallization, we engineered a beta2AR fusion protein in which T4 lysozyme (T4L) replaces most of the third intracellular loop of the GPCR ("beta2AR-T4L") and showed that this protein retains near-native pharmacologic properties. Analysis of adrenergic receptor ligand-binding mutants within the context of the reported high-resolution structure of beta2AR-T4L provides insights into inverse-agonist binding and the structural changes required to accommodate catecholamine agonists. Amino acids known to regulate receptor function are linked through packing interactions and a network of hydrogen bonds, suggesting a conformational pathway from the ligand-binding pocket to regions that interact with G proteins.
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                Author and article information

                Journal
                Biochemistry
                bi
                bichaw
                Biochemistry
                American Chemical Society
                0006-2960
                1520-4995
                08 November 2010
                07 December 2010
                : 49
                : 48
                : 10267-10276
                Affiliations
                Department of Pharmaceutical Chemistry, University of California San Francisco, 1700 4th Street, Byers Hall, Room 508D, San Francisco, California 94158-2558, United States
                Author notes
                [* ]To whom correspondence should be addressed. J.J.I.: e-mail, irwin@ 123456cgl.ucsf.edu ; phone, (415) 514-4127; fax, (415) 514-4260. B.K.S.: e-mail, shoichet@ 123456cgl.ucsf.edu ; phone, (415) 514-4126; fax, (415) 514-4260.
                Article
                10.1021/bi101540g
                2994275
                21058655
                907b5023-26c3-486c-9622-5c3048d8ccb0
                Copyright © 2010 American Chemical Society

                This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org.

                History
                : 21 September 2010
                : 05 November 2010
                : 12 November 2010
                : 07 December 2010
                : 08 November 2010
                Funding
                National Institutes of Health, United States
                Categories
                Current Topic
                Custom metadata
                bi101540g
                bi-2010-01540g

                Biochemistry
                Biochemistry

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