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Structural features for functional selectivity at serotonin receptors.

ABSTRACT: Drugs active at G protein-coupled receptors (GPCRs) can differentially modulate either canonical or noncanonical signaling pathways via a phenomenon known as functional selectivity or biased signaling. We report biochemical studies showing that the hallucinogen lysergic acid diethylamide, its precursor ergotamine (ERG), and related ergolines display strong functional selectivity for ?-arrestin signaling at the 5-HT2B 5-hydroxytryptamine (5-HT) receptor, whereas they are relatively unbiased at the 5-HT1B receptor. To investigate the structural basis for biased signaling, we determined the crystal structure of the human 5-HT2B receptor bound to ERG and compared it with the 5-HT1B/ERG structure. Given the relatively poor understanding of GPCR structure and function to date, insight into different GPCR signaling pathways is important to better understand both adverse and favorable therapeutic activities.

SUBMITTER: Wacker D

PROVIDER: S-EPMC3644390 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Structural features for functional selectivity at serotonin receptors.

Wacker Daniel D Wang Chong C Katritch Vsevolod V Han Gye Won GW Huang Xi-Ping XP Vardy Eyal E McCorvy John D JD Jiang Yi Y Chu Meihua M Siu Fai Yiu FY Liu Wei W Xu H Eric HE Cherezov Vadim V Roth Bryan L BL Stevens Raymond C RC

Science (New York, N.Y.) 20130321 6132

Drugs active at G protein-coupled receptors (GPCRs) can differentially modulate either canonical or noncanonical signaling pathways via a phenomenon known as functional selectivity or biased signaling. We report biochemical studies showing that the hallucinogen lysergic acid diethylamide, its precursor ergotamine (ERG), and related ergolines display strong functional selectivity for β-arrestin signaling at the 5-HT2B 5-hydroxytryptamine (5-HT) receptor, whereas they are relatively unbiased at th ...[more]

PMID: 23519215

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Project description:Cancer is a complex disease resulting from the uncontrolled proliferation of cell signaling events. Protein kinases have been identified as central molecules that participate overwhelmingly in oncogenic events, thus becoming key targets for anticancer drugs. A majority of studies converged on the idea that ligand-binding pockets of kinases retain clues to the inhibiting abilities and cross-reacting tendencies of inhibitor drugs. Even though these ideas are critical for drug discovery, validating them using experiments is not only difficult, but also in some cases infeasible. To overcome these limitations and to test these ideas at the molecular level, we present here the results of receptor-focused in-silico docking of nine marketed drugs to 19 different wild-type and mutated kinases chosen from a wide range of families. This investigation highlights the need for using relevant models to explain the correct inhibition trends and the results are used to make predictions that might be able to influence future experiments. Our simulation studies are able to correctly predict the primary targets for each drug studied in majority of cases and our results agree with the existing findings. Our study shows that the conformations a given receptor acquires during kinase activation, and their micro-environment, defines the ligand partners. Type II drugs display high compatibility and selectivity for DFG-out kinase conformations. On the other hand Type I drugs are less selective and show binding preferences for both the open and closed forms of selected kinases. Using this receptor-focused approach, it is possible to capture the observed fold change in binding affinities between the wild-type and disease-centric mutations in ABL kinase for Imatinib and the second-generation ABL drugs. The effects of mutation are also investigated for two other systems, EGFR and B-Raf. Finally, by including pathway information in the design it is possible to model kinase inhibitors with potentially fewer side-effects.

Dataset Information

Structural features for functional selectivity at serotonin receptors.

Publications

Structural features for functional selectivity at serotonin receptors.

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