957 resultados para free energy simulation


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Mechanical force modulates myriad cellular functions including migration, alignment, proliferation, and gene transcription. Mechanotransduction, the transmission of mechanical forces and its translation into biochemical signals, may be mediated by force induced protein conformation changes, subsequently modulating protein signaling. For the paxillin and focal adhesion kinase interaction, we demonstrate that force-induced changes in protein complex conformation, dissociation constant, and binding Gibbs free energy can be quantified by lifetime-resolved fluorescence energy transfer microscopy combined with intensity imaging calibrated by fluorescence correlation spectroscopy. Comparison with in vitro data shows that this interaction is allosteric in vivo. Further, spatially resolved imaging and inhibitor assays show that this protein interaction and its mechano-sensitivity are equal in the cytosol and in the focal adhesions complexes indicating that the mechano-sensitivity of this interaction must be mediated by soluble factors but not based on protein tyrosine phosphorylation.

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We explore the phase diagram of a two-component ultracold atomic Fermi gas interacting with zero-range forces in the limit of weak coupling. We focus on the dependence of the pairing gap and the free energy on the variations in the number densities of the two species while the total density of the system is held fixed. As the density asymmetry is increased, the system exhibits a transition from a homogenous Bardeen-Cooper-Schrieffer (BCS) phase to phases with spontaneously broken global space symmetries. One such realization is the deformed Fermi surface superfluidity (DFS) which exploits the possibility of deforming the Fermi surfaces of the species into ellipsoidal form at zero total momentum of Cooper pairs. The critical asymmetries at which the transition from DFS to the unpaired state occurs are larger than those for the BCS phase. In this precritical region the DFS phase lowers the pairing energy of the asymmetric BCS state. We compare quantitatively the DFS phase to another realization of superconducting phases with broken translational symmetry: the single-plane-wave Larkin-Ovchinnikov-Fulde-Ferrell phase, which is characterized by a nonvanishing center-of-mass momentum of the Cooper pairs. The possibility of the detection of the DFS phase in the time-of-flight experiments is discussed and quantified for the case of 6Li atoms trapped in two different hyperfine states.

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Nucleation rates for tunneling processes in Minkowski and de Sitter space are investigated, taking into account one loop prefactors. In particular, we consider the creation of membranes by an antisymmetric tensor field, analogous to Schwinger pair production. This can be viewed as a model for the decay of a false (or true) vacuum at zero temperature in the thin wall limit. Also considered is the spontaneous nucleation of strings, domain walls, and monopoles during inflation. The instantons for these processes are spherical world sheets or world lines embedded in flat or de Sitter backgrounds. We find the contribution of such instantons to the semiclassical partition function, including the one loop corrections due to small fluctuations around the spherical world sheet. We suggest a prescription for obtaining, from the partition function, the distribution of objects nucleated during inflation. This can be seen as an extension of the usual formula, valid in flat space, according to which the nucleation rate is twice the imaginary part of the free energy. For the case of pair production, the results reproduce those that can be obtained using second quantization methods, confirming the validity of instanton techniques in de Sitter space. Throughout the paper, both the gravitational field and the antisymmetric tensor field are assumed external.

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The structure of polydisperse hard sphere fluids, in the presence of a wall, is studied by the Rosenfeld density functional theory. Within this approach, the local excess free energy depends on only four combinations of the full set of density fields. The case of continuous polydispersity thereby becomes tractable. We predict, generically, an oscillatory size segregation close to the wall, and connect this, by a perturbation theory for narrow distributions, with the reversible work for changing the size of one particle in a monodisperse reference fluid.

