Showing papers by "Francisco Torrens published in 2010"

Bond-Based 2D Quadratic Fingerprints in QSAR Studies. Virtual and In Vitro Tyrosinase Inhibitory Activity Elucidation

Abstract: In this report, we show the results of quantitative structure–activity relationship (QSAR) studies of tyrosinase inhibitory activity, by using the bond-based quadratic indices as molecular descriptors (MDs) and linear discriminant analysis (LDA), to generate discriminant functions to predict the anti-tyrosinase activity. The best two models [Eqs (6) and (12)] out of the total 12 QSAR models developed here show accuracies of 93.51% and 91.21%, as well as high Matthews correlation coefficients (C) of 0.86 and 0.82, respectively, in the training set. The validation external series depicts values of 90.00% and 89.44% for these best two equations (6) and (12), respectively. Afterwards, a second external prediction data are used to perform a virtual screening of compounds reported in the literature as active (tyrosinase inhibitors). In a final step, a series of lignans is analysed using the in silico-developed models, and in vitro corroboration of the activity is carried out. An issue of great importance to remark here is that all compounds present greater inhibition values than Kojic Acid (standard tyrosinase inhibitor: IC50 = 16.67 μm). The current obtained results could be used as a framework to increase the speed, in the biosilico discovery of leads for the treatment of skin disorders.

Ligand-Based Computer-Aided Discovery of Tyrosinase Inhibitors. Applications of the TOMOCOMD-CARDD Method to the Elucidation of New Compounds

Abstract: In this review an overview of the application of computational approaches is given. Specifically, the uses of Quantitative Structure-Activity Relationship (QSAR) methods for in silico identification of new families of compounds as novel tyrosinase inhibitors are revised. Assembling, validation of models through prediction series, and virtual screening of external data sets are also shown, to prove the accuracy of the QSAR models obtained with the TOMOCOMD-CARDD (TOpological MOlecular COMputational Design-Computer-Aided Rational Drug Design) software and Linear Discriminant Analysis (LDA) as statistical technique. Together with this, a database is collected for these QSAR studies, and could be considered a useful tool in future QSAR modeling of tyrosinase activity and for scientists that work in the field of this enzyme and its inhibitors. Finally, a translation to real world applications is shown by the use of QSAR models in the identification and posterior in-vitro evaluation of different families of compounds. Several different classes of compounds from various sources (natural and synthetic) were identified. Between them, we can find tetraketones, cycloartanes, ethylsteroids, lignans, dicoumarins and vanilloid derivatives. Finally, some considerations are discussed in order to improve the identification of novel drug-like compounds based on the use of QSAR-Ligand-Based Virtual Screening (LBVS).

Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules

Abstract: Novel bond-level molecular descriptors are proposed, based on linear maps similar to the ones defined in algebra theory. The kth edge-adjacency matrix (E k ) denotes the matrix of bond linear indices (non-stochastic) with regard to canonical basis set. The kth stochastic edge-adjacency matrix, ES k , is here proposed as a new molecular representation easily calculated from E k . Then, the kth stochastic bond linear indices are calculated using ES k as operators of linear transformations. In both cases, the bond-type formalism is developed. The kth non-stochastic and stochastic total linear indices are calculated by adding the kth non-stochastic and stochastic bond linear indices, respectively, of all bonds in molecule. First, the new bond-based molecular descriptors (MDs) are tested for suitability, for the QSPRs, by analyzing regressions of novel indices for selected physicochemical properties of octane isomers (first round). General performance of the new descriptors in this QSPR studies is evaluated with regard to the well-known sets of 2D/3D MDs. From the analysis, we can conclude that the non-stochastic and stochastic bond-based linear indices have an overall good modeling capability proving their usefulness in QSPR studies. Later, the novel bond-level MDs are also used for the description and prediction of the boiling point of 28 alkyl-alcohols (second round), and to the modeling of the specific rate constant (log k), partition coefficient (log P), as well as the antibacterial activity of 34 derivatives of 2-furylethylenes (third round). The comparison with other approaches (edge- and vertices-based connectivity indices, total and local spectral moments, and quantum chemical descriptors as well as E-state/biomolecular encounter parameters) exposes a good behavior of our method in this QSPR studies. Finally, the approach described in this study appears to be a very promising structural invariant, useful not only for QSPR studies but also for similarity/diversity analysis and drug discovery protocols.

