Chemical Composition and In Vitro and In Silico Antileishmanial Evaluation of the Essential Oil from Croton linearis Jacq. Stems.

Croton linearis Jacq. is an aromatic shrub that has been utilized in traditional medicine in the Bahamas, Jamaica, and Cuba. Recent studies have revealed the antiprotozoal potential of its leaves. The present work is aimed to identify the volatile constituents of essential oil from the stems of C. linearis (CLS-EO) and evaluate its in vitro antileishmanial activity. In addition, an in silico study of the molecular interactions was performed using molecular docking. A gas chromatographic-mass spectrometric analysis of CLS-EO identified 1,8-cineole (27.8%), α-pinene (11.1%), cis-sabinene (8.1%), p-cymene (5.7%), α-terpineol (4.4%), epi-γ-eudesmol (4.2%), linalool (3.9%), and terpinen-4-ol (2.6%) as major constituents. The evaluation of antileishmanial activity showed that CLS-EO has good activity on both parasite forms (IC50Promastigote = 21.4 ± 0.1 µg/mL; IC50Amastigote = 18.9 ± 0.3 µg/mL), with a CC50 of 49.0 ± 5.0 µg/mL on peritoneal macrophages from BALB/c mice (selectivity index = 2 and 3 using the promastigote and amastigote results). Molecular docking showed good binding of epi-γ-eudesmol with different target enzymes of Leishmania. This study is the first report of the chemical composition and anti-Leishmania evaluation of CLS-EO. These findings provide support for further studies of the antileishmanial effect of this product.

PTML modeling for peptide discovery: in silico design of non-hemolytic peptides with antihypertensive activity.

Hypertension is a medical condition that affects millions of people worldwide. Despite the high efficacy of the current antihypertensive drugs, they are associated with serious side effects. Peptides constitute attractive options for chemical therapy against hypertension, and computational models can accelerate the design of antihypertensive peptides. Yet, to the best of our knowledge, all the in silico models predict only the antihypertensive activity of peptides while neglecting their inherent toxic potential to red blood cells. In this work, we report the first sequence-based model that combines perturbation theory and machine learning through multilayer perceptron networks (SB-PTML-MLP) to enable the simultaneous screening of antihypertensive activity and hemotoxicity of peptides. We have interpreted the molecular descriptors present in the model from a physicochemical and structural point of view. By strictly following such interpretations as guidelines, we performed two tasks. First, we selected amino acids with favorable contributions to both the increase of the antihypertensive activity and the diminution of hemotoxicity. Then, we assembled those suitable amino acids, virtually designing peptides that were predicted by the SB-PTML-MLP model as antihypertensive agents exhibiting low hemotoxicity. The potentiality of the SB-PTML-MLP model as a tool for designing potent and safe antihypertensive peptides was confirmed by predictions performed by online computational tools reported in the scientific literature. The methodology presented here can be extended to other pharmacological applications of peptides.

Evaluación in silico del efecto de compuestos fenólicos de Pleurotus ostreatus sobre la enzima 5-lipoxigenasa (5- LOX) / In silico evaluation of the effect of Pleurotus ostreatus phenolic compounds on the enzyme 5-lipoxygenase (5-LOX)

Introducción: Los hongos comestibles, en particular Pleurotus ostreatus, representan una importante fuente de metabolitos bioactivos con propiedades inmunomoduladoras, antioxidantes y antiinflamatorias. Trabajos recientes han demostrado que extractos y compuestos purificados a partir de esta seta, entre ellos, la fracción rica en fenoles, inhiben el factor nuclear kappa B(NF-κB), la cicloxigenasa (COX) y modulan cascadas de señalización relacionadas con el balance redox. De acuerdo con estos antecedentes, dichos compuestos podrían actuar, además, como inhibidores de la enzima 5- lipoxigenasa (5-LOX). Objetivo: Evaluar el efecto in silico de trece compuestos fenólicos presentes en la especie Pleurotus ostreatus sobre la enzima 5-LOX, al utilizar como compuesto de referencia la mangiferina. Métodos: El acoplamiento se llevó a cabo a través del programa AutoDock 4.2 (http://autodock.scripps.edu) y la estructura de 5 LOX se obtuvo con la base de datos de proteínas, PDB (www.wwpdb.org). Se estimaron la energía libre (ΔG), la constante de disociación (Ki) y la eficiencia de ligando (LE). Se obtuvieron los parámetros de similitud a un fármaco y los relacionados con la absorción, distribución, metabolismo, excreción y toxicidad (ADME/T) de los mejores modelos de acoplamiento. Resultados: Los mejores indicadores de ΔG y Ki, correspondieron a los ácidos homogentísico, clorogénico y gentísico, con valores de ΔG (-11,81; -12,28 y -11,67 kcal/moL) y Ki (2,19 10-9; 9,99 10-10, 2,79 10-9 M), respectivamente. La eficiencia de ligando alcanzó valores adecuados para estos tres compuestos fenólicos. El modelo de acoplamiento del ácido homogentísico mostró los mejores resultados en cuanto a la similitud a un fármaco y pruebas ADME/T. Conclusiones: El estudio in silico reveló las potencialidades de la fracción rica en fenoles de P. ostreatus, y en particular, del ácido homogentísico como inhibidor de la enzima 5 -LOX, y justifica el desarrollo de ensayos confirmativos in vitro/ in vivo que corroboren sus efectos antioxidantes y antinflamatorios(AU)

