Today, emerging and increasing resistance to antibiotics has become a threat to public health worldwide. Antimicrobial peptides have unique action mechanisms making them an attractive therapeutic prospect to be applied against resistant bacteria. However, the major drawback is related with their high hemolytic activity which cancels out the safety requirements for a human antibiotic. Therefore, additional efforts are needed to develop new antimicrobial peptides that possess a greater potency for bacterial cells and less or no toxicity over erythrocytes. In this paper, we introduce a practical approach to simultaneously deal with these two conflicting properties. The convergence of machine learning techniques and desirability theory allowed us to derive a simple, predictive, and interpretable multicriteria classification rule for simultaneously handling the antibacterial and hemolytic properties of a set of cyclic beta-hairpin cationic peptidomimetics (C beta-HCPs). The multicriteria classification rule exhibited a prediction accuracy of about 80% on training and external validation sets. Results from an additional concordance test have shown an excellent agreement between the multicriteria classification rule predictions and the predictions from independent classifiers for complementary antibacterial and hemolytic activities, respectively, evidencing the reliability of the multicriteria classification rule. The rule was also consistent with the general mode of action of cationic peptides pointing out its biophysical relevance. We also propose a multicriteria virtual screening strategy based on the joint use of the multicriteria classification rule, desirability, similarity, and chemometrics concepts. The ability of such a virtual screening strategy to prioritize selective (nonhemolytic) antibacterial C beta-HCPs was assessed and challenged for their predictivity regarding the training, validation, and overall data. In doing so, we were able to rank a selective antibacterial C beta-HCP earlier than a biologically inactive or nonselective antibacterial C beta-HCP with a probability of ca. 0.9. Our results thus indicate that promising chemoinformatics tools were obtained by considering both the multicriteria classification rule and the virtual screening strategy, which could, for instance, be used to aid the discovery and development of potent and nontoxic antimicrobial peptides.

A series of molecular dynamics (MD) simulations of different pregelification mixtures representing intermediate stages of the sol gel process were set up to gain insight into the molecular imprinting process in xerogels, namely, to assess the template gel affinity and template self-aggregation. The physical plausibility of the parametrization was checked, confirming the reliability of the simulations. The simulated mixtures differed in the water/methanol ratio (1:3, 5:3, and 5:1) and in the absence/presence of an organic functional group (phenylaminopropyl-) in the silicate species. The simulation results, expressed mainly by the radial distribution functions and respective coordination numbers, showed that the affinity of the template molecule, damascenone (a hydrophobic species), for the gel backbone would not be attained without the tested functional group, phenylaminopropyl-. The affinity, related to the capability to trap the template within the gel network, was derived mostly from the hydrophobic interaction. It was also inferred from MD simulations that lower water contents (methanol-richer mixtures) would facilitate a better dispersion of both the functional group and the template within the final gel, therefore favoring the imprinting process. From the experimental counterparts of the simulated mixtures, a series of imprinted and nonimprinted xerogels were obtained. There was only one xerogel exhibiting the imprinting effect, namely, the one containing the organic group obtained at the lower water/methanol ratio (1:3), in agreement with predictions from the MD simulations. Such congruence demonstrates the ability of MD simulations to provide information regarding the fine aspects of molecular interactions in pregelification mixtures for imprinting.

In this work, hydrated poly(ethylene oxide) (PEO) chains composed of varying length N irreversibly grafted to an amorphous siloxane surface by one chain end at different coverage densities sigma were studied using atomistic molecular dynamics simulations. We have assessed beginning of the extended overlapping chains (brush regime) at sigma = 0.437 nm(-2) and identified the mushroom-like conformation of nonoverlapping chains. For the studied systems, the specific interactions lead to density distributions different from the functions analytically derived for model systems. The brush regime demonstrates itself in the density distribution functions and the reduced height h/N evolution with sigma. Since the latter dependence indicates h similar to N sigma(1/2) scaling, the brush regime corresponds to the situation of a concentrated aqueous PEO solution with a correlation length sigma(-1/2). The extrapolated thickness of PEO brushes reproduces experimental results fairly well. Water molecules prevent EO monomers from an adsorption to the siloxane surface.

