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Dynamic equilibrium engagement of a polyvalent ligand with a single-site receptor.

ABSTRACT: Intrinsically disordered proteins play critical but often poorly understood roles in mediating protein interactions. The interactions of disordered proteins studied to date typically entail structural stabilization, whether as a global disorder-to-order transition or minimal ordering of short linear motifs. The disordered cyclin-dependent kinase (CDK) inhibitor Sic1 interacts with a single site on its receptor Cdc4 only upon phosphorylation of its multiple dispersed CDK sites. The molecular basis for this multisite-dependent interaction with a single receptor site is not known. By NMR analysis, we show that multiple phosphorylated sites on Sic1 interact with Cdc4 in dynamic equilibrium with only local ordering around each site. Regardless of phosphorylation status, Sic1 exists in an intrinsically disordered state but is surprisingly compact with transient structure. The observation of this unusual binding mode between Sic1 and Cdc4 extends the understanding of protein interactions from predominantly static complexes to include dynamic ensembles of intrinsically disordered states.

SUBMITTER: Mittag T

PROVIDER: S-EPMC2582940 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:G protein-coupled receptors are involved in many biological processes, relaying the extracellular signal inside the cell. Signaling is regulated by the interactions between receptors and their ligands, it can be stimulated by agonists, or inhibited by antagonists or inverse agonists. The development of a new drug targeting a member of this family requires to take into account the pharmacological profile of the designed ligands in order to elicit the desired response. The structure-based virtual screening of chemical libraries may prioritize a specific class of ligands by combining docking results and ligand binding information provided by crystallographic structures. The performance of the method depends on the relevance of the structural data, in particular the conformation of the targeted site, the binding mode of the reference ligand, and the approach used to compare the interactions formed by the docked ligand with those formed by the reference ligand in the crystallographic structure. Here, we propose a new method based on the conformational dynamics of a single protein-ligand reference complex to improve the biased selection of ligands with specific pharmacological properties in a structure-based virtual screening exercise. Interactions patterns between a reference agonist and the receptor, here exemplified on the β2 adrenergic receptor, were extracted from molecular dynamics simulations of the agonist/receptor complex and encoded in graphs used to train a one-class machine learning classifier. Different conditions were tested: low to high affinity agonists, varying simulation duration, considering or ignoring hydrophobic contacts, and tuning of the classifier parametrization. The best models applied to post-process raw data from retrospective virtual screening obtained by docking of test libraries effectively filtered out irrelevant poses, discarding inactive and non-agonist ligands while identifying agonists. Taken together, our results suggest that consistency of the binding mode during the simulation is a key to the success of the method.

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Dynamic equilibrium engagement of a polyvalent ligand with a single-site receptor.

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