Publications

Abstract The formation mechanisms and properties of arc-induced gratings are intrinsically related to the temperature attained by the fiber during arc exposure. In this work, we present further results oil the estimation of the fiber temperature based oil the use of electrically insulated thermocouples. Computer simulations show that under typical arc discharge conditions, the fiber reaches steady-state thermal equilibrium in less than half a second, having a peak temperature of about 1350 degrees C (C) 2008 Wiley Periodicals, Inc.

Abstract The standard (p degrees = 0.1 MPa) molar enthalpies of formation in the crystalline state of phenylacetic acid and ortho-, meta- and para-chlorophenylacetic acids were derived from the standard molar energies of combustion in oxygen at T = 298.15 K, measured by combustion calorimetry. The Knudsen mass-loss effusion technique was used to measure the dependence of the vapour pressure of the solid isomers of chlorophenylacetic acid with the temperature from which the standard molar enthalpies of sublimation were derived using the Clausius-Clapeyron equation. [GRAPHICS] From these values the standard molar enthalpies in the gaseous phase, at T = 298.15 K, were derived, compared with the same parameters estimated from the Cox scheme and interpreted in terms of molecular structure. The standard (p degrees = 0.1 MPa) molar enthalpies, entropies, and Gibbs energies of sublimation, at T = 298.15 K, were derived for the three monochlorophenylacetic acids, using estimated values for the heat capacity differences between the gas and the crystal phases. Moreover, the enthalpies and the temperatures of fusion for the crystalline isomers of chlorophenylacetic acid were measured by differential scanning calorimetry.

Abstract The standard (p degrees = 0.1 MPa) molar enthalpies of formation, in the liquid phase, of 2-, 3- and 4-chloroanisoles, at T = 298.15 K, were derived from their standard massic energies of combustion, in oxygen, to yield CO2(g) and HC1 center dot 600H(2)O(l), measured by rotating bomb combustion calorimetry. The Calvet high-temperature microcalorimetry technique was used to measure the standard molar enthalpies of vaporization of these compounds. [GRAPHICS] From these two sets of experimental values, the standard molar enthalpies of formation in the gaseous phase, at T = 298.15 K, were derived, compared with the same parameters estimated by the Cox scheme and interpreted in terms of molecular structure.

Abstract The present work reports the values of the gaseous standard (p degrees = 0.1 MPa) molar enthalpies of formation of four isomers of dichloroanisole: 2,3-, 2,4-, 2,6-, and 3,5-dichloroanisole, at T=298.15 K. For all compounds, those values were derived from measurements of the standard molar energies of combustion in the condensed phase, using a rotating bomb combustion calorimeter, together with measurements of the standard molar enthalpies of sublimation or vaporization, measured by high temperature Calvet microcalorimetry. Moreover, the enthalpies and the temperatures of fusion for the crystalline isomers of dichloroanisoles were measured by differential scanning calorimetry. [GRAPHICS] The derived standard molar enthalpies of formation in the gaseous phase, at T=298.15 K, for the title compounds were compared with the same parameters estimated by the Cox scheme and interpreted in terms of molecular structure.

Abstract The complexes of ruthenium(II) with phenanthroline (Phen), diphenylphenanthroline (Ph(2)Phen) and with 4,4'-dicarboxy-2,2'-bipyridine acid (Dcbpy) ([Ru(Phen)(2)Dcbpy]Cl(2) and [Ru(Ph(2)Phen)(2)Dcbpy]Cl(2)) were synthesized and the variation of the correspondent fluorescence intensity and lifetime with the pH characterized, Luminescence Intensity, emission wavelength and excited state lifetime all show a typical sigmoid variation with pH in the range 3-9, demonstrating the suitability of this complex for luminescence sensing applications. In aqueous solutions (28% ethanol) the complexes [Ru(Phen)(2)Dcbpy]Cl(2) and [Ru(Ph2Phen)2Dcbpy]Cl2 show, respectively, the following properties: apparent pK(a) of 3.6 +/- 0.4 and 3.7 +/- 0.4; lifetimes of the protonated species 0.46 +/- 0.01 mu s and 0.38 +/- 0.02 mu s and ionised species 0.598 +/- 0.001 mu s and 0.61 +/- 0.08 mu s. The [Ru(Phen)(2)Dcbpy]Cl(2) complex was immobilised in the tip of optical fibers using a hybrid sol-gel procedure based on tetraethoxysilan and phenyltriethoxysilan enabling pH sensitive fiber probes. The immobilised complex shows the following lifetimes: protonated species 1.05 +/- 0.04 mu s and ionised species 1.16 +/- 0.04 mu s. These characteristics show that these ruthenium(II) complexes are good indicators for pH sensing, either in aqueous solution or immobilised in sol-gel, and are well suited for intensity and/or frequency domain interrogation.

