902 resultados para molecular dynamics


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This paper aims to develop an effective numerical simulation technique for the dynamic deflection analysis of nanotubes-based nanoswitches. The nanoswitch is simplified to a continuum structure, and some key material parameters are extracted from typical molecular dynamics (MD). An advanced local meshless formulation is applied to obtain the discretized dynamic equations for the numerical solution. The developed numerical technique is firstly validated by the static deflection analyses of nanoswitches, and then, the fundamental dynamic properties of nanoswitches are analyzed. A parametric comparison with the results in the literature and from experiments shows that the developed modelling approach is accurate, efficient and effective.

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The mechanical vibration properties of single actin filaments from 50 to 288 nm are investigated by the molecular dynamics simulation in this study. The natural frequencies obtained from the molecular simulations agree with those obtained from the analytical solution of the equivalent Euler–Bernoulli beam model. Through the convergence study of the mechanical properties with respect to the filament length, it was found that the Euler–Bernoulli beam model can only be reliably used when the single actin filament is of the order of hundreds of nanometre scale. This molecular investigation not only provides the evidence for the use of the continuum beam model in characterising the mechanical properties of single actin filaments, but also clarifies the criteria for the effective use of the Euler–Bernoulli beam model.

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The majority of patients with non-small-cell lung cancer (NSCLC) present with advanced disease, with targeted therapies providing some improvement in clinical outcomes. The epidermal growth factor receptor (EGFR) tyrosine kinase (TK) plays an important role in the pathogenesis of NSCLC. Tyrosine kinase inhibitors (TKIs), which target the EGFR TK domain, have proven to be an effective treatment strategy; however, patient responses to treatment vary considerably. Therefore, the identification of patients most likely to respond to treatment is essential to optimise the benefit of TKIs. Tumour-associated activating mutations in EGFR can identify patients with NSCLC who are likely to have a good response to TKIs. Nonetheless, the majority of patients relapse within a year of starting treatment. Studies of tumours at relapse have demonstrated expression of a T790M mutation in exon 20 of the EGFR TK domain in approximately 50% of cases. Although conferring resistance to reversible TKIs, these patients may remain sensitive to new-generation irreversible/panerb inhibitors. A number of techniques have been employed for genotypic assessment of tumourassociated DNA to identify EGFR mutations, each of which has advantages and disadvantages. This review presents an overview of the current methodologies used to identify such molecular markers. Recent developments in technology may make the monitoring of changes in patients' tumour genotypes easier in clinical practice, which may enable patients' treatment regimens to be tailored during the course of their disease, potentially leading to improved patient outcomes.

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Dynamic light scattering (DLS) has become a primary nanoparticle characterization technique with applications from materials characterization to biological and environmental detection. With the expansion in DLS use from homogeneous spheres to more complicated nanostructures, comes a decrease in accuracy. Much research has been performed to develop different diffusion models that account for the vastly different structures but little attention has been given to the effect on the light scattering properties in relation to DLS. In this work, small (core size < 5 nm) core-shell nanoparticles were used as a case study to measure the capping thickness of a layer of dodecanethiol (DDT) on Au and ZnO nanoparticles by DLS. We find that the DDT shell has very little effect on the scattering properties of the inorganic core and hence can be ignored to a first approximation. However, this results in conventional DLS analysis overestimating the hydrodynamic size in the volume and number weighted distributions. By introducing a simple correction formula that more accurately yields hydrodynamic size distributions a more precise determination of the molecular shell thickness is obtained. With this correction, the measured thickness of the DDT shell was found to be 7.3 ± 0.3 Å, much less than the extended chain length of 16 Å. This organic layer thickness suggests that on small nanoparticles, the DDT monolayer adopts a compact disordered structure rather than an open ordered structure on both ZnO and Au nanoparticle surfaces. These observations are in agreement with published molecular dynamics results.

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The kaolinite (Kaol) intercalated with potassium acetate (Ac) was prepared and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetry. Molecular dynamic simulation was performed to investigate the structure of Kaol–Ac intercalation complex and the hydrogen bonds between Kaol and intercalated Ac andwater using INTERFACE forcefield. The acetate anions andwater arranged in a bilayer structure in the interlayer space of Kaol. The potassium cations distributed in the interlayer space and strongly coordinated with acetate anions aswell aswater rather than keyed into the ditrigonal holes of tetrahedral surface of Kaol. Strong hydrogen bonds formed between the hydrogen atoms of hydroxyl on the octahedral surface and oxygen atoms of both acetate anions and water. The acetate anions andwater also weakly bonded hydrogen to the silica tetrahedral surface through their hydrogen atoms with the oxygen atoms of silica tetrahedral surface.

