Structural requirements for 5-HT2A and 5-HT1A serotonin receptor potentiation by the biologically active lipid oleamide

Oleamide is an endogenous fatty acid primary amide that possesses sleep-inducing properties in animals and that has been shown to effect serotonergic receptor responses and block gap junction communication. Herein, the potentiation of the 5-HT1A receptor response is disclosed, and a study of the structural features of oleamide required for potentiation of the 5-HT2A and 5-HT1A response to serotonin (5-HT) is described. Of the naturally occurring fatty acids, the primary amide of oleic acid (oleamide) is the most effective at potentiating the 5-HT2A receptor response. The structural features required for activity were found to be highly selective. The presence, position, and stereochemistry of the Δ9-cis double bond is required, and even subtle structural variations reduce or eliminate activity. Secondary or tertiary amides may replace the primary amide but follow a well defined relationship requiring small amide substituents, suggesting that the carboxamide serves as a hydrogen bond acceptor but not donor. Alternative modifications at the carboxamide as well as modifications of the methyl terminus or the hydrocarbon region spanning the carboxamide and double bond typically eliminate activity. A less extensive study of the 5-HT1A potentiation revealed that it is more tolerant and accommodates a wider range of structural modifications. An interesting set of analogs was identified that inhibit rather than potentiate the 5-HT2A, but not the 5-HT1A, receptor response, further suggesting that such analogs may permit the selective modulation of serotonin receptor subtypes and even have opposing effects on the different subtypes.

Requirements for heme and thiols for the nonenzymatic modification of nitrotyrosine

Peroxynitrite-dependent formation of nitrotyrosine has been associated with inactivation of various enzymes and proteins possessing functionally important tyrosines. We have previously reported an enzymatic activity modifying the nitrotyrosine residues in nitrated proteins. Here we are describing a nonenzymatic reduction of nitrotyrosine to aminotyrosine, which depends on heme and thiols. Various heme-containing proteins can mediate the reaction, although the reaction also is catalyzed by heme. The reaction is most effective when vicinal thiols are used as reducing agents, although ascorbic acid also can replace thiols with lesser efficiency. The reaction could be inhibited by (z)-1-[2-(2-aminoethyl)-N-(2-ammonioethyl)amino]diazen-1-ium-1, but not other tested NO donors. HPLC with electrochemical detection analysis of the reaction identified aminotyrosine as the only reaction product. The reduction of nitrotyrosine was most effective at a pH close to physiological and was markedly decreased in acidic conditions. Various nitrophenol compounds also were modified in this reaction. Understanding the mechanism of this reaction could help define the enzymatic modification of nitrotyrosine-containing proteins. Furthermore, this also could assist in understanding the role of nitrotyrosine formation and reversal in the regulation of various proteins containing nitrotyrosine. It also could help define the role of nitric oxide and other reactive species in various disease states.

The prion model for [URE3] of yeast: Spontaneous generation and requirements for propagation

The genetic properties of the non-Mendelian element, [URE3], suggest that it is a prion (infectious protein) form of Ure2p, a mediator of nitrogen regulation in Saccharomyces cerevisiae. Into a ure2Δ strain (necessarily lacking [URE3]), we introduced a plasmid overproducing Ure2p. This induced the frequent “spontaneous generation” of [URE3], with properties identical to the original [URE3]. Altering the translational frame only in the prion-inducing domain of URE2 shows that it is Ure2 protein (and not URE2 RNA) that induces appearance of [URE3]. The proteinase K-resistance of Ure2p is unique to [URE3] strains and is not seen in nitrogen regulation of normal strains. The prion-inducing domain of Ure2p (residues 1–65) can propagate [URE3] in the absence of the C-terminal part of the molecule. In contrast, the C-terminal part of Ure2p cannot be converted to the prion (inactive) form without the prion-inducing domain covalently attached. These experiments support the prion model for [URE3] and extend our understanding of its propagation.

Structural requirements for antigen presentation by mouse CD1

The structural basis for the T cell response to glycolipid antigens (Ags) remains poorly understood. T lymphocytes autoreactive for mouse CD1 (mCD1.1) or reactive for the glycosphingolipid αgalactosylceramide (α-GalCer) presented by mCD1.1 have been described previously. In this paper it is shown that mutations at the top of the α helices and in the bottom of the Ag-binding groove can disrupt both mCD1.1 autoreactivity and α-GalCer recognition. The locations of the positions that affect T cell responses indicate that recognition of mCD1.1 is not likely to be unconventional or superantigen-like. Furthermore, the effects of the bottom of the pocket mutation suggest that the autoreactive response could require an autologous ligand, and they indicate that α-GalCer binds to the groove of mCD1.1, most likely with the shorter 18-carbon hydrophobic chain in the A′ pocket. Natural killer T cell hybridomas with identical T cell antigen receptor (TCR) α chains and different β chains respond differently to α-GalCer presented by mCD1.1 mutants. This finding indicates a role for TCR β in defining natural killer T cell specificity, despite the more restricted diversity of the α chains in these cells. Overall, the data are consistent with a mode of lipoglycan recognition similar to that proposed for glycopeptides, in which the TCR α and β chains survey a surface composed of both mCD1.1 and the carbohydrate portion of α-GalCer.

Training and search methods for speech recognition.

Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance.