911 resultados para MOLECULAR-DYNAMICS SIMULATIONS
Resumo:
Rare HFE variants have been shown to be associated with hereditary hemochromatosis (HH), an iron overload disease. The low frequency of the HFE p.C282Y mutation in HH-affected Brazilian patients may suggest that other HFE-related mutations may also be implicated in the pathogenesis of HH in this population. The main aim was to screen for new HFE mutations in Brazilian individuals with primary iron overload and to investigate their relationship with HH. Fifty Brazilian patients with primary iron overload (transferrin saturation >50% in females and 60% in males) were selected. Subsequent bidirectional sequencing for each HFE exon was performed. The effect of HFE mutations on protein structure were analyzed by molecular dynamics simulation and free binding energy calculations. p.C282Y in homozygosis or in heterozygosis with p.H63D were the most frequent genotypic combinations associated with HH in our sample population (present in 17 individuals, 34%). Thirty-six (72.0%) out of the 50 individuals presented at least one HFE mutation. The most frequent genotype associated with HH was the homozygous p.C282Y mutation (n = 11, 22.0%). One novel mutation (p.V256I) was indentified in heterozygosis with the p.H63D mutation. In silico modeling analysis of protein behavior indicated that the p.V256I mutation does not reduce the binding affinity between HFE and beta 2-microglobulin ((beta 2M) in the same way the p.C282Y mutation does compared with the native HFE protein. In conclusion, screening of HFE through direct sequencing, as compared to p.C282Y/p.H63D genotyping, was not able to increase the molecular diagnosis yield of HH. The novel p.V256I mutation could not be implicated in the molecular basis of the HH phenotype, although its role cannot be completely excluded in HH-phenotype development. Our molecular modeling analysis can help in the analysis of novel, previously undescribed, HFE mutations. (C) 2010 Elsevier Inc. All rights reserved.
Resumo:
Phospholipases A(2) (PLA(2)s) are important components of Bothrops snake venoms, that can induce several effects on envenomations such as myotoxicity, inhibition or induction of platelet aggregation and edema. It is known that venomous and non-venomous snakes present PLA(2) inhibitory proteins (PLIs) in their blood plasma. An inhibitory protein that neutralizes the enzymatic and toxic activities of several PLA2s from Bothrops venoms was isolated from Bothrops alternatus snake plasma by affinity chromatography using the immobilized myotoxin BthTX-I on CNBr-activated Sepharose. Biochemical characterization of this inhibitory protein, denominated alpha BaltMIP, showed it to be a glycoprotein with Mr of similar to 24,000 for the monomeric subunit. CD spectra of the PLA(2)/inhibitor complexes are considerably different from those corresponding to the individual proteins and data deconvolution suggests that the complexes had a relative gain of helical structure elements in comparison to the individual protomers, which may indicate a more compact structure upon complexation. Theoretical and experimental structural studies performed in order to obtain insights into the structural features of aBaltMIP indicated that this molecule may potentially trimerize in solution, thus strengthening the hypothesis previously raised by other authors about snake PLIs oligomerization. (C) 2010 Elsevier Masson SAS. All rights reserved.