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Communication within and across proteins is crucial for the biological functioning of proteins. Experiments such as mutational studies on proteins provide important information on the amino acids, which are crucial for their function. However, the protein structures are complex and it is unlikely that the entire responsibility of the function rests on only a few amino acids. A large fraction of the protein is expected to participate in its function at some level or other. Thus, it is relevant to consider the protein structures as a completely connected network and then deduce the properties, which are related to the global network features. In this direction, our laboratory has been engaged in representing the protein structure as a network of non-covalent connections and we have investigated a variety of problems in structural biology, such as the identification of functional and folding clusters, determinants of quaternary association and characterization of the network properties of protein structures. We have also addressed a few important issues related to protein dynamics, such as the process of oligomerization in multimers, mechanism on protein folding, and ligand induced communications (allosteric effect). In this review we highlight some of the investigations which we have carried out in the recent past. A review on protein structure graphs was presented earlier, in which the focus was on the graphs and graph spectral properties and their implementation in the study of protein structure graphs/networks (PSN). In this article, we briefly summarize the relevant parts of the methodology and the focus is on the advancement brought out in the understanding of protein structure-function relationships through structure networks. The investigations of structural/biological problems are divided into two parts, in which the first part deals with the analysis of PSNs based on static structures obtained from x-ray crystallography. The second part highlights the changes in the network, associated with biological functions, which are deduced from the network analysis on the structures obtained from molecular dynamics simulations.

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The role of invariant water molecules in the activity of plant cysteine protease is ubiquitous in nature. On analysing the 11 different Protein DataBank (PDB) structures of plant thiol proteases, the two invariant water molecules W I and W2 (W220 and W222 in the template 1PPN structure) were observed to form H-bonds with the Ob atom of Asn 175. Extensive energy minimization and molecular dynamics simulation studies up to 2 ns on all the PDB and solvated structures clearly revealed the involvement of the H-bonding association of the two water molecules in fixing the orientation of the asparagine residue of the catalytic triad. From this study, it is suggested that H-bonding of the water molecule at the W1 invariant site better stabilizes the Asn residue at the active site of the catalytic triad.

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Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

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Homodimeric protein tryptophanyl tRNA synthetase (TrpRS) has a Rossmann fold domain and belongs to the 1c subclass of aminoacyl tRNA synthetases. This enzyme performs the function of acylating the cognate tRNA. This process involves a number of molecules (2 protein subunits, 2 tRNAs and 2 activated Trps) and thus it is difficult to follow the complex steps in this process. Structures of human TrpRS complexed with certain ligands are available. Based on structural and biochemical data, mechanism of activation of Trp has been speculated. However, no structure has yet been solved in the presence of both the tRNA(Trp) and the activated Trp (TrpAMP). In this study, we have modeled the structure of human TrpRS bound to the activated ligand and the cognate tRNA. In addition, we have performed molecular dynamics (MD) simulations on these models as well as other complexes to capture the dynamical process of ligand induced conformational changes. We have analyzed both the local and global changes in the protein conformation from the protein structure network (PSN) of MD snapshots, by a method which was recently developed in our laboratory in the context of the functionally monomeric protein, methionyl tRNA synthetase. From these investigations, we obtain important information such as the ligand induced correlation between different residues of this protein, asymmetric binding of the ligands to the two subunits of the protein as seen in the crystal structure analysis, and the path of communication between the anticodon region and the aminoacylation site. Here we are able to elucidate the role of dimer interface at a level of detail, which has not been captured so far.

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Nuclear magnetic resonance (NMR) spectroscopy provides us with many means to study biological macromolecules in solution. Proteins in particular are the most intriguing targets for NMR studies. Protein functions are usually ascribed to specific three-dimensional structures but more recently tails, long loops and non-structural polypeptides have also been shown to be biologically active. Examples include prions, -synuclein, amylin and the NEF HIV-protein. However, conformational preferences in coil-like molecules are difficult to study by traditional methods. Residual dipolar couplings (RDCs) have opened up new opportunities; however their analysis is not trivial. Here we show how to interpret RDCs from these weakly structured molecules. The most notable residual dipolar couplings arise from steric obstruction effects. In dilute liquid crystalline media as well as in anisotropic gels polypeptides encounter nematogens. The shape of a polypeptide conformation limits the encounter with the nematogen. The most elongated conformations may come closest whereas the most compact remain furthest away. As a result there is slightly more room in the solution for the extended than for the compact conformations. This conformation-dependent concentration effect leads to a bias in the measured data. The measured values are not arithmetic averages but essentially weighted averages over conformations. The overall effect can be calculated for random flight chains and simulated for more realistic molecular models. Earlier there was an implicit thought that weakly structured or non-structural molecules would not yield to any observable residual dipolar couplings. However, in the pioneering study by Shortle and Ackerman RDCs were clearly observed. We repeated the study for urea-denatured protein at high temperature and also observed indisputably RDCs. This was very convincing to us but we could not possibly accept the proposed reason for the non-zero RDCs, namely that there would be some residual structure left in the protein that to our understanding was fully denatured. We proceeded to gain understanding via simulations and elementary experiments. In measurements we used simple homopolymers with only two labelled residues and we simulated the data to learn more about the origin of RDCs. We realized that RDCs depend on the position of the residue as well as on the length of the polypeptide. Investigations resulted in a theoretical model for RDCs from coil-like molecules. Later we extended the studies by molecular dynamics. Somewhat surprisingly the effects are small for non-structured molecules whereas the bias may be large for a small compact protein. All in all the work gave clear and unambiguous results on how to interpret RDCs as structural and dynamic parameters of weakly structured proteins.

