Publications by authors named "Anita K Nivedha"

G protein-coupled receptors engage both G proteins and β-arrestins, and their coupling can be biased by ligands and mutations. Here, to resolve structural elements and mechanisms underlying effector coupling to the angiotensin II (AngII) type 1 receptor (AT1R), we combined alanine scanning mutagenesis of the entire sequence of the receptor with pharmacological profiling of Gα and β-arrestin engagement to mutant receptors and molecular dynamics simulations. We showed that Gα coupling to AT1R involved a large number of residues spread across the receptor, whereas fewer structural regions of the receptor contributed to β-arrestin coupling regulation.

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The structural features that contribute to the efficacy of biased agonists targeting G protein-coupled receptors (GPCRs) towards G proteins or β-arrestin (β-arr) signaling pathways is nebulous, although such knowledge is critical in designing biased ligands. The dynamics of the agonist-GPCR complex is one of the critical factors in determining agonist bias. Angiotensin II type I receptor (AT1R) is an ideal model system to study the molecular basis of bias since it has multiple β-arr2 and Gq protein biased agonists as well as experimentally solved three dimensional structures.

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Aurora kinases and protein kinase C (PKC) have been shown to be involved in different aspects of cancer progression. To date, no dual Aurora/PKC inhibitor with clinical efficacy and low toxicity is available. Here, we report the identification of compound as a potent small molecule capable of selectively inhibiting Aurora A kinase and PKC isoforms α, β1, β2 and θ.

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G protein-coupled receptors (GPCRs) are membrane-bound proteins that are ubiquitously expressed in many cell types and take part in mediating multiple signaling pathways. GPCRs are dynamic proteins and exist in an equilibrium between an ensemble of conformational states such as inactive and fully active states. This dynamic nature of GPCRs is one of the factors that confers their basal activity even in the absence of any ligand-mediated activation.

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Agonist binding in the extracellular region of the G protein-coupled adenosine A2A receptor increases its affinity to the G proteins in the intracellular region, and vice versa. The structural basis for this effect is not evident from the crystal structures of AR in various conformational states since it stems from the receptor dynamics. Using atomistic molecular dynamics simulations on four different conformational states of the adenosine A receptor, we observed that the agonists show decreased ligand mobility, lower entropy of the extracellular loops in the active-intermediate state compared with the inactive state.

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Anti-carbohydrate monoclonal antibodies (mAbs) hold great promise as cancer therapeutics and diagnostics. However, their specificity can be mixed, and detailed characterization is problematic, because antibody-glycan complexes are challenging to crystallize. Here, we developed a generalizable approach employing high-throughput techniques for characterizing the structure and specificity of such mAbs, and applied it to the mAb TKH2 developed against the tumor-associated carbohydrate antigen sialyl-Tn (STn).

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G-protein-coupled receptors (GPCRs) mediate multiple signaling pathways in the cell, depending on the agonist that activates the receptor and multiple cellular factors. Agonists that show higher potency to specific signaling pathways over others are known as "biased agonists" and have been shown to have better therapeutic index. Although biased agonists are desirable, their design poses several challenges to date.

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Molecular docking programs are primarily designed to align rigid, drug-like fragments into the binding sites of macromolecules and frequently display poor performance when applied to flexible carbohydrate molecules. A critical source of flexibility within an oligosaccharide is the glycosidic linkages. Recently, Carbohydrate Intrinsic (CHI) energy functions were reported that attempt to quantify the glycosidic torsion angle preferences.

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Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop a set of Carbohydrate Intrinsic (CHI) energy functions that quantify the conformational properties of oligosaccharides, based on the values of their glycosidic torsion angles. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the protein data bank.

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