Inhibition of Caco-2 and MCF-7 cancer cells using chalcones: synthesis, biological evaluation and computational study.

Cancer is the second death cause worldwide, with breast and colon cancer among the most prevalent types. Traditional treatment strategies have several side effects that inspire the development of novel anticancer agents derived from natural sources, like chalcone derivatives. For this investigation, twenty-three chalcones (4a-w) were synthesized and evaluated as antiproliferative agents against MCF-7 and Caco-2 cells, finding three and two compounds with similar or higher antiproliferative activity than daunorubicin, while only two chalcones showed better selectivity indexes than daunorubicin on MCF-7. From these results, we developed good-performance QSAR models (r > 0.850, q2>0.650), finding several structural features that could modify chalcone activity and selectivity. According to these models, chalcones 4w and 4t have high potency and selectivity against Caco-2 and MCF-7, respectively, which make them attractive candidates for hit-to-lead development of ROS-independent pro apoptotic agents.

Nucleus-Independent Chemical Shift (NICS) as a Criterion for the Design of New Antifungal Benzofuranones.

The assertion made by Wu et al. that aromaticity may have considerable implications for molecular design motivated us to use nucleus-independent chemical shifts (NICS) as an aromaticity criterion to evaluate the antifungal activity of two series of indol-4-ones. A linear regression analysis of NICS and antifungal activity showed that both tested variables were significantly related (p < 0.05); when aromaticity increased, the antifungal activity decreased for series I and increased for series II. To verify the validity of the obtained equations, a new set of 44 benzofuran-4-ones was designed by replacing the nitrogen atom of the five-membered ring with oxygen in indol-4-ones. The NICS(0) and NICS(1) of benzofuran-4-ones were calculated and used to predict their biological activities using the previous equations. A set of 10 benzofuran-4-ones was synthesized and tested in eight human pathogenic fungi, showing the validity of the equations. The minimum inhibitory concentration (MIC) in yeasts was 31.25 µg·mL-1 for Candida glabrata, Candida krusei and Candida guilliermondii with compounds 15-32, 15-15 and 15-1. The MIC for filamentous fungi was 1.95 µg·mL-1 for Aspergillus niger for compounds 15-1, 15-33 and 15-34. The results obtained support the use of NICS in the molecular design of compounds with antifungal activity.

Quantitative structure-activity relationship to elucidate human CYP2A6 inhibition by organosulfur compounds.

CYP2A6 is a human enzyme responsible for the metabolic elimination of nicotine, and it is also involved in the activation of procarcinogenic nitrosamines, especially those present in tobacco smoke. Several investigations have reported that reducing this enzyme activity may contribute to anti-smoking therapy as well as reducing the risk of promutagens in the body. For these reasons, several authors investigate selective inhibitors molecules toward this enzyme. The aim of this study was to evaluate the interactions between a set of organosulfur compounds and the CYP2A6 enzyme by a quantitative structure-activity relationship (QSAR) analysis. The present work provides a better understanding of the mechanisms involved, with the final goal of providing information for the future design of CYP2A6 inhibitors based on dietary compounds. The reported activity data were modeled by means of multiple regression analysis (MLR) and partial least-squares (PLS) techniques. The results indicate that hydrophobic and steric factors govern the union, while electronic factors are strongly involved in the case of monosulfides.

Cinnamaldehyde and related phenylpropanoids, natural repellents, and insecticides against Sitophilus zeamais (Motsch.). A chemical structure-bioactivity relationship.

BACKGROUND: The insecticidal and repellent effects on adult Sitophilus zeamais of 12 cinnamaldehyde-related compounds was evaluated by contact toxicity bioassays and a two-choice olfactometer. To determine non-toxicity in mammals, body weight, serum biochemical profiles, liver weight, physiological parameters, sperm motility, and histopathological data were obtained as complementary information in C57BL/6 mice treated with the best natural compound. RESULTS: Based on 24 h LC95 and LC50 values, α-methyl-cinnamaldehyde and cinnamaldehyde exhibited better insecticidal action than the other compounds. The best repellent effect was observed with α-bromo-cinnamaldehyde, which even repelled at the lowest concentration studied (0.28 µmol L-1 ). The evaluation of a quantitative structure-activity relationship found a linear relationship between the LC50 values for adult weevil toxicity and dipolo with Q values (giving the difference between orbital electronegativity carbon 1 and orbital electronegativity carbon 3 of the molecule) in cinnamaldehyde-related compounds. The polar surface and Log P descriptors also revealed a linear relationship with the S. zeamais repellent effect for cinnamaldehyde analogues. Cinnamaldehyde did not show toxicity in the parameters evaluated in mice. CONCLUSION: From the phenylpropanoid components studied, the natural compound that had the best insecticidal and repellent action against S. zeamais was cinnamaldehyde. It presented no mammalian toxicity. © 2018 Society of Chemical Industry.