TOMOCOMD-CAMPS and protein bilinear indices--novel bio-macromolecular descriptors for protein research: I. Predicting protein stability effects of a complete set of alanine substitutions in the Arc repressor.

Abstract: Descriptors calculated from a specific representation scheme encode only one part of the chemical information. For this reason, there is a need to construct novel graphical representations of proteins and novel protein descriptors that can provide new information about the structure of proteins. Here, a new set of protein descriptors based on computation of bilinear maps is presented. This novel approach to biomacromolecular design is relevant for QSPR studies on proteins. Protein bilinear indices are calculated from the kth power of nonstochastic and stochastic graph–theoretic electronic-contact matrices, and , respectively. That is to say, the kth nonstochastic and stochastic protein bilinear indices are calculated using and as matrix operators of bilinear transformations. Moreover, biochemical information is codified by using different pair combinations of amino acid properties as weightings. Classification models based on a protein bilinear descriptor that discriminate between Arc mutants of stability similar or inferior to the wild-type form were developed. These equations permitted the correct classification of more than 90% of the mutants in training and test sets, respectively. To predict tm and values for Arc mutants, multiple linear regression and piecewise linear regression models were developed. The multiple linear regression models obtained accounted for 83% of the variance of the experimental tm. Statistics calculated from internal and external validation procedures demonstrated robustness, stability and suitable power ability for all models. The results achieved demonstrate the ability of protein bilinear indices to encode biochemical information related to those structural changes significantly influencing the Arc repressor stability when punctual mutations are induced.

Table of periodic properties of human immunodeficiency virus inhibitors

Abstract: Classification algorithms are proposed based on information entropy. The feasibility of mixing a given human immunodeficiency virus (HIV) inhibitor with dissimilar ones is studied. The 31 inhibitors are classified by their structural chemical properties. Many classification algorithms are based on information entropy. An excessive number of results appear compatible with the data and suffer combinatorial explosion. However, after the equipartition conjecture one has a selection criterion. According to this conjecture, the best configuration is that in which entropy production is most uniformly distributed. The structural elements of an inhibitor can be ranked according to their inhibitory activity. In didanosine (ddI) the base is a guanine derivative and the furan contains only one O heteroatom; ddI is selected as reference. In most inhibitors the furan contains one O heteroatom. The analysis is in agreement with principal component analysis and compares well with other classification taken as good based on docking, etc.

Experimental Studies for Modelling the Phase Behaviour of Monomer/Polymer/Disc Composites

Abstract: Nanoparticles do not stabilize the mixtures of epoxy monomer (prepolymer)/thermoplastic modifier (PS) and the ones of thermoplastic modifier dispersed within cured epoxy matrix. A small amount of thermoplastic co-polymer poly(styrene-b-methyl methacrylate) [P(S-b-MMA)] of MMA 4-22 wt.%, mixed with PS, makes compatible the mixtures with monomer epoxy precursor and cured epoxy matrix. The mixtures of cured epoxy matrix with thermoplastic consisting of PS and P(S-b-MMA), with nanofil 1%, are stable: the instability produced by the nanofil is overcome by the stability provided by the co-polymer. A model by Balazs' group to explain the phase behaviour of polymer/clay composites is extended.

Fullerite crystal thermodynamic characteristics and the law of corresponding states.

