The dielectric properties of proteins are central to their stability and activity. We use the Frohlich- are roughly those of a homogeneous, isotropic dielectric medium, with a dielectric constant of 4.7 + 1.0 (ferro) or 3.4 + 1.0 (ferri), in agreement with powder experiments. Statistical uncertainty and sensitivity to model parameters are small. Analysis of the radial dependence of the dipole fluctuations suggests that the inner half of the protein has a somewhat lower dielectric constant of 1.5-2, consistent with its biological function in electron transfer. These results suggest that Poisson-Boltzmann models could treat the protein bulk as a low-dielectric medium and the charged surface groups as part of the solvent region.

In this paper we reformulate and extend a method proposed recently for estimating the classical configurational entropy difference between molecular conformations of proteins from molecular dynamics simulations. The method involves a quasi-harmonic oscillator approximation, in which a temperature-dependent (quasi-harmonic) Hamiltonian for the system is parameterized from a detailed computer simulation. The quasi-harmonic potential function is assumed to have a quadratic form with the coefficients chosen so that the mean square fluctuations of the coordinates evaluated from an ensemble average within the harmonic approximation have the same values as the results obtained from a molecular dynamics trajectory on the complete anharmonic potential surface, while the quasi-harmonic kinetic energy function is similar to the standard harmonic expression. It is shown that with the quasi-harmonic Hamiltonian, the effective vibrational frequencies and normal modes can be obtained. This makes possible a detailed comparison with the results obtained from the harmonic approximation and provides a simple procedure for estimating the quantum corrections to thermodynamic properties. The results of vibrational normal mode and molecular dynamics simulations for a polypeptide -helix are used to calculate the harmonic and quasi-harmonic approximations to the entropy of this model system at three temperatures, 5, 100, and 300 K. The entropy difference AS between the two sets of calculations provides an estimate of the importance of anharmonicity in the determination of the configurational entropy.

Antidepressant prescribing patterns and factors influencing the choice of antidepressant for the treatment of depression were examined in the Factors Influencing Depression Endpoints Research (FINDER) study, a prospective, observational study in 12 European countries of 3468 adults about to start antidepressant medication for their first episode of depression or a new episode of recurrent depression. Selective serotonin reuptake inhibitors (SSRIs) were the most commonly prescribed antidepressant (63.3% patients), followed by serotonin-norepinephrine reuptake inhibitors (SNRIs, 13.6%), but there was considerable variation across countries. Notably, tricyclic and tetracyclic antidepressants (TCAs) were prescribed for 26.5% patients in Germany. The choice of the antidepressant prescribed was strongly influenced by the previous use of antidepressants, which was significantly associated with the prescription of a SSRI (OR 0.64; 95% CI 0.54, 0.76), a SNRI (OR 1.49; 95% CI 1.18, 1.88) or a combination of antidepressants (OR 2.78; 95% CI 1.96, 3.96). Physician factors (age, gender, speciality) and patient factors (severity of depression, age, education, smoking, number of current physical conditions and functional syndromes) were associated with initial antidepressant choice in some models. In conclusion, the prescribing of antidepressants varies by country, and the type of antidepressant chosen is influenced by physician- as well as patient-related factors.

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How G protein-coupled receptor conformational dynamics control G protein coupling to trigger signaling is a key but still open question. We addressed this question with a model system composed of the purified ghrelin receptor assembled into lipid discs. Combining receptor labeling through genetic incorporation of unnatural amino acids, lanthanide resonance energy transfer, and normal mode analyses, we directly demonstrate the occurrence of two distinct receptor:Gq assemblies with different geometries whose relative populations parallel the activation state of the receptor. The first of these assemblies is a preassembled complex with the receptor in its basal conformation. This complex is specific of Gq and is not observed with Gi. The second one is an active assembly in which the receptor in its active conformation triggers G protein activation. The active complex is present even in the absence of agonist, in a direct relationship with the high constitutive activity of the ghrelin receptor. These data provide direct evidence of a mechanism for ghrelin receptor-mediated Gq signaling in which transition of the receptor from an inactive to an active conformation is accompanied by a rearrangement of a preassembled receptor:G protein complex, ultimately leading to G protein activation and signaling.GPCR | G protein | preassembly | conformation dynamics | signaling G protein-coupled receptors (GPCRs), one of the largest cell surface receptor families, are involved in many cellular signaling processes (1). Based on this property, as well as their importance as drug targets, the molecular aspects of GPCR functioning have been extensively investigated. In particular, coupling to heterotrimeric G proteins has been the focus of numerous studies. Indeed, delineating the molecular mechanisms responsible for receptor:G protein interaction is absolutely required to better understand how signaling is controlled. Recent years have seen spectacular advances that have culminated in elucidation of the 3D structure of the β 2 -adrenergic receptor:Gs complex (2). Nevertheless, the need for further progress remains, in particular to fully understand the dynamics of this interaction. This is a crucial question, given that how the receptor interacts with its G protein partner governs signaling, and thus biological and pathophysiological responses.To date, two different models for GPCR:G protein interaction have been proposed: collision coupling and preassembly. Originally, it was proposed that receptors and G proteins couple by collision (3, 4). One of the main features of this model is that only activated receptors interact with G proteins. Since then, alternative models of signaling have been developed. One of these, the preassembly model, proposes that the receptor and the G protein make a complex even in the absence of agonist (5-8).

