Jai A P Shanata

California Institute of Technology, Pasadena, CA, United States

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Publications (5)54.23 Total impact

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    ABSTRACT: Drug-receptor binding interactions of four agonists, ACh, nicotine, and the smoking cessation compounds varenicline (Chantix) and cytisine (Tabex), have been evaluated at both the 2:3 and 3:2 stoichiometries of the α4β2 nicotinic acetylcholine receptor (nAChR). Previous studies have established that unnatural amino acid mutagenesis can probe three key binding interactions at the nAChR: a cation-π interaction, and two hydrogen-bonding interactions to the protein backbone of the receptor. We find that all drugs make a cation-π interaction to TrpB of the receptor. All drugs except ACh, which lacks an N(+)H group, make a hydrogen bond to a backbone carbonyl, and ACh and nicotine behave similarly in acting as a hydrogen-bond acceptor. However, varenicline is not a hydrogen-bond acceptor to the backbone NH that interacts strongly with the other three compounds considered. In addition, we see interesting variations in hydrogen bonding interactions with cytisine that provide a rationalization for the stoichiometry selectivity seen with this compound.
    Journal of the American Chemical Society 06/2012; 134(28):11474-80. · 10.68 Impact Factor
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    ABSTRACT: Functional coupling of residues that are far apart in space is the quintessential property of allosteric receptors. Data from functional studies of allosteric receptors, such as whole-cell dose-response relations, can be used to determine if mutation to a receptor significantly impacts agonist potency. However, the classification of perturbations as primarily impacting binding or allosteric function is more challenging, often requiring detailed kinetic studies. This protocol describes a simple strategy, derived from mutant cycle analysis, for elucidating long-range functional coupling in allosteric receptors (ELFCAR). Introduction of a gain-of-function reporter mutation, followed by a mutant cycle analysis of the readily measured macroscopic EC(50) values can provide insight into the role of many physically distant targets. This new method should find broad application in determining the functional roles of residues in allosteric receptors.
    Methods in molecular biology (Clifton, N.J.) 01/2012; 796:97-113. · 1.29 Impact Factor
  • Jai A. P. Shanata, Henry A. Lester, Dennis A. Dougherty
    Biophysical Journal - BIOPHYS J. 01/2010; 98(3).
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    ABSTRACT: The functional coupling of residues that are far apart in space is the quintessential property of allosteric proteins. For example, in Cys-loop receptors, the gating of an intrinsic ion channel is allosterically regulated by the binding of small molecule neurotransmitters 50-60 A from the channel gate. Some residues near the binding site must have as their primary function the communication of the binding event to the gating region. These gating pathway residues are essential to function, but their identification and characterization can be challenging. This work introduces a simple strategy, derived from mutant cycle analysis, for identifying gating pathway residues using macroscopic measurements alone. In the exemplar Cys-loop receptor, the nicotinic acetylcholine receptor, a well-characterized reporter mutation (betaL9'S) known to impact gating, was combined with mutations of target residues in the ligand-binding domain hypothesized or previously found to be functionally significant. A mutant cycle analysis of the macroscopic EC(50) measurements can then provide insights into the role of the target residue. This new method, elucidating long-range functional coupling in allosteric receptors, can be applied to several reporter mutations in a wide variety of receptors to identify previously characterized and novel mutations that impact the gating pathway. We support our interpretation of macroscopic data with single-channel studies. Elucidating long-range functional coupling in allosteric receptors should be broadly applicable to determining functional roles of residues in allosteric receptors.
    Biophysical Journal 05/2009; 96(8):3168-78. · 3.67 Impact Factor
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    ABSTRACT: Nicotine addiction begins with high-affinity binding of nicotine to acetylcholine (ACh) receptors in the brain. The end result is over 4,000,000 smoking-related deaths annually worldwide and the largest source of preventable mortality in developed countries. Stress reduction, pleasure, improved cognition and other central nervous system effects are strongly associated with smoking. However, if nicotine activated ACh receptors found in muscle as potently as it does brain ACh receptors, smoking would cause intolerable and perhaps fatal muscle contractions. Despite extensive pharmacological, functional and structural studies of ACh receptors, the basis for the differential action of nicotine on brain compared with muscle ACh receptors has not been determined. Here we show that at the alpha4beta2 brain receptors thought to underlie nicotine addiction, the high affinity for nicotine is the result of a strong cation-pi interaction to a specific aromatic amino acid of the receptor, TrpB. In contrast, the low affinity for nicotine at the muscle-type ACh receptor is largely due to the fact that this key interaction is absent, even though the immediate binding site residues, including the key amino acid TrpB, are identical in the brain and muscle receptors. At the same time a hydrogen bond from nicotine to the backbone carbonyl of TrpB is enhanced in the neuronal receptor relative to the muscle type. A point mutation near TrpB that differentiates alpha4beta2 and muscle-type receptors seems to influence the shape of the binding site, allowing nicotine to interact more strongly with TrpB in the neuronal receptor. ACh receptors are established therapeutic targets for Alzheimer's disease, schizophrenia, Parkinson's disease, smoking cessation, pain, attention-deficit hyperactivity disorder, epilepsy, autism and depression. Along with solving a chemical mystery in nicotine addiction, our results provide guidance for efforts to develop drugs that target specific types of nicotinic receptors.
    Nature 04/2009; 458(7237):534-7. · 38.60 Impact Factor