Efficient mining of discriminative molecular fragments

Frequent pattern discovery in structured data is receiving an increasing attention in many application areas of sciences. However, the computational complexity and the large amount of data to be explored often make the sequential algorithms unsuitable. In this context high performance distributed computing becomes a very interesting and promising approach. In this paper we present a parallel formulation of the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The application is characterized by a highly irregular tree-structured computation. No estimation is available for task workloads, which show a power-law distribution in a wide range. The proposed approach allows dynamic resource aggregation and provides fault and latency tolerance. These features make the distributed application suitable for multi-domain heterogeneous environments, such as computational Grids. The distributed application has been evaluated on the well known National Cancer Institute’s HIV-screening dataset.

Selective and highly efficient dye scavenging by a pH-responsive molecular hydrogelator

A structurally simple low molecular weight hydrogelator derived from isophthalic acid forms robust pH-responsive hydrogels capable of highly efficient and selective dye adsorption.

GSHMC: an efficient method for molecular simulation

The hybrid Monte Carlo (HMC) method is a popular and rigorous method for sampling from a canonical ensemble. The HMC method is based on classical molecular dynamics simulations combined with a Metropolis acceptance criterion and a momentum resampling step. While the HMC method completely resamples the momentum after each Monte Carlo step, the generalized hybrid Monte Carlo (GHMC) method can be implemented with a partial momentum refreshment step. This property seems desirable for keeping some of the dynamic information throughout the sampling process similar to stochastic Langevin and Brownian dynamics simulations. It is, however, ultimate to the success of the GHMC method that the rejection rate in the molecular dynamics part is kept at a minimum. Otherwise an undesirable Zitterbewegung in the Monte Carlo samples is observed. In this paper, we describe a method to achieve very low rejection rates by using a modified energy, which is preserved to high-order along molecular dynamics trajectories. The modified energy is based on backward error results for symplectic time-stepping methods. The proposed generalized shadow hybrid Monte Carlo (GSHMC) method is applicable to NVT as well as NPT ensemble simulations.

Linear viscoelasticity from molecular dynamics simulation of entangled polymers

The linear viscoelastic (LVE) spectrum is one of the primary fingerprints of polymer solutions and melts, carrying information about most relaxation processes in the system. Many single chain theories and models start with predicting the LVE spectrum to validate their assumptions. However, until now, no reliable linear stress relaxation data were available from simulations of multichain systems. In this work, we propose a new efficient way to calculate a wide variety of correlation functions and mean-square displacements during simulations without significant additional CPU cost. Using this method, we calculate stress−stress autocorrelation functions for a simple bead−spring model of polymer melt for a wide range of chain lengths, densities, temperatures, and chain stiffnesses. The obtained stress−stress autocorrelation functions were compared with the single chain slip−spring model in order to obtain entanglement related parameters, such as the plateau modulus or the molecular weight between entanglements. Then, the dependence of the plateau modulus on the packing length is discussed. We have also identified three different contributions to the stress relaxation:  bond length relaxation, colloidal and polymeric. Their dependence on the density and the temperature is demonstrated for short unentangled systems without inertia.

Purification and molecular cloning of antimicrobial peptides from Scots pine seedlings