The type III receptor tyrosine kinase (RTK) KIT plays a crucial role in the transmission of cellular signals through phosphorylation events that are associated with a switching of the protein conformation between inactive and active states. D816V KIT mutation is associated with various pathologies including mastocytosis and cancers. D816V-mutated KIT is constitutively active, and resistant to treatment with the anti-cancer drug Imatinib. To elucidate the activating molecular mechanism of this mutation, we applied a multi-approach procedure combining molecular dynamics (MD) simulations, normal modes analysis (NMA) and binding site prediction. Multiple 50-ns MD simulations of wild-type KIT and its mutant D816V were recorded using the inactive auto-inhibited structure of the protein, characteristic of type III RTKs. Computed free energy differences enabled us to quantify the impact of D816V on protein stability in the inactive state. We evidenced a local structural alteration of the activation loop (A-loop) upon mutation, and a long-range structural re-organization of the juxta-membrane region (JMR) followed by a weakening of the interaction network with the kinase domain. A thorough normal mode analysis of several MD conformations led to a plausible molecular rationale to propose that JMR is able to depart its auto-inhibitory position more easily in the mutant than in wild-type KIT and is thus able to promote kinase mutant dimerization without the need for extra-cellular ligand binding. Pocket detection at the surface of NMA-displaced conformations finally revealed that detachment of JMR from the kinase domain in the mutant was sufficient to open an access to the catalytic and substrate binding sites.

This paper investigates the microscopic mechanisms of charge screening in proteins. The screening of an arbitrary perturbing charge density by a protein and its surrounding solution is characterized by a generalized susceptibility, which is approximately given by the mean dipole-dipole correlation matrix of the system. This susceptibility is a microscopic quantity; the sum of its matrix elements gives the macroscopic susceptibility of continuum electrostatics. When screening of a single perturbing point charge is considered, this susceptibility reduces to a scalar quantity, dependent on position within the protein. The contribution of the positional degrees of freedom of the protein atoms can be estimated from molecular dynamics simulations. This contribution gives rise to large spatial variations of the susceptibility, whose significance for protein function is discussed. The model is applied to the small alpha helix deca-alanine, and to the electron-transfer protein cytochrome c. The results agree qualitatively with previous normal mode calculations. The importance, and the large spatial variations, of charge screening by deca-alanine suggest that dielectric screening may play a role in the binding of charged ligands by helices. In cytochrome c, the dielectric susceptibility in response to a point charge is at a minimum in the central heme region, resulting in a lowering of the reorganization free energy for charge transfer to and from the heme.

Proteins are found in solution as ensembles of conformations in dynamic equilibrium. Exploration of functional motions occurring on micro- to millisecond time scales by molecular dynamics (MD) simulations still remains computationally challenging. Alternatively, normal mode (NM) analysis is a well-suited method to characterize intrinsic slow collective motions, often associated with protein function, but the absence of anharmonic effects preclude a proper characterization of conformational distributions in a multidimensional NM space. Using both methods jointly appears to be an attractive approach that allows an extended sampling of the conformational space. In line with this view, the MDeNM (molecular dynamics with excited normal modes) method presented here consists of multiple-replica short MD simulations in which motions described by a given subset of low-frequency NMs are kinetically excited. This is achieved by adding additional atomic velocities along several randomly determined linear combinations of NM vectors, thus allowing an efficient coupling between slow and fast motions. The relatively high-energy conformations generated with MDeNM are further relaxed with standard MD simulations, enabling free energy landscapes to be determined. Two widely studied proteins were selected as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM provides a larger extent of sampling in a few nanoseconds, outperforming long standard MD simulations. A high degree of correlation with motions inferred from experimental sources (X-ray, EPR, and NMR) and with free energy estimations obtained by metadynamics was observed. Finally, the large sets of conformations obtained with MDeNM can be used to better characterize relevant dynamical populations, allowing for a better interpretation of experimental data such as SAXS curves and NMR spectra.