In this work, static and dynamic properties of interfacial water molecules on the amorphous siloxane surface covered by poly(ethylene oxide) (PEO) chains grafted at different coverage densities sigma were studied using atomistic molecular dynamics simulations. It is shown that water molecules compete with the ethylene oxide (EO) monomers for interaction sites on the siloxane surface and for the space above it. Two types of orientations of the water molecules are identified as the most populated: one with the dipole moment vector pointing toward the siloxane surface and another with the dipole moment vector pointing about 5 degrees away from the surface. In both the hydrogen pair is amenable to rotate around the dipolar axis. The higher the coverage density the larger the disorder of water molecules, but the dipole moment-down orientation still dominates. The number of water-water hydrogen bonds monotonically decreases with sigma, whereas the number of water-PEO hydrogen bonds displays a maximum around the crossover to the brush regime (stretched chains). The interfacial water molecules seem to be anchored to the siloxane surface by the water oxygen atom rather than by hydrogen bonding. The confinement due to the solid substrate does not affect the first solvation layer of PEO chains. The mobility of water molecules is attenuated by the siloxane surface and also by the PEO chains more considerably in the direction perpendicular to the siloxane substrate.

Prostate cancer (PCa) is the second-leading cause of cancer deaths among men in the around the world. Understanding the biology of PCa is essential to the development of novel therapeutic strategies, in order to prevent this disease. However, after PCa make metastases, chemotherapy plays an extremely important role. With the pass of the time, PCa cell lines become resistant to the current anti-PCa drugs. For this reason, there is a necessity to develop new anti-PCa agents with the ability to be active against several PCa cell lines. The present work is an effort to overcome this problem. We introduce here the first multi-target approach for the design and prediction of anti-PCa agents against several cell lines. Here, a fragment-based QSAR model was developed. The model had a sensitivity of 88.36% and specificity 89.81% in training series. Also, the model showed 94.06% and 92.92% for sensitivity and specificity, respectively. Some fragments were extracted from the molecules and their contributions to anti-PCa activity were calculated. Several fragments were identified as potential substructural features responsible of anti-PCa activity and new molecular entities designed from fragments with positive contributions were suggested as possible anti-PCa agents.

The kinetics of an important rotamerization occurring in vinylpyranoanthocyanin-phenol pigment (Portisin) was analyzed according to the transition state (TS) formalism. The relevant stationary states, the TS and the equivalent minima, were fully characterized. This included the optimization of the respective geometries and the analytical calculation of all vibrational frequencies. The reaction coordinate was identified, as associated with a single imaginary frequency in TS, and an appropriate intrinsic coordinate analysis (IRC) ensured that this state was connected with the correspondent equivalent minima. For the minimum, the harmonic and one-dimensional hindered rotor models were used to describe the reaction coordinate. The activation thermodynamics properties were then evaluated. The results obtained were interpreted according to the theoretical models assumed. The results are important for a prompt result for this group of portisins. (C) 2010 Wiley Periodicals, Inc. Int J Quantum Chem 111: 1355-1360, 2011

Several pure and Ag-doped gold surfaces were used as models of nanoporous gold catalysts where O-2 was suggested to be activated. Density functional theory (DFT) calculations show that residual Ag on Au is able to promote adsorption and to dissociate thermodynamically favorable O-2 with high rate constants.

Ethylene glycol, the simplest of the diols, is a popular solvent, an antifreeze agent, a coolant, and a precursor in polymer production. In molecular modeling it is a model compound used to develop potentials for complex systems, like sugars. Despite the fact that many force fields for ethylene glycol exist in the literature, only few of them have been designed to reproduce the macroscopic properties of glycol and its mixtures, and rather more attention has been paid to the microscopic structure of the liquid. Those potentials that reproduce the properties accurately,apply also nonstandard fudge factors, therefore are not fully compatible with any popular force field. In this paper, we present a new potential for ethylene glycol, based on the OPLS all-atom force field and fully compatible with it, as well as with popular models for water. This potential is carefully validated against a broad range of physical properties measured experimentally and published in the literature. These properties include the density, expansion coefficient, compressibility, enthalpy of vaporization, surface tension, self-diffusion coefficient, and viscosity. Therefore, the potential presented here may be used in simulations of not only pure glycol but also mixtures with water, organic solvents, ionic liquids, phase interfaces, etc.