Preliminary results of the recognition and release of molsidomine from molecularly imprinted polymers are reported. The molecularly imprinted polymers (MIPs) were prepared with molsidomine as a template molecule through radical polymerization. Eight different functional monomers were used with ethylene glycol dimethacrylate as crosslinker and dimethylsulphoxide as porogenic solvent. Non-covalent interactions between molsidomine and each functional monomer in DMSO prior to thermal bulk polymerization was utilized. Parallel stationary and dynamic binding experiments on both MIPs and NIPs (non-imprinted control polymers) were applied to verified imprinting process. Prepared polymers bound and remove molsidomine not selectively, but drug release properties were satisfactory.

Novel host-guest supramolecular copolymers have been prepared from a ß-cyclodextrin (binded to ethylenediamintetraacetic acid, EDTA) dimer and a ditopic guest with two adamantyl groups bound to pyromellitic acid. Molecular weight and molecular size were determined from static and dynamic light scattering measurements (SLS and DLS, respectively). The analysis of results suggests that the supramolecular polymer adopts a shruck structure with an average molecular weight value of Mn =(1.51±0.02)×104 g·mol-1 (degree of polymerization equal to 5).

A new gemini steroid surfactant derived from 3a,7a,12a-trihydroxy-5ß-cholan-24-amine (steroid residue) and ethylenediamintetraacetic acid (spacer) was synthesized and characterized in aqueous solution by surface tension measurements and fluorescence intensity of pyrene. These techniques evidence the existence of a threshold concentration, cac, below which a three layers film is formed at the air-water interface. At high concentrations, the intensity ratio of the vibronic peaks of pyrene, I1/I3, (= 0.81) is very close to published values for sodium cholate micelles, indicating that the probe is located in a region with a very low polarity and far from water.

The tautomerism between enol and inone forms of 1-phenylazo-2-naphthol is discussed in this work. The density functional theory (DFT) method is used at the level of B3LYP/6-31+G(d,p) for computations and it showed good agreement with the experimental data qualitatively. Generally quinone forms (of studied compounds) are more stable than naphthol forms. Electron attracting groups move the equilibrium also towards quinone form while releasing groups move the equilibrium to the naphthol form. The polarity of solvents does not have significant effect on the equilibrium.

A computational study of dimers formed by aniline and one CH3X molecule, X being CN, Cl or F, was carried out to elucidate the main characteristics of the interacting systems. Two different structures were found for each of the dimers, depending on the relative location of the CH3X molecule with respect to the amino hydrogen atoms. The most stable minimum for both acetonitrile and methyl chloride corresponds to structures where the CH3X molecule is located with its methyl group over the aromatic ring establishing a C-H···p contact and simultaneously interacting with the amino group with a N-H···X contact. In methyl fluoride complex, however, no significant interaction takes place with the aromatic ring in the most stable structure. In this case, the interaction takes places with the amino group forming a five member cycle with N-H···F and C-H···N contacts. As regards interaction energies, the stronger complex is formed with acetonitrile, with an interaction energy amounting to -6.4 kcal/mol. Methyl chloride and methyl fluoride form complexes with interaction energies amounting to -4.1 and -4.2 kcal/mol, respectively, though the structural arrangements are quite different for both structures. The results of the SAPT(DFT) analysis indicate that in most complexes the leading contribution to the stabilization of the complex is dispersion, though the electrostatic contribution is almost as important. However, in methyl fluoride most stable complex the larger attractive term is of electrostatic nature.

The novel TOMOCOMD–CARDD approach has been introduced here for the classification and design of antifungal agents using computer-aided molecular design. For this purpose, no stochastic and stochastic atom-based quadratic fingerprinting were used to codify the antifungal-related chemical structure information from a comprehensive data set of 2478 organic compounds having a great structural variability, 1087 of them being antifungal agents covering the broadest antifungal mechanisms of action known so far. The two ligand-based antifungal-activity classification models obtained by using Linear Discriminant Analysis, including no stochastic and stochastic indices, classified correctly 90.73% and 92.47%, respectively, of 1772 chemicals in the training set. These models showed moderate-to-high Matthews correlation coefficients (MCC of 0.81 and 0.85) as well as a very good accuracy, sensitivity, specificity and false alarm rate. These models were able of classifying correctly 92.16% and 87.56% of 706 compounds in an external test set. In general, the TOMOCOMD–CARDD models were best in predicting antifungal activity when compared with six of the most recent models reported so far; indicating that this approach could be very useful to identify (design and/or select) new antifungal agents against life-threatening fungal infections.