In silico study toward the identification of new and safe potential inhibitors of photosynthetic electron transport.

To address the rising global demand for food, it is necessary to search for new herbicides that can control resistant weeds. We performed a 2D-quantitative structure-activity relationship (QSAR) study to predict compounds with photosynthesis-inhibitory activity. A data set of 44 compounds (quinolines and naphthalenes), which are described as photosynthetic electron transport (PET) inhibitors, was used. The obtained model was approved in internal and external validation tests. 2D Similarity-based virtual screening was performed and 64 compounds were selected from the ZINC database. By using the VEGA QSAR software, 48 compounds were shown to have potential toxic effects (mutagenicity and carcinogenicity). Therefore, the model was also tested using a set of 16 molecules obtained by a similarity search of the ZINC database. Six compounds showed good predicted inhibition of PET. The obtained model shows potential utility in the design of new PET inhibitors, and the hit compounds found by virtual screening are novel bicyclic scaffolds of this class.

Quantitative structure-activity relationship (QSAR) analysis of plant-derived compounds with larvicidal activity against Zika Aedes aegypti (Diptera: Culicidae) vector using freely available descriptors.

BACKGROUND: We have developed a quantitative structure-activity relationship (QSAR) model for predicting the larvicidal activity of 60 plant-derived molecules against Aedes aegypti L. (Diptera: Culicidae), a vector of several diseases such as dengue, yellow fever, chikungunya and Zika. The balanced subsets method (BSM) based on k-means cluster analysis (k-MCA) was employed to split the data set. The replacement method (RM) variable subset selection technique coupled with multivariable linear regression (MLR) proved to be successful for exploring 18 326 molecular descriptors and fingerprints calculated with PaDEL, Mold2 and EPI Suite open-source softwares. RESULTS: A robust QSAR model (Rtrain2=0.84, Strain = 0.20 and Rtest2=0.92, Stest = 0.23) involving five non-conformational descriptors was established. The model was validated and tested through the use of an external test set of compounds, the leave-one-out (LOO) and leave-more-out (LMO) cross-validation methods, Y-randomization and applicability domain (AD) analysis. CONCLUSION: The QSAR model surpasses previously published models based on geometrical descriptors, thereby representing a suitable tool for predicting larvicidal activity against the vector A. aegypti using a conformation-independent approach. © 2018 Society of Chemical Industry.

On the relationship of anthranilic derivatives structure and the FXR (Farnesoid X receptor) agonist activity.

Farnesoid X receptor (FXR) is a nuclear receptor related to lipid and glucose homeostasis and is considered an important molecular target to treatment of metabolic diseases as diabetes, dyslipidemia, and liver cancer. Nowadays, there are several FXR agonists reported in the literature and some of it in clinical trials for liver disorders. Herein, a compound series was employed to generate QSAR models to better understand the structural basis for FXR activation by anthranilic acid derivatives (AADs). Furthermore, here we evaluate the inclusion of the standard deviation (SD) of EC50 values in QSAR models quality. Comparison between the use of experimental variance plus average values in model construction with the standard method of model generation that considers only the average values was performed. 2D and 3D QSAR models based on the AAD data set including SD values showed similar molecular interpretation maps and quality (Q2LOO, Q2(F2), and Q2(F3)), when compared to models based only on average values. SD-based models revealed more accurate predictions for the set of test compounds, with lower mean absolute error indices as well as more residuals near zero. Additionally, the visual interpretation of different QSAR approaches agrees with experimental data, highlighting key elements for understanding the biological activity of AADs. The approach using standard deviation values may offer new possibilities for generating more accurate QSAR models based on available experimental data.

Anti-Mycobacterial Evaluation of 7-Chloro-4-Aminoquinolines and Hologram Quantitative Structure-Activity Relationship (HQSAR) Modeling of Amino-Imino Tautomers.

In an ongoing research program for the development of new anti-tuberculosis drugs, we synthesized three series (A, B, and C) of 7-chloro-4-aminoquinolines, which were evaluated in vitro against Mycobacterium tuberculosis (MTB). Now, we report the anti-MTB and cytotoxicity evaluations of a new series, D (D01-D21). Considering the active compounds of series A (A01-A13), B (B01-B13), C (C01-C07), and D (D01-D09), we compose a data set of 42 compounds and carried out hologram quantitative structure-activity relationship (HQSAR) analysis. The amino-imino tautomerism of the 4-aminoquinoline moiety was considered using both amino (I) and imino (II) forms as independent datasets. The best HQSAR model from each dataset was internally validated and both models showed significant statistical indexes. Tautomer I model: leave-one-out (LOO) cross-validated correlation coefficient (q²) = 0.80, squared correlation coefficient (r²) = 0.97, standard error (SE) = 0.12, cross-validated standard error (SEcv) = 0.32. Tautomer II model: q² = 0.77, r² = 0.98, SE = 0.10, SEcv = 0.35. Both models were externally validated by predicting the activity values of the corresponding test set, and the tautomer II model, which showed the best external prediction performance, was used to predict the biological activity responses of the compounds that were not evaluated in the anti-MTB trials due to poor solubility, pointing out D21 for further solubility studies to attempt to determine its actual biological activity.

