Molecular modelling studies of binding of DACD derivatives into G-Quadruplex DNA: comparison of force field and quantum polarized ligand docking methods

The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.

Predicting metal-binding site residues in low-resolution structural models

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.

Automatic prediction of functional site regions in low-resolution protein structures

World-wide structural genomics initiatives are rapidly accumulating structures for which limited functional information is available. Additionally, state-of-the art structural prediction programs are now capable of generating at least low resolution structural models of target proteins. Accurate detection and classification of functional sites within both solved and modelled protein structures therefore represents an important challenge. We present a fully automatic site detection method, FuncSite, that uses neural network classifiers to predict the location and type of functionally important sites in protein structures. The method is designed primarily to require only backbone residue positions without the need for specific side-chain atoms to be present. In order to highlight effective site detection in low resolution structural models FuncSite was used to screen model proteins generated using mGenTHREADER on a set of newly released structures. We found effective metal site detection even for moderate quality protein models illustrating the robustness of the method.

A data assimilation method for using low-resolution Earth observation data in heterogeneous ecosystems

We present an approach for dealing with coarse-resolution Earth observations (EO) in terrestrial ecosystem data assimilation schemes. The use of coarse-scale observations in ecological data assimilation schemes is complicated by spatial heterogeneity and nonlinear processes in natural ecosystems. If these complications are not appropriately dealt with, then the data assimilation will produce biased results. The “disaggregation” approach that we describe in this paper combines frequent coarse-resolution observations with temporally sparse fine-resolution measurements. We demonstrate the approach using a demonstration data set based on measurements of an Arctic ecosystem. In this example, normalized difference vegetation index observations are assimilated into a “zero-order” model of leaf area index and carbon uptake. The disaggregation approach conserves key ecosystem characteristics regardless of the observation resolution and estimates the carbon uptake to within 1% of the demonstration data set “truth.” Assimilating the same data in the normal manner, but without the disaggregation approach, results in carbon uptake being underestimated by 58% at an observation resolution of 250 m. The disaggregation method allows the combination of multiresolution EO and improves in spatial resolution if observations are located on a grid that shifts from one observation time to the next. Additionally, the approach is not tied to a particular data assimilation scheme, model, or EO product and can cope with complex observation distributions, as it makes no implicit assumptions of normality.

Mode of operation and low-resolution structure of a multi-domain and hyperthermophilic endo-beta-1,3-glucanase from Thermotoga petrophila

1,3-beta-Glucan depolymerizing enzymes have considerable biotechnological applications including biofuel production, feedstock-chemicals and pharmaceuticals. Here we describe a comprehensive functional characterization and low-resolution structure of a hyperthermophilic laminarinase from Thermotoga petrophila (TpLam). We determine TpLam enzymatic mode of operation, which specifically cleaves internal beta-1,3-glucosidic bonds. The enzyme most frequently attacks the bond between the 3rd and 4th residue from the non-reducing end, producing glucose, laminaribiose and laminaritriose as major products. Far-UV circular dichroism demonstrates that TpLam is formed mainly by beta structural elements, and the secondary structure is maintained after incubation at 90 degrees C. The structure resolved by small angle X-ray scattering, reveals a multi-domain structural architecture of a V-shape envelope with a catalytic domain flanked by two carbohydrate-binding modules. Crown Copyright (C) 2011 Published by Elsevier Inc. All rights reserved.

Low-Resolution Molecular Models Reveal the Oligomeric State of the PPAR and the Conformational Organization of Its Domains in Solution

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimal space manoeuvres in a non-Keplerian force field

In this work the problem of a spacecraft bi-impulsive transfer between two given non coplanar elliptical orbits, with minimum fuel consumption, is solved considering a non-Keplerian force field (the perturbing forces include Earth gravity harmonics and atmospheric drag). The problem is transformed in the Two Point Boundary Value Problem. It is developed and implemented a new algorithm, that uses the analytical expressions developed here. A dynamics that considered a Keplerian force field was used to produce an initial guess to solve the Two Point Boundary Value Problem. Several simulations were performed to observe the spacecraft orbital behaviour by different kind of perturbations and constraints, on a fuel consumption optimization point of view. (C) 2002 COSPAR. Published by Elsevier B.V. Ltd. All rights reserved.

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceum ATCC 12472

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field.

H-1 low- and high-field NMR study of the effects of plasma treatment on the oil and water fractions in crude heavy oil

The chemical and physical properties of a Brazilian heavy oil submitted to plasma treatment were investigated by H-1 low-and high-field nuclear magnetic resonance (NMR) combined to the characterization of rheological properties, thermogravimetry and measurement of basic sediments and water (BSW) content. The crude oil was treated in a dielectric barrier discharge plasma reactor, using natural gas, CO2 or H-2 as working gas. The results indicated a large drop in the water content of the plasma-treated samples as compared to the crude oil, giving rise to a reduction in the viscosity. No significant chemical change was produced in the oil portion itself, as observed by H-1 NMR. The water contents determined by H-1 low-field NMR analyses agreed well with those obtained by BSW, indicating the low-field NMR methods as a useful tool for following the effects of plasma treatments on heavy oils, allowing the separation of the effects caused on the water and oil fractions. (C) 2011 Elsevier Ltd. All rights reserved.

