Escola Superior Agrária
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Browsing Escola Superior Agrária by advisor "Abreu, Rui M.V."
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- Estudo do potencial anti-inflamatório de uma biblioteca de compostos naturais de cogumelos por screening virtual contra as Enzimas COX (-1 E -2)Publication . Shiraishi, Carlos S.H.; Abreu, Rui M.V.; Gonçalves, Odinei HessO uso de Anti-Inflamatórios Não Esteroides (AINEs) no tratamento de doenças inflamatórias tem sido generalizado, principalmente no tratamento da artrite reumatóide. Os AINEs atuam principalmente promovendo a inibição das enzimas ciclooxigenases, especificamente as isoenzimas COX-1 e COX-2. As enzimas COX catalisam a conversação do ácido araquidônico em prostaglandinas. Os AINEs que atuam como inibidores das enzimas COX, induzem uma significativa atividade anti-inflamatória, analgésica e antipirética. No entanto, dados recentes mostram que o uso prolongado de AINEs pode originar efeitos colaterais cardiovasculares, incluindo insuficiência cardíaca isquêmica e infarte do miocárdio. O uso de compostos naturais como potenciais anti-inflamatórios, através da inibição das enzimas COX, têm sido assim proposto. Neste estudo, uma biblioteca de compostos de baixo peso molecular (LMW 3.0), presentes em cogumelos, foi preparada e aumentada para 190 compostos, a partir de bibliotecas preparadas anteriormente com 40 compostos (LMW 1.0) e 115 compostos (LMW 2.0), respetivamente. As famílias de compostos presentes na biblioteca incluem: quinonas, isoflavonas, flavonas, catecóis, aminas, ácidos gordos, alcaloides, terpenos, esteroides e derivados de aminoácidos. Foram também realizados estudos in silico de toxicidade (ADMET), tendo-se previsto que no geral estes compostos apresentam baixa toxicidade. De seguida realizou-se a seleção das estruturas 3D, de cada uma das enzimas COX, e procedeu-se à seleção do melhor software de docking por intermédio de estudo de Re-Docking e Cross-Docking. A biblioteca LMW 3.0 foi então testada in silico, contra as estruturas selecionadas das enzimas COX-1 e COX-2, utilizando o software de docking selecionado, o AutoDock Vina (VINA). Dos 190 compostos testados, os quatro que apresentaram o valor mais baixo de constante de inibição (Ki) previsto contra COX-1, foram: a Aurisina A (152,4 nM), a Naringina (496,8 nM), a 5,6-Epoxi-24(R)-metilcolesta-7,22-dien-3B-ol (588,1 nM) e a Aurisina K (696,2 nM). Para a COX-2, os compostos que apresentaram menor valor de Ki previsto foram: a Clavilactona C (55,4 nM); o Inonotusol C (77,6 nM), o Inonotusol A (91,9 nM) e a Putrescina-1,4-dicinamida (91,9 nM). Foram também realizados estudos in silico de toxicidade (ADMET), tendo-se previsto que, no geral, os compostos que apresentaram melhor potencial inibidor das enzimas COX-1 e COX-2 apresentaramtambém baixa toxicidade prevista. A modo de avaliar o melhor composto (clavilactona C), realizou-se a dinâmica molecular demonstrando a estabilidade com a proteína COX-2. Os compostos que apresentaram maior potencial previsto de inibição da COX-1 e COX-2 poderão assim ser considerados como candidatos a fármacos com potencial anti-inflamatório, sendo necessário no entanto que esta atividade seja verificada experimentalmente.
- Low molecular weight compounds from mushrooms as potential Bcl-2 inhibitors: docking and virtual screening studiesPublication . Khelifa, Sabrine; Abreu, Rui M.V.; Ferreira, Isabel C.F.R.; Khelil, Amel HajMushrooms have the ability to promote apoptosis in tumor cell lines, but the mechanism of action is not quite well understood. Inhibition of the interaction between Bcl-2 and pro-apoptotic proteins could be an important step that leads to apoptosis. Therefore, the discovery of compounds with the ability to inhibit Bcl-2 is an ongoing research topic in drug discovery. In this study, we started by analyzing Bcl-2 experimental structures that are currently available in Protein Data Bank database. After analysis of the more relevant Bcl-2 structures, 4 were finally selected. An analysis of the best docking methodology was then performed using a cross-docking and re-docking approach while testing 2 docking softwares: AutoDock 4 and AutoDock Vina. Autodock4 provided the best docking results and was selected to perform a virtual screening study applied to a dataset of 40 Low Molecular Weight (LMW) compounds present in mushrooms, using the selected Bcl-2 structures as target. Results suggest that steroid are the more promising family, among the analyzed compounds, and may have the ability to interact with Bcl-2 and this way promoting tumor apoptosis. The steroids that presented lowest estimated binding energy (ΔG) were: Ganodermanondiol, Cerevisterol, Ganoderic Acid X and Lucidenic Lactone; with estimated ΔG values between -8,45 and -8,23 Kcal/mol. A detailed analysis of the docked conformation of these 4 top ranked LMW compounds was also performed and illustrates a plausible interaction between the 4 top raked steroids and Bcl-2, thus substantiating the accuracy of the predicted docked poses. Therefore, tumoral apoptosis promoted by mushroom might be related to Bcl-2 inhibition mediated by steroid family of compounds.