Synthesis, theoretical studies, and effect on the photosynthetic electron transport of trifluoromethyl arylamides.

BACKGROUND: The photosynthetic apparatus is targeted by various herbicides, including several amides such as diuron and linuron. Considering the need for the discovery of new active ingredients to cope with weed resistance, the synthesis of a series of trifluoromethyl aryl amides is herein described whose inhibitory properties were assessed in vitro on the photosynthetic electron transport chain, and in vivo on the growth of a model cyanobacterial strain. Theoretical studies were also carried out. RESULTS: Starting with 1-fluoro-2-nitro-4-(trifluoromethyl) benzene, the preparation of the amides was achieved via a three-step sequence, namely nucleophilic aromatic substitution, reduction with SnCl2 /HCl, and acylation reactions. The measurement of ferricyanide reduction by functionally intact spinach chloroplasts showed that several derivatives are capable of inhibiting the photosynthetic apparatus. The most active amides presented IC50 values close to 1 µmol L-1 , and showed the presence of a 4-bromophenyl group as a common structural feature. The addition of these brominated amides to the culture medium of a model cyanobacterial strain, Synechococcus elongatus PCC 6301, caused various degrees of growth inhibition. Theoretical studies (molecular modeling and quantitative structure-activity relationship) of all amides and their comparison with some known herbicides confirmed these experimental findings and provided more in-depth information about the possible molecular target of these compounds. CONCLUSION: Trifluoromethyl amides herein described, which were shown to act at the PSII level, may represent a novel scaffold to be exploited aiming at the development of new active ingredients for weed control. © 2017 Society of Chemical Industry.

Is molecular alignment an indispensable requirement in the MIA-QSAR method?

For a decade, the multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) approach has been successfully used in the modeling of several chemical and biological properties of chemical compounds. However, the key pitfall of this method has been its exclusive applicability to congeneric datasets due to the prerequisite of aligning the chemical images with respect to the basic molecular scaffold. The present report aims to explore the use of the 2D-discrete Fourier transform (2D-DFT) as a means of opening way to the modeling, for the first time, of structurally diverse noncongruent chemical images. The usability of the 2D-DFT in QSAR modeling of noncongruent chemical compounds is assessed using a structurally diverse dataset of 100 compounds, with reported inhibitory activity against MCF-7 human breast cancer cell line. An analysis of the statistical parameters of the built regression models validates their robustness and high predictive power. Additionally, a comparison of the results obtained with the 2D-DFT MIA-QSAR approach with those of the DRAGON molecular descriptors is performed, revealing superior performance for the former. This result represents a milestone in the MIA-QSAR context, as it opens way for the possibility of screening for new molecular entities with the desired chemical or therapeutic utility.

In vitro activity of natural phenolic compounds against fluconazole-resistant Candida species: a quantitative structure-activity relationship analysis.

AIMS: To evaluate the antifungal activity and to analyse the structure-activity relationship of eleven natural phenolic compounds against four Candida species which are resistant to fluconazole. METHODS AND RESULTS: Four different species of Candida isolates were used: Candida albicans, Candida krusei, Candida tropicalis and Candida dubliniensis. The phenolic compound carvacrol showed the highest anti-Candida bioactivity, followed by thymol and isoeugenol. The obtained minimum inhibitory concentration (MIC) values obtained were used in a quantitative structure-activity relationship (QSAR) analysis where the electronic, steric, thermodynamic and topological descriptors served as dependent variables. According to the descriptors obtained in this QSAR study, the antifungal activity of phenols has a first action specific character which is based on their interaction with plasma or mitochondrial membranes. The second action is based on a steric descriptor-the maximal and minimal projection of the area-which could explain the inability of some phenolic compounds to be biotransformed to quinones methylene by Candida species. CONCLUSIONS: According to the descriptors obtained in this QSAR study, the anti-Candida activity of ortho-substituted phenols is due to more than one action mechanism. The anti-Candida activity of phenolic compounds can be predicted by their molecular properties and structural characteristics. SIGNIFICANCE AND IMPACT OF THE STUDY: These results could be employed to predict the anti-Candida activity of new phenolic compounds in the search for new alternatives or complementary therapies to combat against candidiasis.