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In a multi-target complex network, the links (L-ij) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K-i, K-m, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

In a multi-target complex network, the links (Lij) represent the interactions between the drug (di) and the target (tj), characterized by different experimental measures (Ki, Km, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (cj). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%–90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular OPEN ACCESS Int. J. Mol. Sci. 2014, 15 17036 targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally

There are many of pathogen parasite species with different susceptibility profile to antiparasitic drugs. Unfortunately, almost QSAR models predict the biological activity of drugs against only one parasite species. Consequently, predicting the probability with which a drug is active against different species with a single unify model is a goal of the major importance. In so doing, we use Markov Chains theory to calculate new multi-target spectral moments to fit a QSAR model that predict by the first time a mt-QSAR model for 500 drugs tested in the literature against 16 parasite species and other 207 drugs no tested in the literature using spectral moments. The data was processed by Linear Discriminant Analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 311 out of 358 active compounds (86.9%) and 2328 out of 2577 non-active compounds (90.3%) in training series. Overall training performance was 89.9%. Validation of the model was carried out by means of external predicting series. In these series the model classified correctly 157 out 190, 82.6% of antiparasitic compounds and 1151 out of 1277 non-active compounds (90.1%). Overall predictability performance was 89.2%. In addition we developed four types of non Linear Artificial Neural Networks (ANN) and we compared with the mt-QSAR model. The improved ANN model had an overall training performance was 87%. The present work report the first attempts to calculate within a unify framework probabilities of antiparasitic action of drugs against different parasite species based on spectral moment analysis

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

The acid-catalyzed [3+2] and [4+2] cycloadditions between methyl glyoxylate oxime (1) and cyclopentadiene were investigated using various Lewis and/or Bronsted acids at different temperatures in dichloromethane as solvent. Besides the expected new adducts, (±)-methyl [(3-exo)-2-hydroxy-2-azabicyclo[2.2.1]hept-5-ene]-3-carboxylate (2) and (±)-methyl [(3-endo)-2-hydroxy-2-azabicyclo[2.2.1]hept-5-ene]-3-carboxylate (3) a third addict, (±) methyl (1R,4R,5R)-(2-ox-3-azabicyclo[3.3.0]oct-7-ene)-4-carboxylate (4), whose formation can be explained by a concerted 1,3-dipolar cycloaddition, was obtained. Yields and product ratios were found to be more dependent on the catalyst than on the temperature; these results and the stereochemistry of the adducts, confirmed by spectroscopic data (1H and 13C NMR) and by X-ray cycloadditions

The first members of a new family of heterocarbobicyclic nucleoside analogues have been synthesized from the cis/trans mixture of (4-amino-5,6-dihydro-4H-cyclopenta[b]thiophen-6-yl)methanols cis/trans-7. The separation of cis and trans intermediates during preparation of the 6-chloropurine derivatives allowed separate preparation of the purine heterocarbanucleosides cis-10 and trans-11, from which cis-(12-14) and trans-(16-18) were obtained by replacement of the 6-chloro substituent with amino, hydroxy and cyclopropylamino groups. Additionally, the 6-phenyl-purinyl analogues cis-15 and trans-19 were prepared from cis-10 and trans-11 using Suzuki-Miyaura methodology

Starting from (±)-trans- and (±)-cis-3-hydroxymethyl-1-indanol, novel 6-substituted purinylcarbanucleoside derivatives of indan (5, 6, 9, 10, 15 and 17) were synthesized through a key coupling reaction with 6-chloropurine under Mitsunobu conditions. Suzuki–Miyaura reactions of the protected 6-chloropurine derivative with different arylboronic acids afforded the corresponding 6-arylpurinylcarbanucleoside derivatives. Finally, three new 5-halouracilcarbanucleosides (19, 20 and 21) were prepared by reaction of uracilcarbanucleoside 18 with different N-halosuccinimides. All of the new analogues were evaluated for antiviral activity against a wide variety of viruses

Ethyl 2-(diisopropoxyphosphoryl)-2H-azirine-3-carboxylate was generated “in situ” and reacted with a number of 1,3-butadienes. Cycloadducts, or in one case an ensuing rearranged product, were isolated with moderate to good yields