Eduardo Borges de Melo

Multivariate SAR/QSAR of 3-aryl-4-hydroxyquinolin-2(1H)-one derivatives as type I fatty acid synthase (FAS) inhibitors

Two multivariate studies, a PCA-SAR and a PLS-QSAR, of 3-aryl-4-hydroxyquinolin-2(1H)-one derivatives described as type I fatty acid synthase (FAS) inhibitors, are presented in this work. The variable selection was performed with the Fishers weight and Ordered Predictors Selection (OPS) algorithm, respectively. In the PCA, a separation between active and inactive compounds was obtained by six descriptors (topological and geometrical). The PLS model presented five descriptors and two Latent Variables. Leave-N-out cross validation and y-randomization test showed that the model presented robustness and no chance correlation, respectively, and the descriptors indicated that the FAS inhibition depends on electronic distribution of the investigated compounds. The model obtained in this study may provide a guidance for proposition of new FAS inhibitors.

Four-dimensional structure-activity relationship model to predict HIV-1 integrase strand transfer inhibition using LQTA-QSAR methodology.

Despite highly active antiretroviral therapy (HAART) implementation, there is a continuous need to search for new anti-HIV agents. HIV-1 integrase (HIV-1 IN) is a recently validated biological target for AIDS therapy. In this work, a four-dimensional quantitative structure-activity relationship (4D-QSAR) study using the new methodology named LQTA-QSAR approach with a training set of 85 HIV-1 IN strand transfer inhibitors (INSTI), containing the β-diketo acid (DKA) substructure, was carried out. The GROMACS molecular dynamic package was used to obtain a conformational ensemble profile (CEP) and LQTA-QSAR was employed to calculate Coulomb and Lennard-Jones potentials and to generate the field descriptors. The partial least-squares (PLS) regression model using 14 field descriptors and 8 latent variables (LV) yielded satisfactory statistics (R2= 0.897, SEC = 0.270, and F = 72.827), good performance in internal (QLOO2 = 0.842 and SEV = 0.314) and external prediction (Rpred2 = 0.839, SEP = 0.384, AREpred = 4.942%, k = 0.981, k′ = 1.016, and |R02 – R0′2 = 0.0257). The QSAR model was shown to be robust (leave-N-out cross validation; average QLNO2 = 0.834) and was not built by chance (y-randomization test; R2 intercept = 0.109; Q2 intercept = -0.398). Fair chemical interpretation of the model could be traced, including descriptors related to interaction with the metallic cofactors and the hydrophobic loop. The model obtained has a good potential for aid in the design of new INSTI, and it is a successful example of application of LQTA-QSAR as an useful tool to be used in computer-aided drug design (CADD).

1,2,3-Triazole-based analogue of benznidazole displays remarkable activity against Trypanosoma cruzi.

The current treatment of Chagas disease is based on the use of two drugs, nifurtimox and benznidazole, which present limited efficacy in the chronic stage of the disease and toxic side effects. Although some progress has been made in the development of new drugs to treat this disease, the discovery of novel compounds is urgently required. In this work we report the synthesis and biological evaluation of 1,2,3-triazole-based analogues of benznidazole. A small series of 27 compounds was successfully synthesized via microwave-assisted copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) and ruthenium-catalyzed azide-alkyne cycloaddition (RuAAC) from N-benzyl-2-azidoacetamide (1) and a set of commercial terminal alkynes. Analogues 24 (IC50 40 μM) and 28 (IC50 50 μM) showed comparable activities to benznidazole (IC50 34 μM) against trypomastigote form and analogue 15 (IC50 7 μM) was found to be the most active. Regarding the cytotoxicity assessment of the series, most compounds were not cytotoxic. This work shows that the designed strategy is efficiently capable of generating novel benzindazole analogues and reveals one analogue is more active than benznidazole.

An alternative approach for the use of water solubility of nonionic pesticides in the modeling of the soil sorption coefficients.

The collection of data to study the damage caused by pesticides to the environment and its ecosystems is slowly acquired and costly. Large incentives have been established to encourage research projects aimed at building mathematical models for predicting physical, chemical or biological properties of environmental interest. The organic carbon normalized soil sorption coefficient (K(oc)) is an important physicochemical property used in environmental risk assessments for compounds released into the environment. Many models for predicting logK(oc) that have used the parameters logP or logS as descriptors have been published in recent decades. The strong correlation between these properties (logP and logS) prevents them from being used together in multiple linear regressions. Because the sorption of a chemical compound in soil depends on both its water solubility and its water/organic matter partitioning, we assume that models capable of combining these two properties can generate more realistic results. Therefore, the objective of this study was to propose an alternative approach for modeling logK(oc), using a simple descriptor of solubility, here designated as the logarithm of solubility corrected by octanol/water partitioning (logS(P)). Thus, different models were built with this descriptor and with the conventional descriptors logP and logS, alone or associated with other explanatory variables representing easy-to-interpret physicochemical properties. The obtained models were validated according to current recommendations in the literature, and they were compared with other previously published models. The results showed that the use of logS(p) instead of conventional descriptors led to simple models with greater statistical quality and predictive power than other more complex models found in the literature. Therefore, logS(P) can be a good alternative to consider for the modeling of logK(oc) and other properties that relate to both solubility and water/organic matter partitioning.