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The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of llostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein esponsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.

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Molecular dynamics investigation of benzene in one-dimensional channel systems A1PO(4)-5, VPI-5, and carbon nanotube is reported. The results suggest that, in all the three host systems, the plane of benzene is almost perpendicular to the channel axis when the molecule is near the center of the channel and the plane of benzene is parallel to the channel axis when the molecule is near the wall of the channel. The density distribution of benzene as a function of channel length, z and the radial distance, r, from the channel axis is also different in the three host structures. Anisotropy in translational diffusion coefficient, calculated in body-fixed frame of benzene, suggests that benzene prefers to move with its plane parallel to the direction of motion in A1PO(4)-5 and VPI-5 whereas in carbon nanotube the motion occurs predominantly with the plane of the benzene perpendicular to the direction of motion.;Anisotropy associated with the rotational motion is seen to alter significantly in confinement as compared to liquid benzene. In A1PO(4)-5, the rotational anisotropy is reversed as compared to liquid benzene thereby suggesting that anisotropy arising out of molecular geometry can be reduced. Reorientational correlation times for C-6 and C-2 axes Of benzene are reported. Apart from the inertial decay of reorientational correlation function due to free, rotation, two other distinct regimes of decay are observed in narrower channels (AIPO(4)-5 and carbon nanotube): (i) an initial fast decay (0.5-2 ps) and (ii) a slower decay (>2 ps) of reorientational correlation function where C-6 decays slower than C-2 Similar to what is observed in liquid benzene. In the initial fast decay, it is seen that the decay for C-6 is faster than C-2 which is in contrast to what is observed in liquid benzene or for benzene confined in VPI-5.

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This paper reports the structural behavior and thermodynamics of the complexation of siRNA with poly(amidoamine) (PAMAM) dendrimers of generation 3 (G3) and 4 (G4) through fully atomistic molecular dynamics (MD) simulations accompanied by free energy calculations and inherent structure determination. We have also done simulation with one siRNA and two dendrimers (2 x G3 or 2xG4) to get the microscopic picture of various binding modes. Our simulation results reveal the formation of stable siRNA-dendrimer complex over nanosecond time scale. With the increase in dendrimcr generation, the charge ratio increases and hence the binding energy between siRNA and dendrimer also increases in accordance with available experimental measurements. Calculated radial distribution functions of amines groups of various subgenerations in a given generation of dendrimer and phosphate in backbone of siRNA reveals that one dendrimer of generation 4 shows better binding with siRNA almost wrapping the dendrimer when compared to the binding with lower generation dendrimer like G3. In contrast, two dendrimers of generation 4 show binding without siRNA wrapping the den-rimer because of repulsion between two dendrimers. The counterion distribution around the complex and the water molecules in the hydration shell of siRNA give microscopic picture of the binding dynamics. We see a clear correlation between water. counterions motions and the complexation i.e. the water molecules and counterions which condensed around siRNA are moved away from the siRNA backbone when dendrimer start binding to the siRNA back hone. As siRNA wraps/bind to the dendrimer counterions originally condensed onto siRNA (Na-1) and dendrimer (Cl-) get released. We give a quantitative estimate of the entropy of counterions and show that there is gain in entropy due to counterions release during the complexation. Furthermore, the free energy of complexation of IG3 and IG4 at two different salt concentrations shows that increase in salt concentration leads to the weakening of the binding affinity of siRNA and dendrimer.

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Molecular dynamics simulation studies on polyene antifungal antibiotic amphotericin B, its head-to-tail dimeric structure and lipid - amphotericin B complex demonstrate interesting features of the flexibilities within the molecule and define the optimal interactions for the formation of a stable dimeric structure and complex with phospholipid.

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Recent computer simulations on zeolites Y and A have found that the diffusion coefficient and the rate of intercage diffusion exhibit, apart from a linear dependence on the reciprocal of the square of the sorbate diameter, an anomalous peak as sorbate diameter approaches the window diameter. Here we report molecular dynamics simulations of zeolite NaA incorporating framework flexibility as a function of sorbate diameter in order to verify the existence of anomalous diffusion. Results suggest persistence of anomalous diffusion or ring effect. This suggests that the anomalous behavior is a general effect characteristic of zeolites Y and A. The barrier for diffusion across the eight-ring window is seen to be negative and is found to decrease with sorbate size. The effect of sorbate on the cage motion has also been investigated. Results suggest that the window expands during intercage migration only if the sorbate size is comparable to the window diameter. Flexible cage simulations yield a higher value for the diffusion coefficient and also the rate of intercage diffusion. This increase has been shown to be due to an increase in the intercage diffusions via the centralized diffusion mode rather than the surface-mediated mode. It is shown that this increase arises from an increase in the single particle density distribution in the region near the cage center.