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The protein shells, or capsids, of nearly all spherelike viruses adopt icosahedral symmetry. In the present Letter, we propose a statistical thermodynamic model for viral self-assembly. We find that icosahedral symmetry is not expected for viral capsids constructed from structurally identical protein subunits and that this symmetry requires (at least) two internal switching configurations of the protein. Our results indicate that icosahedral symmetry is not a generic consequence of free energy minimization but requires optimization of internal structural parameters of the capsid proteins

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We consider damage spreading transitions in the framework of mode-coupling theory. This theory describes relaxation processes in glasses in the mean-field approximation which are known to be characterized by the presence of an exponentially large number of metastable states. For systems evolving under identical but arbitrarily correlated noises, we demonstrate that there exists a critical temperature T0 which separates two different dynamical regimes depending on whether damage spreads or not in the asymptotic long-time limit. This transition exists for generic noise correlations such that the zero damage solution is stable at high temperatures, being minimal for maximal noise correlations. Although this dynamical transition depends on the type of noise correlations, we show that the asymptotic damage has the good properties of a dynamical order parameter, such as (i) independence of the initial damage; (ii) independence of the class of initial condition; and (iii) stability of the transition in the presence of asymmetric interactions which violate detailed balance. For maximally correlated noises we suggest that damage spreading occurs due to the presence of a divergent number of saddle points (as well as metastable states) in the thermodynamic limit consequence of the ruggedness of the free-energy landscape which characterizes the glassy state. These results are then compared to extensive numerical simulations of a mean-field glass model (the Bernasconi model) with Monte Carlo heat-bath dynamics. The freedom of choosing arbitrary noise correlations for Langevin dynamics makes damage spreading an interesting tool to probe the ruggedness of the configurational landscape.

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We study the static properties of the Little model with asymmetric couplings. We show that the thermodynamics of this model coincides with that of the Sherrington-Kirkpatrick model, and we compute the main finite-size corrections to the difference of the free energy between these two models and to some clarifying order parameters. Our results agree with numerical simulations. Numerical results are presented for the symmetric Little model, which show that the same conclusions are also valid in this case.

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In cells, DNA is routinely subjected to significant levels of bending and twisting. In some cases, such as under physiological levels of supercoiling, DNA can be so highly strained, that it transitions into non-canonical structural conformations that are capable of relieving mechanical stress within the template. DNA minicircles offer a robust model system to study stress-induced DNA structures. Using DNA minicircles on the order of 100 bp in size, we have been able to control the bending and torsional stresses within a looped DNA construct. Through a combination of cryo-EM image reconstructions, Bal31 sensitivity assays and Brownian dynamics simulations, we have been able to analyze the effects of biologically relevant underwinding-induced kinks in DNA on the overall shape of DNA minicircles. Our results indicate that strongly underwound DNA minicircles, which mimic the physical behavior of small regulatory DNA loops, minimize their free energy by undergoing sequential, cooperative kinking at two sites that are located about 180° apart along the periphery of the minicircle. This novel form of structural cooperativity in DNA demonstrates that bending strain can localize hyperflexible kinks within the DNA template, which in turn reduces the energetic cost to tightly loop DNA.

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The binding free energy for the interaction between serines 204 and 207 of the fifth transmembrane helix of the beta(2)-adrenergic receptor (beta(2)-AR) and catecholic hydroxyl (OH) groups of adrenergic agonists was analyzed using double mutant cycles. Binding affinities for catecholic and noncatecholic agonists were measured in wild-type and mutant receptors, carrying alanine replacement of the two serines (S204A, S207A beta(2)-AR), a constitutive activating mutation, or both. The free energy coupling between the losses of binding energy attributable to OH deletion from the ligand and from the receptor indicates a strong interaction (nonadditivity) as expected for a direct binding between the two sets of groups. However, we also measured a significant interaction between the deletion of OH groups from the receptor and the constitutive activating mutation. This suggests that a fraction of the decrease in agonist affinity caused by serine mutagenesis may involve a shift in the conformational equilibrium of the receptor toward the inactive state. Direct measurements using a transient transfection assay confirm this prediction. The constitutive activity of the (S204A, S207A) beta(2)-AR mutant is 50 to 60% lower than that of the wild-type beta(2)-AR. We conclude that S204 and S207 do not only provide a docking site for the agonist, but also control the equilibrium of the receptor between active (R*) and inactive (R) forms.