Low resolution structural characterization of the Hsp70-interacting protein - Hip - from Leishmania braziliensis emphasizes its high asymmetry

The Hsp70 is an essential molecular chaperone in protein metabolism since it acts as a pivot with other molecular chaperone families. Several co-chaperones act as regulators of the Hsp70 action cycle, as for instance Hip (Hsp70-interacting protein). Hip is a tetratricopeptide repeat protein (TPR) that interacts with the ATPase domain in the Hsp70-ADP state, stabilizing it and preventing substrate dissociation. Molecular chaperones from protozoans, which can cause some neglected diseases, are poorly studied in terms of structure and function. Here, we investigated the structural features of Hip from the protozoa Leishmania braziliensis (LbHip), one of the causative agents of the leishmaniasis disease. LbHip was heterologously expressed and purified in the folded state, as attested by circular dichroism and intrinsic fluorescence emission techniques. LbHip forms an elongated dimer, as observed by analytical gel filtration chromatography, analytical ultracentrifugation and small angle X-ray scattering (SAXS). With the SAXS data a low resolution model was reconstructed, which shed light on the structure of this protein, emphasizing its elongated shape and suggesting its domain organization. We also investigated the chemical-induced unfolding behavior of LbHip and two transitions were observed. The first transition was related to the unfolding of the TPR domain of each protomer and the second transition of the dimer dissociation. Altogether. LbHip presents a similar structure to mammalian Hip, despite their low level of conservation, suggesting that this class of eukaryotic protein may use a similar mechanism of action. (C) 2012 Elsevier Inc. All rights reserved.

Low-Resolution Molecular Models Reveal the Oligomeric State of the PPAR and the Conformational Organization of Its Domains in Solution

The peroxisome proliferator-activated receptors (PPARs) regulate genes involved in lipid and carbohydrate metabolism, and are targets of drugs approved for human use. Whereas the crystallographic structure of the complex of full length PPAR gamma and RXR alpha is known, structural alterations induced by heterodimer formation and DNA contacts are not well understood. Herein, we report a small-angle X-ray scattering analysis of the oligomeric state of hPPAR gamma alone and in the presence of retinoid X receptor (RXR). The results reveal that, in contrast with other studied nuclear receptors, which predominantly form dimers in solution, hPPAR gamma remains in the monomeric form by itself but forms heterodimers with hRXR alpha. The low-resolution models of hPPAR gamma/RXR alpha complexes predict significant changes in opening angle between heterodimerization partners (LBD) and extended and asymmetric shape of the dimer (LBD-DBD) as compared with X-ray structure of the full-length receptor bound to DNA. These differences between our SAXS models and the high-resolution crystallographic structure might suggest that there are different conformations of functional heterodimer complex in solution. Accordingly, hydrogen/deuterium exchange experiments reveal that the heterodimer binding to DNA promotes more compact and less solvent-accessible conformation of the receptor complex.

Multiple stellar populations in globular clusters with photometry and low resolution spectroscopy

Our view of Globular Clusters has deeply changed in the last decade. Modern spectroscopic and photometric data have conclusively established that globulars are neither coeval nor monometallic, reopening the issue of the formation of such systems. Their formation is now schematized as a two-step process, during which the polluted matter from the more massive stars of a first generation gives birth, in the cluster innermost regions, to a second generation of stars with the characteristic signature of fully CNO-processed matter. To date, star-to-star variations in abundances of the light elements (C, N, O, Na) have been observed in stars of all evolutionary phases in all properly studied Galactic globular clusters. Multiple or broad evolutionary sequences have also been observed in nearly all the clusters that have been observed with good signal-to-noise in the appropriate photometric bands. The body of evidence suggests that spreads in light-element abundances can be fairly well traced by photometric indices including near ultraviolet passbands, as CNO abundance variations affect mainly wavelengths shorter than ~400 nm owing to the rise of some NH and CN molecular absorption bands. Here, we exploit this property of near ultraviolet photometry to trace internal chemical variations and combined it with low resolution spectroscopy aimed to derive carbon and nitrogen abundances in order to maximize the information on the multiple populations. This approach has been proven to be very effective in (i) detecting multiple population, (ii) characterizing their global properties (i.e., relative fraction of stars, location in the color-magnitude diagram, spatial distribution, and trends with cluster parameters) and (iii) precisely tagging their chemical properties (i.e., extension of the C-N anticorrelation, bimodalities in the N content).

Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.