Introduction: Edible mushrooms, Pleurotus ostreatus in particular, are an important source of bioactive metabolites with immunomodulatory, antioxidant and anti-inflammatory properties. Recent studies have shown that extracts and compounds purified from this mushroom, among them the phenol-rich fraction, inhibit nuclear factor kappa B (NF-κB), cyclooxygenase (COX), and modulate signaling cascades related to redox balance. According to these antecedents, such compounds could also act as inhibitors of the enzyme 5-lipoxygenase (5-LOX). Objective: Evaluate the in silico effect of 13 phenolic compounds present in the species Pleurotus ostreatus on the enzyme 5-LOX using mangiferin as reference compound. Methods: Docking was carried out with the software AutoDock 4.2 (http://autodock.scripps.edu) and the 5-LOX structure was obtained with the protein database PDB (www.wwpdb.org). Estimation was performed of free energy (ΔG), dissociation constant (Kd) and ligand efficiency (LE). Drug-likeness parameters were obtained, as well as those related to absorption, distribution, metabolism, excretion and toxicity (ADMET) of the best docking models. Results: The best ΔG and Kd indicators were homogentisic, chlorogenic and gentisic acids, with ΔG and Kd values of -11.81, -12.28, -11.67 kcal/mol, and 2.19 10-9, 9.99 10-10, 2.79 10-9 M, respectively. Ligand efficiency achieved adequate values for these three phenolic compounds. The docking model for homogentisic acid showed the best results in terms of drug likeness and ADMET tests. Conclusions: The in silico study revealed the potential of the phenol-rich fraction of P. ostreatus, homogentisic acid in particular, as an enzyme 5-LOX inhibitor, and justifies the development of confirmatory in vitro / in vivo assays to corroborate its antioxidant and anti-inflammatory effects(AU)

In vitro evaluation of arylsubstituted imidazoles derivatives as antiprotozoal agents and docking studies on sterol 14α-demethylase (CYP51) from Trypanosoma cruzi, Leishmania infantum, and Trypanosoma brucei.

There is an urgent need to discover and develop new drugs to combat parasitic diseases as Chagas disease (Trypanosoma cruzi), sleeping sickness (Trypanosoma brucei), and leishmaniasis (Leishmania ssp.). These diseases are considered among the 13 most unattended diseases worldwide according to the WHO. In the present work, the synthesis of 14 arylsubstituted imidazoles and its molecular docking onto sterol 14α-demethylase (CYP51) was executed. In addition, the compounds, antiprotozoal activity against T. brucei, T. cruzi, Trypanosoma brucei rhodesiense, and Leishmania infantum was evaluated. In vitro antiparasitic results of the arylsubstituted imidazoles against T. brucei, T. cruzi, T.b. rhodesiense, and L. infantum indicated that all samples from arylsubstituted imidazole compounds presented interesting antiparasitic activity to various extent. The ligands 5a, 5c, 5e, 5f, 5g, 5i, and 5j exhibited strong activity against T. brucei, T. cruzi, T.b. rhodesiense, and L. infantum with IC50 values ranging from 0.86 to 10.23 µM. Most samples were cytotoxic against MRC-5 cell lines (1.12 < CC50 < 51.09 µM) and only ligand 5c showed a good selectivity against all tested parasites. According to the results of the molecular docking, the aromatic substituents in positions 1, 4, and 5 have mainly stabilizing hydrophobic interactions with the enzyme matrix, while the oxygen from NO2, SO3H, and OH groups interacts with the Fe2+ ion of the Heme group.

QSAR model toward the rational design of new agrochemical fungicides with a defined resistance risk using substructural descriptors.

The increasing resistance of several phytopathogenic fungal species to the existing agrochemical fungicides has alarmed to the worldwide scientific community. There is no available methodology to predict in an efficient way if a new fungicide will have resistance risk due to fungal species which cause considerable crop losses. In an attempt to overcome this problem, a multi-resistance risk QSAR model, based on substructural descriptors was developed from a heterogeneous database of compounds. The purpose of this model is the classification, design, and prediction of agrochemical fungicides according to resistance risk categories. The QSAR model classified correctly 85.11% of the fungicides and the 85.07% of the inactive compounds in the training series, for an accuracy of 85.08%. In the prediction series, the percentages of correct classification were 85.71 and 86.55% for fungicides and inactive compounds, respectively, with an accuracy of 86.39%. Some fragments were extracted and their quantitative contributions to the fungicidal activity were calculated taking into consideration the different resistance risk categories for agrochemical fungicides. In the same way, some fragments present in molecules with fungicidal activity and with negative contributions were analyzed like structural alerts responsible of resistance risk.

Rational design of new agrochemical fungicides using substructural descriptors.

BACKGROUND: The increasing resistance of several phytopathogenic fungal species to existing agrochemical fungicides has alarmed the worldwide scientific community. In an attempt to overcome this problem, a discriminant model based on substructural descriptors was developed from a heterogeneous database of compounds for the design of, search for and prediction of agrochemical fungicides. RESULTS: The discriminant model classifies correctly 81.95% of the fungicides and 81.54% of the inactive compounds in the training series, with an accuracy of 81.72%. In the prediction series, the percentage of correct classification was 80.59 and 85.56% for fungicides and inactive compounds respectively, with an accuracy of 83.44%. Some fragments were extracted and their contributions were calculated. From the fragments that were determined to make positive contributions to the fungicidal activity, new molecules such as pyrrole derivatives were designed and the probabilities of their being fungicides were calculated. These molecules were correctly classified as potential fungicides. CONCLUSION: The discriminant model based on substructural descriptors provides a promising methodology for the development of molecular patterns to be used in the design of, search for and prediction of agrochemical fungicides of wide spectrum. This constitutes an alternative for the discovery of compounds that are able to decrease crop losses caused by phytopathogenic fungal species.