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Single amino acid substitution is the type of protein alteration most related to human diseases. Current studies seek primarily to distinguish neutral mutations from harmful ones. Very few methods offer an explanation of the final prediction result in terms of the probable structural or functional effect on the protein. In this study, we describe the use of three novel parameters to identify experimentally-verified critical residues of the TP53 protein (p53). The first two parameters make use of a surface clustering method to calculate the protein surface area of highly conserved regions or regions with high nonlocal atomic interaction energy (ANOLEA) score. These parameters help identify important functional regions on the surface of a protein. The last parameter involves the use of a new method for pseudobinding free-energy estimation to specifically probe the importance of residue side-chains to the stability of protein fold. A decision tree was designed to optimally combine these three parameters. The result was compared to the functional data stored in the International Agency for Research on Cancer (IARC) TP53 mutation database. The final prediction achieved a prediction accuracy of 70% and a Matthews correlation coefficient of 0.45. It also showed a high specificity of 91.8%. Mutations in the 85 correctly identified important residues represented 81.7% of the total mutations recorded in the database. In addition, the method was able to correctly assign a probable functional or structural role to the residues. Such information could be critical for the interpretation and prediction of the effect of missense mutations, as it not only provided the fundamental explanation of the observed effect, but also helped design the most appropriate laboratory experiment to verify the prediction results.

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The specific heat, cp, of two amorphous silicon (a-Si) samples has been measured by differential scanning calorimetry in the 100–900K temperature range. When the hydrogen content is reduced by thermal annealing, cp approaches the value of crystalline Si (c-Si). Within experimental accuracy, we conclude that cp of relaxed pure a-Si coincides with that of c-Si. This result is used to determine the enthalpy, entropy, and Gibbs free energy of defect-free relaxed a-Si. Finally, the contribution of structural defects on these quantities is calculated and the melting point of several states of a-Si is predicted

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The objective of this work was to assess the effects of pH and ionic strength upon zinc adsorption, in three highly weathered variable charge soils. Adsorption isotherms were elaborated from batch adsorption experiments, with increasing Zn concentrations (0-80 mg L-1), and adsorption envelopes were constructed through soil samples reactions with 0.01, 0.1 and 1 mol L-1 Ca(NO3)2 solutions containing 5 mg L-1 of Zn, with an increasing pH value from 3 to 8. Driving force of reaction was quantified by Gibbs free energy and separation factor. Isotherms were C-, H- and L-type and experimental results were fitted to nonlinear Langmuir model. Maximum adsorption ranged from 59-810 mg kg-1, and Zn affinity was greater in subsoil (0.13-0.81 L kg-1) than in the topsoil samples (0.01-0.34 L kg-1). Zinc adsorption was favorable and spontaneous, and showed sharply increase (20-90%) in the 4-6 pH range. No effect of ionic strength was observed at pH values below 5, because specific adsorption mechanisms predominated in the 3-5 pH range. Above pH 5, and in subsoil samples, Zn was adsorbed by electrostatic mechanisms, since ionic strength effect was observed. Despite depth and ionic strength effects, Zn adsorption depends mainly on the pH.

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The protein shells, or capsids, of nearly all spherelike viruses adopt icosahedral symmetry. In the present Letter, we propose a statistical thermodynamic model for viral self-assembly. We find that icosahedral symmetry is not expected for viral capsids constructed from structurally identical protein subunits and that this symmetry requires (at least) two internal switching configurations of the protein. Our results indicate that icosahedral symmetry is not a generic consequence of free energy minimization but requires optimization of internal structural parameters of the capsid proteins

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We present a new phenomenological approach to nucleation, based on the combination of the extended modified liquid drop model and dynamical nucleation theory. The new model proposes a new cluster definition, which properly includes the effect of fluctuations, and it is consistent both thermodynamically and kinetically. The model is able to predict successfully the free energy of formation of the critical nucleus, using only macroscopic thermodynamic properties. It also accounts for the spinodal and provides excellent agreement with the result of recent simulations.

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3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.