A novel protocol for rapid and efficient purification of antimicrobial peptides from plant seedlings has been developed. Two peptides with antimicrobial activity, designated p1 and p2, were purified nearly to homogeneity from Scots pine seedlings by a combination of sulfuric acid extraction, ammonium sulfate precipitation, heat-inactivation and ion-exchange chromatography on phosphocellulose. Purified proteins had molecular masses of 11 kDa (p1) and 5.8 kDa (p2) and were identified by mass spectrometry as defensin and lipid-transfer protein, respectively. We demonstrated their growth inhibitory effects against a group of phytopathogenic fungi. Furthermore, we report for the first time molecular cloning and characterization of defensin I cDNA from Scots pine. A cDNA expression library from 7 days Scots pine seedlings was generated and used to isolate a cDNA clone corresponding to Scots pine defensin, termed PsDef1. The full-length coding sequence of PsDef1 is 252 bp in length and has an open reading frame capable to encode a protein of 83 amino residues. The deduced sequence has the typical features of plant defensins, including an endoplasmic reticulum signal sequence of 33 aa, followed by a characteristic defensin domain of 50 amino acids representing its active form. The calculated molecular weight of the mature form of PsDef1 is 5601.6 Da, which correlates well with the results of SDS-PAGE analysis. Finally, the antimicrobial properties of PsDef1 against a panel of fungi and bacteria define it as a member of the morphogenic group of plant defensins. (C) 2009 Elsevier Inc. All rights reserved.

Flavonoids and cognition: The molecular mechanisms underlying their behavioural effects

Evidence Suggests that a group of phytochemicals known as flavonoids are highly effective in reversing age-related declines in neuro-cognitive performance through their ability to interact with the cellular and molecular architecture of the brain responsible for memory and by reducing neuronal loss due to neurodegenerative Processes. In particular, they may increase the number of, and strength of, connections between neurons, via their specific interactions with the ERK and Akt signalling pathways, leading to an increase in neurotrophins Such as BDNF. Concurrently, their effects on the peripheral and Cerebral vascular system may also lead to enhancements in cognitive performance through increased brain blood flow and an ability to initiate neurogenesis in the hippocampus. Finally, they have also been shown to reduce neuronal damage and losses induced by various neurotoxic species and neuroinflammation. Together, these processes act to maintain the number and quality of synaptic connections in the brain. a factor known to be essential for efficient LTP, synaptic plasticity and ultimately the efficient working of memory. (C) 2009 Elsevier Inc. All rights reserved.

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.

Grid warehousing of molecular dynamics protein unfolding data

With the increasing awareness of protein folding disorders, the explosion of genomic information, and the need for efficient ways to predict protein structure, protein folding and unfolding has become a central issue in molecular sciences research. Molecular dynamics computer simulations are increasingly employed to understand the folding and unfolding of proteins. Running protein unfolding simulations is computationally expensive and finding ways to enhance performance is a grid issue on its own. However, more and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. This paper describes efforts to provide a grid-enabled data warehouse for protein unfolding data. We outline the challenge and present first results in the design and implementation of the data warehouse.

Syntheses, structures and efficient catalysis for C–C coupling of some benzaldehyde thiosemicarbazone complexes of palladium

Reaction of the 4-R-benzaldehyde thiosemicarbazones (denoted in general as L-R; R = OCH(3), CH(3), H, Cl and NO(2)) with trans-[Pd(PPh(3))(2)Cl(2)] afforded a group of mixed-ligand complexes (denoted in general as 1-R) incorporating a N,S-coordinated thiosemicarbazone. a triphenylphosphine and a chloride. Similar reaction with Na(2)[PdCl(4)] afforded a family of bis-thiosemicarbazone complexes (denoted in general as 2-R), where each ligand is N,S-coordinated. Crystal structures of 1-CH(3), 1-NO(2), 2-OCH(3), 2-NO(2) and L-NO(2) have been determined. In all the complexes the thiosemicarbazones are coordinated to the metal center, via dissociation of the acidic proton, as bidentate N,S-donors forming five-membered chelate rings. With reference to the structure of the uncoordinated thiosemicarbazone, this coordination mode is associated with a conformational change around the C=N bond. All the 1-R and 2-R complexes display intense absorptions in the visible region. Catalytic activity of the 1-R and 2-R complexes towards some C-C coupling reactions (e.g. Suzuki, Heck and Sonogashira) has been examined and while both are found to be efficient catalysts, 1-R is much better catalyst than 2-R.