Abstract Ionic liquids (ILs) have achieved special and dedicated attention from the scientific community in recent years and a large number of studies involving different features of properties and applications of ILs have been presented. The complete understanding of the phase behaviour of lLs with water is an important issue yet there are few experimental data on their phase equilibria. In this work the predictive capability of COSMO-RS, a predictive model based on unimolecular quantum chemistry calculations, was evaluated for the description of the liquid-liquid equilibria (LLE) and the vapour-liquid equilibria (VLE) of diverse binary mixtures of water and lLs. The effect of the ions conformers on the quality of the predictions was assessed and the quantum chemical COSMO calculation at the BP/TZVP level derived from the lowest energy conformations was adopted. While the LLE predictions degrade with increasing the hydrophilic IL anion character, in general a good qualitative agreement between the model predictions and experimental VLE and LLE data was obtained. COSMO-RS showed to be very helpful as an a prior! predictive method in order to find suitable candidates for a certain task or specific applications before extensive experimental measurements.

Abstract Low range mass spectra (MS) characterization of serum proteome offers the best chance of discovering proteome-(early drug-induced cardiac toxicity) relationships, called here Pro-EDICToRs. However, due to the thousands of proteins involved, finding the single disease-related protein could be a hard task. The search for a model based on general MS patterns becomes a more realistic choice. In our previous work (Gonzalez-Diaz, H., et al. Chem. Res. Toxicol. 2003, 16, 1318-1327), we introduced the molecular structure information indices called 3D-Markovian electronic delocalization entropies (3D-MEDNEs). In this previous work, quantitative structure-toxicity relationship (QSTR) techniques allowed us to link 3D-MEDNEs with blood toxicological properties of drugs. In this second part, we extend 3D-MEDNEs to numerically encode biologically relevant information present in MS of the serum proteome for the first time. Using the same idea behind QSTR techniques, we can seek now by analogy a quantitative proteome-toxicity relationship (QPTR). The new QPTR models link MS 3D-MEDNEs with drug-induced toxicological properties from blood proteome information. We first generalized Randic's spiral graph and lattice networks of protein sequences to represent the MS of 62 serum proteome samples with more than 370 100 intensity (I(i)) signals with m/z bandwidth above 700-12000 each. Next, we calculated the 3D-MEDNEs for each MS using the software MARCA-INSIDE. After that, we developed several QPTR models using different machine learning and MS representation algorithms to classify samples as control or positive Pro-EDICToRs samples. The best QPTR proposed showed accuracy values ranging from 83.8% to 87.1% and leave-one-out (LOO) predictive ability of 77.4-85.5%. This work demonstrated that the idea behind classic drug QSTR models may be extended to construct QPTRs with proteome MS data.

Abstract Up to now, very few applications of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies have been reported in the literature. However, none of them report the optimization of objectives related directly to the final pharmaceutical profile of a drug. In this paper, a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies, simultaneously considering the potency, bioavailability, and safety of a set of drug candidates, is introduced. The results of the desirability-based MOOP (the levels of the predictor variables concurrently producing the best possible compromise between the properties determining an optimal drug candidate) are used for the implementation of a ranking method that is also based on the application of desirability functions. This method allows ranking drug candidates with unknown pharmaceutical properties from combinatorial libraries according to the degree of similarity with the previously determined optimal candidate. Application of this method will make it possible to filter the most promising drug candidates of a library (the best-ranked candidates), which should have the best pharmaceutical profile (the best compromise between potency, safety and bioavailability). In addition, a validation method of the ranking process, as well as a quantitative measure of the quality of a ranking, the ranking quality index (W), is proposed. The usefulness of the desirability-based methods of MOOP and ranking is demonstrated by its application to a library of 95 fluoroquinolones, reporting their gram-negative antibacterial activity and mammalian cell cytotoxicity. Finally, the combined use of the desirability-based methods of MOOP and ranking proposed here seems to be a valuable tool for rational drug discovery and development.

Abstract The Quantitative Structure-Property Relationships (QSPRs) based on Graph OF Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798: and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the Study of complex mixtures of artificial polymers OF biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (pi(k)) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BR We used the MARCH-INSIDE approach to calculate the pi(k)(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on pi(k)(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach Captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.

Abstract Up to now, very few reports have been published concerning the application of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies. However, none reports the optimization of objectives related directly to the desired pharmaceutical profile of the drug. In this work, for the first time, it is proposed a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies considering simultaneously the pharmacological, pharmacokinetic and toxicological profile of a set of molecule candidates. The usefulness of the method is demonstrated by applying it to the simultaneous optimization of the analgesic, anti inflammatory, and ulcerogenic properties of a library of fifteen 3-(3-methylplienyl)-2-substituted amino-3H-quinazolin-4-one compounds. The levels of the predictor variables producing concurrently the best possible compromise between these properties is found and used to design a set of new optimized drug candidates. Our results also suggest the relevant role of the bulkiness of alkyl substituents on the C-2 position of the quinazoline ring over the Ulcerogenic properties for this family of compounds. Finally, and most importantly, the desirability-based MOOP method proposed is a valuable toot and shall aid in the future rational design of novel successful drugs. (C) 2008 Wiley Periodicals, Inc.