Resumo:
The Schistosoma mansoni fatty acid binding protein (FABP), SmA, is a vaccine candidate against, S. mansoni and F hepatica. Previously, we demonstrated the importance of a correct fold to achieve protection in immunized animals after cercariae challenge [[10]. C.R.R. Ramos, R.C.R. Figueredo, T.A. Pertinhez, M.M. Vilar, A.L.T.O. Nascimento, M. Tendler, I. Raw, A. Spisni, P.L. Ho, Gene structure and M20T polymorphism of the Schistosoma mansoni Sm14 fatty acid-binding protein: structural, functional and immunoprotection analysis. J. Biol. Chem. 278 (2003) 12745-12751]. Here we show that the reduction of vaccine efficacy over time is due to protein dimerization and subsequent aggregation. We produced the mutants Sm14-M20(C62S) and Sm14M20(C62V) that, as expected, did not dimerize in SDS-PAGE. Molecular dynamics calculations and unfolding experiments highlighted a higher structural stability of these mutants with respect to the wild-type. In addition, we found that the mutated proteins, after thermal denaturation, refolded to their active native molecular architecture as proved by the recovery of the fatty acid binding ability. Sm14-M20(C62V) turned out to be the more stable form over time, providing the basis to determine the first 3D solution structure of a Sm14 protein in its apo-form. Overall, Sm14-M20(C62V) possesses an improved structural stability over time, an essential feature to preserve its immunization capability and, in experimentally immunized animals, it exhibits a protection effect against S. mansoni cercariae infections comparable to the one obtained with the wild-type protein. These facts indicate this protein as a good lead molecule for large-scale production and for developing an effective Sm14 based anti-helminthes vaccine. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
With the constant development of new antibiotics, selective pressure is a force to reckon when investigating antibiotic resistance. Although advantageous for medical treatments, it leads to increasing resistance. It is essential to use more potent and toxic antibiotics. Enzymes capable of hydrolyzing antibiotics are among the most common ways of resistance and TEM variants have been detected in several resistant isolates. Due to the rapid evolution of these variants, complex phenotypes have emerged and the need to understand their biological activity becomes crucial. To investigate the biochemical properties of TEM-180 and TEM-201 several computational methodologies have been used, allowing the comprehension of their structure and catalytic activity, which translates into their biological phenotype. In this work we intent to characterize the interface between these proteins and the several antibiotics used as ligands. We performed explicit solvent molecular dynamics (MD) simulations of these complexes and studied a variety of structural and energetic features. The interfacial residues show a distinct behavior when in complex with different antibiotics. Nevertheless, it was possible to identify some common Hot Spots among several complexes – Lys73, Tyr105 and Glu166. The structural changes that occur during the Molecular Dynamic (MD) simulation lead to the conclusion that these variants have an inherent capacity of adapting to the various antibiotics. This capability might be the reason why they can hydrolyze antibiotics that have not been described until now to be degraded by TEM variants. The results obtained with computational and experimental methodologies for the complex with Imipenem have shown that in order to this type of enzymes be able to acylate the antibiotics, they need to be capable to protect the ligand from water molecules.
Resumo:
Dissertation presented to obtain a Ph.D. degree in Biology, speciality Microbiology, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
Resumo:
This study was developed with the purpose to investigate the effect of polysaccharide/plasticiser concentration on the microstructure and molecular dynamics of polymeric film systems, using transmission electron microscope imaging (TEM) and nuclear magnetic resonance (NMR) techniques. Experiments were carried out in chitosan/glycerol films prepared with solutions of different composition. The films obtained after drying and equilibration were characterised in terms of composition, thickness and water activity. Results show that glycerol quantities used in film forming solutions were responsible for films composition; while polymer/total plasticiser ratio in the solution determined the thickness (and thus structure) of the films. These results were confirmed by TEM. NMR allowed understanding the films molecular rearrangement. Two different behaviours for the two components analysed, water and glycerol were observed: the first is predominantly moving free in the matrix, while glycerol is mainly bounded to the chitosan chain. (C) 2013 Elsevier Ltd. All rights reserved.
Resumo:
Dissertation presented to obtain a Ph.D. Degree in Chemical Physics
Resumo:
A thesis submitted in fulfillment of the requirements for the degree of the Masters in Molecular Genetics and Biomedicine
Resumo:
Astrocytes have recently become a major center of interest in neurochemistry with the discoveries on their major role in brain energy metabolism. An interesting way to probe this glial contribution is given by in vivo (13) C NMR spectroscopy coupled with the infusion labeled glial-specific substrate, such as acetate. In this study, we infused alpha-chloralose anesthetized rats with [2-(13) C]acetate and followed the dynamics of the fractional enrichment (FE) in the positions C4 and C3 of glutamate and glutamine with high sensitivity, using (1) H-[(13) C] magnetic resonance spectroscopy (MRS) at 14.1T. Applying a two-compartment mathematical model to the measured time courses yielded a glial tricarboxylic acid (TCA) cycle rate (Vg ) of 0.27 ± 0.02 μmol/g/min and a glutamatergic neurotransmission rate (VNT ) of 0.15 ± 0.01 μmol/g/min. Glial oxidative ATP metabolism thus accounts for 38% of total oxidative metabolism measured by NMR. Pyruvate carboxylase (VPC ) was 0.09 ± 0.01 μmol/g/min, corresponding to 37% of the glial glutamine synthesis rate. The glial and neuronal transmitochondrial fluxes (Vx (g) and Vx (n) ) were of the same order of magnitude as the respective TCA cycle fluxes. In addition, we estimated a glial glutamate pool size of 0.6 ± 0.1 μmol/g. The effect of spectral data quality on the fluxes estimates was analyzed by Monte Carlo simulations. In this (13) C-acetate labeling study, we propose a refined two-compartment analysis of brain energy metabolism based on (13) C turnover curves of acetate, glutamate and glutamine measured with state of the art in vivo dynamic MRS at high magnetic field in rats, enabling a deeper understanding of the specific role of glial cells in brain oxidative metabolism. In addition, the robustness of the metabolic fluxes determination relative to MRS data quality was carefully studied.