Molecular barley breeding

Breeding progress in barley yield in the UK is being sustained at a rate in the order of 1% per annum against a background of declining seed sales. Commercial barley breeders are largely concentrating upon the elite local gene pool but with genotypic evidence suggesting that there is still considerable variation between current recommended cultivars, even those produced as half-sibs by the same breeder. Marker Assisted Selection (MAS) protocols could be substituted for conventional selection for a number of major-gene targets but, in the majority of cases, conventional selection is more resource efficient. Results from current QTL mapping studies have not yet identified sufficiently robust and validated targets for UK barley breeders to adopt MAS to assist in the selection of complex traits such as yield and malting quality. Results from multiple population mapping amongst the elite gene pool being utilised by breeders and from association studies of elite germplasm tested as part of the UK recommended list trial process do, however, show some promise.

Investigating flavonoids as molecular templates for the design of small-molecule inhibitors of cell signaling

Epidemiological and clinical trials reveal compelling evidence for the ability of dietary flavonoids to lower cardiovascular disease risk. The mechanisms of action of these polyphenolic compounds are diverse, and of particular interest is their ability to function as protein and lipid kinase inhibitors. We have previously described structure-activity studies that reinforce the possibility for using flavonoid structures as templates for drug design. In the present study, we aim to begin constructing rational screening strategies for exploiting these compounds as templates for the design of clinically relevant, antiplatelet agents. We used the platelet as a model system to dissect the structural influence of flavonoids, stilbenes, anthocyanidins, and phenolic acids on inhibition of cell signaling and function. Functional groups identified as relevant for potent inhibition of platelet function included at least 2 benzene rings, a hydroxylated B ring, a planar C ring, a C ring ketone group, and a C-2 positioned B ring. Hydroxylation of the B ring with either a catechol group or a single C-4' hydroxyl may be required for efficient inhibition of collagen-stimulated tyrosine phosphorylated proteins of 125 to 130 kDa, but may not be necessary for that of phosphotyrosine proteins at approximately 29 kDa. The removal of the C ring C-3 hydroxyl together with a hydroxylated B ring (apigenin) may confer selectivity for 37 to 38 kDa phosphotyrosine proteins. We conclude that this study may form the basis for construction of maps of flavonoid inhibitory activity on kinase targets that may allow a multitargeted therapeutic approach with analogue counterparts and parent compounds.

Mode-specific chemisorption of CH4 on Pt{110}-(1 x 2) explored by first-principles molecular dynamics

The chemisorption of CH4 on Pt{110}-(1 x 2) has been studied by vibrational analysis of the reaction pathway defined by the potential energy surface and, in time reversal, by first-principles molecular dynamics simulations of CH4 associative desorption, with the electronic structure treated explicitly using density functional theory. We find that the symmetric stretch vibration ν1 is strongly coupled to the reaction coordinate; our results therefore provide a firm theoretical basis for recently reported state-resolved reactivity measurements, which show that excitation of the ν1 normal mode is the most efficient way to enhance the reaction probability

Molecular design of a discrete chain-folding polyimide for controlled inkjet deposition of supramolecular polymers

A supramolecular polymer based upon two complementary polymer components is formed by sequential deposition from solution in THF, using a piezoelectric drop-on-demand inkjet printer. Highly efficient cycloaddition or ‘click’ chemistry afforded a well-defined poly(ethylene glycol) featuring chain-folding diimide end groups, which possesses greatly enhanced solubility in THF relative to earlier materials featuring random diimide sequences. Blending the new polyimide with a complementary poly(ethylene glycol) system bearing pyrene end groups (which bind to the chain-folding diimide units) overcomes the limited solubility encountered previously with chain-folding polyimides in inkjet printing applications. The solution state properties of the resulting polymer blend were assessed via viscometry to confirm the presence of a supramolecular polymer before depositing the two electronically complementary polymers by inkjet printing techniques. The novel materials so produced offer an insight into ways of controlling the properties of printed materials through tuning the structure of the polymer at the (supra)molecular level.