Abstract: The existence of single-wall carbon nanotubes in organic solvents in the form of clusters is discussed. A theory is developed based on a bundlet model, which enables describing the cluster-size distribution function. Comparison of calculated solubilities with experiments would permit obtaining energetic parameters, characterizing the interaction of a nanotube with its surrounding. Fullerenes and nanotubes are objects whose behaviour in many physical situations is characterized by peculiarities, which show up in that these systems represent the only soluble forms of carbon, what is related to their molecular structures. The fullerene molecule is a virtually uniform closed spherical-spheroidal surface and a nanotube is a smooth cylindrical unit. Both structures give rise to weak interactions between the neighbouring units in a crystal and promote their interaction with solvent molecules. The phenomena have a unified explanation in the bundlet model, in which the free energy of a nanotube in a cluster is combined from two components: a volume one proportional to the number of molecules n in a cluster and a surface one proportional to n1/2. Growth mechanisms of fractal clusters in fullerene solutions are analyzed along with similarity laws, determining the thermodynamic characteristics of fullerite crystals. In accordance with the similarity laws, the dimensionless Debye temperatures theta0 for all crystals belonging to the considered class should be close. Temperatures theta0 are determined by a similarity relation from experimental and estimated data. Fullerite theta0 is twice that for inert-gas crystals because, near the Debye point, the fullerite crystal is orientationally ordered so that its structure is dissimilar to face-centred cubic. A fullerene molecule whose thermal rotation is frozen cannot be considered as a spherically symmetric particle. The fulfilment of the similarity laws, which are valuable for particles with spherically symmetric interaction potential, would hardly be expected.

Protein negative/positively cooperative binding to zwitterionic/anionic vesicles

Abstract: The role of electrostatics is studied in the adsorption of cationic proteins to zwitterionic phosphatidylcholine (PC) and anionic mixed PC/phosphatidylglycerol (PG) small unilamellar vesicles (SUVs) [1]. For model proteins the interaction is monitored vs. PG content at low ionic strength [2]. The adsorption of lysozyme-myoglobin-bovine serum albumin (BSA) (isoelectric point, pI 5-11) is investigated in SUVs, along with changes of the fluorescence emission spectra of the proteins, via their adsorption on SUVs [3]. In the Gouy-Chapman formalism the activity coefficient goes with the square of charge number [4]. Deviations from the ideal model indicate asymmetric location of anionic phospholipid in the bilayer inner leaflet, in mixed zwitterionic/anionic SUVs for protein-PC/PG, in agreement with experiments-molecular dynamics simulations. Effective SUV charge stays constant. Myoglobin-, DNC-melittin- and melittin-zwitterionic associations are described by a partition model, modulated by electrostatic charging of membrane as protein accumulates at interface. Provisional conclusions follow. (1) In mixed zwitterionic/anionic vesicles the charge effect on the protein binding model was analyzed. For lysozyme-anionic enough vesicles and myoglobin the electrostatic repulsion between cationic ad proteins dominates over the electrostatic attraction between ad protein dipoles. (2) The salt effect on the protein binding model of mixed zwitterionic/anionic vesicles was analyzed. The cooperativity increases with ionic strength. The corresponding interpretation is that the electrostatic repulsion between cationic ad proteins decreases with increasing salt effect, and the electrostatic attraction between ad protein dipoles becomes dominant over the electrostatic repulsion between ad protein charges. (3) In anionic vesicles the effect of vesicle charge on protein binding shows that, with increasing anionic character of the vesicles, the protein-protein electrostatic repulsion is decreasingly important vs. the protein-vesicle attraction, and the electrostatic attraction between ad protein dipoles becomes dominant over the electrostatic repulsion between ad protein charges. (4) For lysozyme-mixed zwitterionic/anionic vesicles and myoglobin cooperativity increases with pH. With increasing pH and decreasing cationic character of the protein, the protein-protein electrostatic repulsion is decreasingly important against the protein-SUV attraction, and the electrostatic attraction between ad protein dipoles becomes dominant over the electrostatic repulsion between ad protein charges. Furthermore the opposed effect is observed for lysozyme-zwitterionic vesicles. (5) For protein-mixed zwitterionic/anionic vesicle binding there is more dispersion in the results, which could indicate asymmetric location of anionic phospholipid.