Modeling structure–activity relationships of prodiginines with antimalarial activity using GA/MLR and OPS/PLS

In the present study, we performed a multivariate quantitative structure-activity relationship (QSAR) analysis of 52 prodiginines with antimalarial activity. Variable selection was based on the genetic algorithm (GA) and ordered predictor selection (OPS) approaches, and the models were built using the multiple linear regression (MLR) and partial least squares (PLS) regression methods. The leave-N-out crossvalidation and y-randomization tests showed that the models were robust and free from chance correlation. The mechanistic interpretation of the results was supported by earlier findings. In addition, the comparison of our models with those previously described indicated that the OPS/PLS-based model had a higher quality of external prediction. Thus, this study provides a comprehensive approach to the evaluation of the antimalarial activity of prodiginines, which may be used as a support tool in designing new therapeutic agents for malaria.

α e β-glucosidases como alvos moleculares para desenvolvimento de farmacos

Glucosidases are involved in key steps in the processing of oligosaccharides by cleaving O-glucose residues. Since they catalyze breaking and transfer reactions of glucosidic groups for the normal growth and development of all the cells, defects or genetic deficiencies in these enzymes are associated with serious disorders of the carbohydrate metabolism. Thus, glucosidases represent important targets to develop inhibitors, owing to their potential activities against viruses, tumoral growth and metastasis, diabetes, Gauchers disease and other syndromes associated with the lisosomal storage of glucoesphingolipids, and osteoarthritis. This paper presents a description of the biochemical pathways and mechanisms of a and b-glucosidases, and the currently available drugs capable to inhibit these enzymes.

The effect of different log P algorithms on the modeling of the soil sorption coefficient of nonionic pesticides

Collecting data on the effects of pesticides on the environment is a slow and costly process. Therefore, significant efforts have been focused on the development of models that predict physical, chemical or biological properties of environmental interest. The soil sorption coefficient normalized to the organic carbon content (Koc) is a key parameter that is used in environmental risk assessments. Thus, several log Koc prediction models that use the hydrophobic parameter log P as a descriptor have been reported in the literature. Often, algorithms are used to calculate the value of log P due to the lack of experimental values for this property. Despite the availability of various algorithms, previous studies fail to describe the procedure used to select the appropriate algorithm. In this study, models that correlate log Koc with log P were developed for a heterogeneous group of nonionic pesticides using different freeware algorithms. The statistical qualities and predictive power of all of the models were evaluated. Thus, this study was conducted to assess the effect of the log P algorithm choice on log Koc modeling. The results clearly demonstrate that the lack of a selection criterion may result in inappropriate prediction models. Seven algorithms were tested, of which only two (ALOGPS and KOWWIN) produced good results. A sensible choice may result in simple models with statistical qualities and predictive power values that are comparable to those of more complex models. Therefore, the selection of the appropriate log P algorithm for modeling log Koc cannot be arbitrary but must be based on the chemical structure of compounds and the characteristics of the available algorithms.

INIBIDORES DA HIV-INTEGRASE: POTENCIAL ABORDAGEM FARMACOLÓGICA PARA TRATAMENTO DA AIDS

AIDS has the HIV as its etiological agent. Researches has been done to find new pharmacological agents to be used in therapy, because of problems of resistance and side effects. The HIV-integrase inhibitors are some of those new agents that are being studied. This updating focusses on the fundamental information about HIV and HIV-integrase and the main methods being used to develop these new drugs, with examples for each case.

Qualidade de medicamentos isentos de prescrição: um estudo com marcas de dipirona comercializadas em uma drogaria de Cascavel (PR, Brasil)

Dipyrone is an antipyretic and analgesic medicine very used by the Brazilian population. The administration is considered safe even in pregnant women, nurseling and children, but is forbidden in some countries, as supposedly causes agranulocytosis and aplastic anemia. In 2001, National Health Surveillance Agency (Anvisa) approved the commercialization of this medicine in Brazil. However, it does not matter the safeness in the use of a medicine advances, if it does not have quality. Based on this quality, this work was elaborated, that analyzes seven samples of commercialized different marks of dipyrone oral solution in pharmaceutical establishment in the Cascavel city, Paraná, Brazil. The results demonstrate that the quality control of similar drugs must be improved as were the ones that presented quality deviations.

ESTUDO COMPUTACIONAL DE 1H-IMIDAZOL-2-IL-PIRIMIDINA-4,6-DIAMINAS PARA A IDENTIFICAÇÃO DE POTENCIAIS PRECURSORES DE NOVOS AGENTES ANTIMALÁRICOS

The aim of this study was develop in silico studies with a data set of 1 H -imidazol-2-yl-pyrimidine-4,6-diamines derivatives described as antimalarial agents with the intention of obtain data and tools useful in the development of new drugs of this class. A QSAR model was developed using topological, geometrical and electronic molecular descriptors with aid of the OPS/PLS approach. The data set was also used for pharmacophoric modeling, that was used in the ZINC database for found compounds that show good fit with the model. Due to the similarity between the four selected hits in the virtual screening with the data set, the obtained equation was used for predict the potential antimalarial activity. All hits were within the applicablity domain of the QSAR model, and showed adquates Monges leadlikeness score and predicted safety profiles.