Resumo:
Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.
A variational approach for calculating Franck-Condon factors including mode-mode anharmonic coupling
Resumo:
We have implemented our new procedure for computing Franck-Condon factors utilizing vibrational configuration interaction based on a vibrational self-consistent field reference. Both Duschinsky rotations and anharmonic three-mode coupling are taken into account. Simulations of the first ionization band of Cl O2 and C4 H4 O (furan) using up to quadruple excitations in treating anharmonicity are reported and analyzed. A developer version of the MIDASCPP code was employed to obtain the required anharmonic vibrational integrals and transition frequencies
Resumo:
The electron hole transfer (HT) properties of DNA are substantially affected by thermal fluctuations of the π stack structure. Depending on the mutual position of neighboring nucleobases, electronic coupling V may change by several orders of magnitude. In the present paper, we report the results of systematic QM/molecular dynamic (MD) calculations of the electronic couplings and on-site energies for the hole transfer. Based on 15 ns MD trajectories for several DNA oligomers, we calculate the average coupling squares 〈 V2 〉 and the energies of basepair triplets X G+ Y and X A+ Y, where X, Y=G, A, T, and C. For each of the 32 systems, 15 000 conformations separated by 1 ps are considered. The three-state generalized Mulliken-Hush method is used to derive electronic couplings for HT between neighboring basepairs. The adiabatic energies and dipole moment matrix elements are computed within the INDO/S method. We compare the rms values of V with the couplings estimated for the idealized B -DNA structure and show that in several important cases the couplings calculated for the idealized B -DNA structure are considerably underestimated. The rms values for intrastrand couplings G-G, A-A, G-A, and A-G are found to be similar, ∼0.07 eV, while the interstrand couplings are quite different. The energies of hole states G+ and A+ in the stack depend on the nature of the neighboring pairs. The X G+ Y are by 0.5 eV more stable than X A+ Y. The thermal fluctuations of the DNA structure facilitate the HT process from guanine to adenine. The tabulated couplings and on-site energies can be used as reference parameters in theoretical and computational studies of HT processes in DNA
Resumo:
Bimodal dispersal probability distributions with characteristic distances differing by several orders of magnitude have been derived and favorably compared to observations by Nathan [Nature (London) 418, 409 (2002)]. For such bimodal kernels, we show that two-dimensional molecular dynamics computer simulations are unable to yield accurate front speeds. Analytically, the usual continuous-space random walks (CSRWs) are applied to two dimensions. We also introduce discrete-space random walks and use them to check the CSRW results (because of the inefficiency of the numerical simulations). The physical results reported are shown to predict front speeds high enough to possibly explain Reid's paradox of rapid tree migration. We also show that, for a time-ordered evolution equation, fronts are always slower in two dimensions than in one dimension and that this difference is important both for unimodal and for bimodal kernels
Resumo:
The adrenergic receptors (ARs) belong to the superfamily of membrane-bound G protein coupled receptors (GPCRs). Our investigation has focused on the structure-function relationship of the alpha 1b-AR subtype used as the model system for other GPCRs. Site-directed mutagenesis studies have elucidated the structural domains of the alpha 1b-AR involved in ligand binding, G protein coupling or desensitization. In addition, a combined approach using site-directed mutagenesis and molecular dynamics analysis of the alpha 1b-AR has provided information about the potential mechanisms underlying the activation process of the receptor, i.e. its transition from the 'inactive' to the 'active' conformation.
Resumo:
Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.