The recently introduced non-stochastic and stochastic bond-based linear indices are been generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. These improved modified descriptors are applied to several well-known data sets in order to validate each one of them. Particularly, Cramer’s steroid data set has become a benchmark for the assessment of novel QSAR methods. This data set has been used by several researchers using 3D-QSAR approaches such as CoMFA, MQSM, CoMMA, E-state, and so on. For that reason, it is selected by us for the shake of comparability. In addition, to evaluate the effectiveness of this novel approach in drug design we model the angiotensin-converting enzyme inhibitory activity of perindoprilate’s s-stereoisomers combinatorial library, as well as codify information related to a pharmacological property highly dependent on the molecular symmetry of a set of seven pairs of chiral N-alkylated 3-(3-hydroxyphenyl)-piperidines that bind s-receptors. The validation of this method is achieved by comparison with earlier publications applied to the same data sets. The non-stochastic and stochastic bond-based 3D-chiral linear indices appear to provide a very interesting alternative to other more common 3D-QSAR descriptors.

The absolute configuration (AC) of synthetic 4-Methyl-1,3,4,5-tetrahydro-2H-1,5-benzodiazepin-2-one was confirmed by comparison of the experimental circular dichroism with theoretical curves generated from the density functional theory (DFT) calculations. Initial analysis were carried out by Sybyl simulated annealing at force field MMFF94s.All the conformers were optimized by B3LYP/6-31G(d) level of theory. Electronic excitation energies (wavelength) and rotational strengths R (cgs) were calculated by time dependent density functional theory using density functional B3PW91 and bases set TZVP. Agreement between theoretical and experimental CD curves verified the R configuration of synthetic 4-methyl-1,3,4,5-tetrahydro-2H-1,5-benzodiazepin-2-one.

Cancer is among the top ten causes of death in the world but in spite of the efforts of the pharmaceutical companies and many governmental organizations, new and more effective drugs are urgently needed. Computer assisted studies have been widely used to predict anticancer activity taking into account different molecular descriptors, statistical techniques, cell lines and data sets of congeneric and non-congeneric compounds. This paper describes a QSAR study and the successful application of 3D-MoRSE descriptors for developing Linear Discriminant Analysis (LDA) to predict the anticancer potential of a diverse set of indolocarbazoles derivatives. Despite the structural complexity of this sort of compounds the used descriptors are able to identify the most remarkable features like the incidence of polarizability of the substituents and the interatomic distance in the 7-azaindole moiety in the antiproliferative activity. A comparison with other approaches such as the Getaway, Randic molecular profile, Geometrical, RDF descriptors, was carried out showing the model with 3D-MoRSE descriptors resulted in the best accuracy and predictive capability. An LDA based desirability analysis was conducted to select the levels of the predictor variables which should generate more desirable drugs, i.e. with higher posterior probability to be classified cytotoxic.

In this report, we show the results of QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitory activity, by using the bond-based quadratic indices as molecular descriptors (MDs) and linear discriminant analysis (LDA), togenerate discriminant functions to predict the anti-tyrosinase activity. The best two models (Eqs.8 and 14) 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 8 and 14, correspondingly. Afterwards, a second external prediction data was 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 analyzed by using the in silico developed models, and in vitro corroboration of the activity is carried out. An aspect of great importance to remark here, is that all compounds present greater inhibition values than Kojic Acid (standard tyrosinase inhibitor: IC50 =16.67µM). The current obtained results could be used as a method to increase the speed, in the biosilico discovery of leads for the treatment of skin disorders.