Three bis-amide bis-phenoxy N2O2 ligands were obtained from the 2:1 molar reaction of phenyl salicylate and the diamines (1,2-diaminoethane, 1,3-diaminopropane and 1,4-diaminobutane) to yield H4Ln (H4L1, H4L2, H4L3 respectively). The ligands have been characterised by elemental analysis, IR, and 1H 13C NMR spectroscopies, mass spectrometry (ES) and X-ray diffraction.

Examples of interesting ligands previously requiring lengthy synthetic procedures have been prepared by one step routes, opening the way to more extensive studies of their complexes and to possible applications. New amine bis-(phenolate) ligand with pendant arm on the amine nitrogen donor have been synthesized, via the Mannich condensation, between a disubstituted phenol, formaldehyde, and N(2-pyridylmethyl)amine

We report here new preparation with significant yield improvement of title compound. For this purpose the preparation of 4,4'-diethylaminoethoxyhexestrol dihydrochloride under different reported and analogue conditions have been tried. The optimized synthesis of Coralgil is reported. The synthesis was also scaled up to multi-grams for chemo-genomics study.

The separation of enantiomeric substrates using a parallel kinetic resolution strategy is becoming increasingly popular. 1 In recent years, attention has focussed on the use of traditional chiral auxilaries as complementary quasi-enantiomeric resolving agents. 2 In particular, Davies, 3 has elegantly shown the parallel kinetic resolution of the racemic enone (rac)-1 using a pair of quasi-enantiomeric lithium amides (S)-2 and (R)-3 to give the corresponding syn,syn,antiadducts 4 and 5 with near perfect levels of complementary stereocontrol (Scheme 1).

The separation of enantiomeric substrates using a parallel kinetic resolution is becoming increasingly popular.1 In recent years, attention has focussed on the use of traditional chiral auxiliaries as complementary quasi-enantiomeric resolving agents. 2 In particular, Davies, 3 has elegantly shown the parallel kinetic resolution of the racemic enone (rac)-1 using a pair of quasi-enantiomeric lithium amides (S)-2 and (R)-3 to give the corresponding syn,syn,anti-adducts 4 and 5 with near perfect levels of complementary stereocontrol (Scheme 1).

Trichomonas vaginalis (Tv) is the causative agent of the most common, nonviral, sexually transmitted disease in women and men world-wide. Since 1959 metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However resistance to MTZ in some patients and the great cost associated to the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, were able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in training (test) sets, respectively. These results validate the models for use in the ligand-based virtual screening. Also they showed large Matthews’ correlation coefficients (C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidenced the robustness of the obtained models. Later, both models were applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classified 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is a more important criterion for validating the models. In addition, these classification functions were applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds were synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Besides, out of the seven compounds that were screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) showed pronounced cytocidal activity at the concentration of 100µg/ml at 24h (48h) within the range of 98.66%-100% (99.40%-100%) while only two molecules (chemicals VA7-37 and VA7-38) showed high cytocidal activity at the concentration of 10µg/ml at 24h (48h): 98.38% (94.23%) and 97.59% (98.10%) correspondingly. The LDA-assisted QSAR models presented here could significantly reduce the number of synthesized and tested compounds and increase the chance of finding new chemical entities with trichomonacidal activity.

New antitrichomonal agents are needed to combat emerging metronidazoleresistant trichomoniasis and reduce the side-effects associated with currently available drugs. Toward this end, bond-based quadratic indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic total and bond-type quadratic indices for heteroatoms. The obtained LDA-based QSAR models, using non-stochastic and stochastic indices, were able to classify correctly 87.91% (87.50%) and 89.01% (84.38%) of the chemicals in training (test) sets, respectively. They showed large Matthews’ correlation coefficients (C) of 0.75 (0.71) and 0.78 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidenced the robustness of the obtained models. Later, both models were applied to the virtual screening of 12 compounds already proved against Trichomonas Vaginalis (Tv). As a result, they correctly classified 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is a more important criterion for validating the models. In addition, these classification functions were also applied to a library of twenty-one chemicals in order to find new lead antitrichomonal agents. These compounds were synthesized and tested for in vitro activity against Tv. As expected, theoretical results almost coincided with experimental ones since there was obtained a correct classification for both models of 95.24% (20 out of 21) of the chemicals. Out of the twenty-one compounds that were screened, and synthesized, two molecules (chemicals G-1, UC-245), showed high to moderate cytocidal activity at the concentration of 10µg/ml, other two compounds (G-0 and CRIS-148) showed high cytocidal activity only at the concentration of 100µg/ml, and the remaining chemicals (from CRIS-105 to CRIS-153 except CRIS-148) were inactive at these assayed concentrations. Finally, the best candidate, G-1 (cytocidal activity of 100% at 10µg/ml) was in vivo assayed in ovariectomized Wistar rats achieving promissory results as a trichomonacidal drug-like compound. The LDA-based QSAR models presented here can be considered as a computer-assisted system that could potentially significantly reduce the number of synthesized and tested compounds and increase the chance of finding new chemical entities with antitrichomonal activity.

There are many different kinds of pathogen bacteria species with very different susceptibility profile to different antibacterial drugs. One limitation of QSAR models are the biological activity of drugs against only one bacteria species. In previous paper we develop one unified Markov model to describe the biological activity of different drugs tested in the literature against some of the antimicrobial species. Consequently predicting the probability with which a drug is active against different bacteria species with a single unify model is a goal of the major importance. This work develops one unified Markov model to describe the biological activity of more than 70 drugs tested in the references against to 96 bacteria species. Linear Discriminant Analysis (LDA) classifying drugs as active or non-active against the different tested bacteria species processed the data. The model correctly classifies 199 out of 237 active compounds (83.9%) and 168 out of 200 non-active compounds (84%). Overall training predictability was 84% (367 out of 437 cases). Validation of the model was carring out by means of external predicting series, classifying the model 202 out 243, 83.13% of compounds. In order to show how the model function in practice a virtual screening was carring out recognizing the model as active 84.5%, 480 out of 568 antibacterial compounds not used in training or predicting series. The present is an attempt to calculate withing a unify framework probabilities of antibacterial action of drugs against many different species.

The series of nine amides of substituted 8-hydroxyquinolines were prepared. The synthetic procedures of compounds are presented. All the prepared quinoline derivatives were analyzed using RP-HPLC method for the lipophilicity measurement and their lipophilicity were determined. The prepared compounds were tested for the reduction of chlorophyll content in Chlorella vulgaris Beij. Several compounds showed biological activity comparable with or higher than the standard 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU). The relationships between the lipophilicity and the chemical structure of the studied compounds are discussed as well as structure-activity relationships (SAR) between the chemical structure and the biological activities of the evaluated compounds.

Based on the molecular modeling analysis against Y181C HIV-1 RT, dipyridodiazepinone derivatives containing unsubstituted lactam nitrogen and 2- chloro-8-arylthiomethyl were synthesized via efficient route. Some of them were evaluated for their antiviral activity against HIV-1 RT subtype E and were found to exhibit virustatic activity comparable to some clinically used therapeutic agents.