Contributions of the GABAergic system of the prelimbic cortex and basolateral amygdala to morphine withdrawal-induced contextual fear.

Morphine withdrawal can trigger disruptions in neuronal pathways involved in the modulation and expression of anxiety and fear-related behaviors, particularly those involved in associative learning. When it comes to contextual fear, specific subdivisions of the medial prefrontal cortex (mPFC) regulate the expression of defensive behaviors through projections to specific amygdala (AM) nuclei, such as the prelimbic cortex (PrL). The basolateral nucleus (BLA) of the AM has been shown to be involved in the modulation and expression of associative memories of fear, including those associated with opiate withdrawal-related aversive events. The purpose of this study is to determine the role of GABA mechanisms in the PrL and BLA in startle potentiation and freezing behavior caused by morphine-precipitated withdrawal. Our findings show that morphine withdrawal promotes the emergence of contextual conditioned fear in animals when they are exposed to the same environment where the withdrawal sessions were performed. This suggests that the neural circuits underlying the organism's response to conditioned stressors and the circuits modulating the negative affective states induced by drug withdrawal may overlap. The pharmacological manipulation of GABAergic neurotransmission in the PrL and BLA can reverse contextual fear in morphine-withdrawn rats, an effect that appears to be mediated, at least in part, by GABAA receptors.

Simple solvation potential for coarse-grained models of proteins.

We formulate a simple solvation potential based on a coarsed-grained representation of amino acids with two spheres modeling the C(alpha) atom and an effective side-chain centroid. The potential relies on a new method for estimating the buried area of residues, based on counting the effective number of burying neighbors in a suitable way. This latter quantity shows a good correlation with the buried area of residues computed from all atom crystallographic structures. We check the discriminatory power of the solvation potential alone to identify the native fold of a protein from a set of decoys and show the potential to be considerably selective.

Optimal potentials for predicting inter-helical packing in transmembrane proteins.

A set of pairwise contact potentials between amino acid residues in transmembrane helices was determined from the known native structure of the transmembrane protein (TMP) bacteriorhodopsin by the method of perceptron learning, using Monte Carlo dynamics to generate suitable "decoy" structures. The procedure of finding these decoys is simpler than for globular proteins, since it is reasonable to assume that helices behave as independent, stable objects and, therefore, the search in the conformational space is greatly reduced. With the learnt potentials, the association of the helices in bacteriorhodopsin was successfully simulated. The folding of a second TMP (the helix-dimer glycophorin A) was then accomplished with only a refinement of the potentials from a small number of decoys.

Elucidation of the disulfide-folding pathway of hirudin by a topology-based approach.

A theoretical model for the folding of proteins containing disulfide bonds is introduced. The model exploits the knowledge of the native state to favor the progressive establishment of native interactions. At variance with traditional approaches based on native topology, not all native bonds are treated in the same way; in particular, a suitable energy term is introduced to account for the special strength of disulfide bonds, as well as their ability to undergo intramolecular reshuffling. The model thus possesses the minimal ingredients necessary to investigate the much debated issue of whether the refolding process occurs through partially structured intermediates with native or non-native disulfide bonds. This strategy is applied to a context of particular interest, the refolding process of hirudin, a thrombin-specific protease inhibitor, for which conflicting folding pathways have been proposed. We show that the only two parameters in the model (temperature and disulfide strength) can be tuned to reproduce well a set of experimental transitions between species with different number of formed disulfides. This model is then used to provide a characterization of the folding process and a detailed description of the species involved in the rate-limiting step of hirudin refolding.

Adsorptionlike collapse of diblock copolymers

A linear copolymer made of two reciprocally attracting N-monomer blocks collapses to a compact phase through a novel transition, whose exponents are determined with extensive Monte Carlo simulations in two and three dimensions. In the former case, an identification with the statistical geometry of suitable percolation paths allows one to predict that the number of contacts between the blocks grows like N9/16. In the compact phase the blocks are mixed and, in two dimensions, also zipped, in such a way to form a spiral, double chain structure.

Mechanical unfolding of directed polymers in a poor solvent: critical exponents.

We study the thermodynamics of an exactly solvable model of a self-interacting, partially directed self-avoiding walk in two dimensions when a force is applied on one end of the chain. The critical force for the unfolding is determined exactly, as a function of the temperature, below the Theta transition. The transition is of second order and is characterized by new critical exponents that are determined by a careful numerical analysis. The usual polymer critical index nu on the critical line, and another one which we call zeta, takes a nontrivial value that is numerically close to 2/3.

Different pulling modes in DNA overstretching: a theoretical analysis.

We study the thermally driven denaturation of a double-stranded polymer in the presence of a stretching force via Monte-Carlo simulations. When one strand only is stretched, the denaturation transition is first order, while when both strands are stretched, melting is second order. By revisiting the Poland-Scheraga model for DNA melting, we show that at room temperature, the most likely scenario is that DNA melts as it overstretches. Our results are in general agreement with the most recent experiments and suggest how varying temperature and stretching mode may help settle the question whether S-DNA exists or not.

Form of growing strings.

Patterns and forms adopted by nature are often the results of simple dynamical paradigms. Here we show that a growing self-interacting string attached to a tracking origin, modeled to resemble nascent polypeptides in vivo, develops helical structures which are more pronounced at the growing end. We also show that the dynamic growth ensemble shares several features of an equilibrium ensemble in which the growing end of the polymer is under an effective stretching force. A statistical analysis of native states of proteins shows that the signature of this nonequilibrium phenomenon has been fixed by evolution at the C terminus, the growing end of a nascent protein. These findings suggest how evolution may have built on the properties of a generic nonequilibrium growth process in favoring helical structures in nascent chains.

Simple model to study insertion of a protein into a membrane.

A simple coarse grained model on a two-dimensional lattice is presented to elucidate the main effects ruling the insertion of a protein into a polar environment such as a lipidic membrane. The amino acids are divided into two classes (hydrophobic or polar), and they behave differently according to their surroundings. In aqueous solution the hydrophobic amino acids are forced to minimize contacts with water, whereas in the apolar environment all the amino acids try to aggregate regardless to their specificity. The lattice is employed in order to perform exact calculations and to generate a fictitious protein data bank. Despite the simplicity of the model, some morphological features of the protein-like lattice structures obtained by our model are compatible with the observed phenomenology of transmembrane proteins. These results seem to corroborate the hypothesis that the number of classes into which the amino acids can be divided that correctly describe the phenomena may be extremely low.