- Preparação e screening virtual de uma biblioteca de compostos de baixo peso molecular oriundos de cogumelos contra proteínas da família BCL-2Publication . Borges, Bianca Ferreira; Abreu, Rui M.V.; Ineu, Rafael PortoOs cogumelos apresentam uma grande diversidade na sua composição química, quer de compostos de alto peso molecular, quer compostos de baixo peso molecular (LMW-“Low Molecular Weight”). Devido a sua composição química os cogumelos apresentam inúmeras bioactividades, incluindo: atividade antioxidante, antitumoral, antimicrobiana entre outras. A atividade antitumoral de cogumelos tem sido associada a presença de polissacarídeos nos cogumelos, no entanto ha uma crescente base de conhecimento que mostra que compostos LMW também tem um papel essencial na atividade antitumoral de diferentes espécies de cogumelos. Neste trabalho começou-se por realizar uma pesquisa bibliográfica, de forma a selecionar compostos LMW, presentes em diferentes espécies de cogumelos e associados de alguma forma a uma atividade antitumoral. No total selecionaram-se 115 compostos que formaram a nova biblioteca LMW 2.0, que foi cuidadosamente preparada para estudos in silico. Em uma segunda parte do trabalho foram realizados estudos de screening virtual da biblioteca LMW 2.0 utilizando o software de docking molecular AutoDock 4.0, de forma a tentar estimar quais os compostos da biblioteca que poderão ser os melhores inibidores de 3 proteínas da família Bcl-2: a Bcl-2 (linfoma de célula B 2), a Bcl-XL (linfoma de células B extra grandes) e a MCL-1 (leucemia mieloide-1). Estas proteínas foram escolhidas pois estão envolvidas nas vias de sinalização da apoptose promovendo a sua inibição, sendo atualmente conhecidos alvos terapêuticos em processo tumorais. Assim este trabalho teve como objetivo tentar identificar compostos LMW, presentes em cogumelos, que possam potenciar a apoptose tumoral, interagindo com a família Bcl-2 de proteínas anti-apoptóticas. No geral a proteína MCL-1 parece ser mais sensível aos compostos da biblioteca LMW 2.0, com valores de Ki (constante de inibição) estimados mais baixos, variando entre 17,1 nM e 64,7 nM para os dez melhores compostos. De seguida os melhores resultados foram obtidos para a Bcl-XL com valores entre os 51,5 e 185,6 nM e finalmente os resultados menos interessantes foram da Bcl-2 com valores de Ki entre 140,7 nM e 281 nM. Os compostos glicosilados apresentaram no geral uma melhor capacidade inibidora estimada. A visualização em detalhe das conformações de interação previstas mostra que a melhor capacidade inibidora dos compostos glicolisados fica provavelmente a dever-se à interação da glucose com alguns aminoácidos polares que formam a orla exterior do centro ativo das proteínas em estudo.
- QSAR modeling studies of a library of Human Tyrosinase inhibitorsPublication . Mateus, Cristiano; Abreu, Rui M.V.; Barros, LillianMelanogenesis is the chemical process responsible for synthesizing melanin, which occurs in melanocytes, in subcellular lysosome-like organelles called melanosomes. Melanin plays a vital role in protecting the skin from damage caused by ultraviolet rays. However, excess melanin production or abnormal distribution can cause various pigmentation disorders, such as over-tanning, age spots, and melasma. Skin disorders like these, have prompted the development of skin-whitening compounds to reduce melanin content. Furthermore, inhibition of melanin synthesis is considered a valid therapeutic strategy for treating advanced melanotic melanomas Human tyrosinase (hsTYR) is the most important enzyme involved in the melanogenesis process, as it catalyzes, at least, its first two steps. Tyrosinase from the white button mushroom Agaricus bisporus (abTYR) has been widely available at low cost from commercial sources for several decades, whereas hsTYR is still expensive and difficult to produce. The importance of discovering more and better hsTYR inhibitors has been widely discussed, as when tested against hsTYR, several abTYR inhibitors provide disappointing results, including some of the most extensively used depigmenting compounds now used in dermocosmetics. An in silico methodology that can be used to predict compound bioactivities is QSAR (quantitative structure-activity relationship) modelling. A QSAR model tries to find correlations between a biological activity of interest and molecular descriptors calculated from the compound structure. In this work, a QSAR model was developed to predict hsTYR inhibition activity using the PYTHON computer language and its PyQSAR package. To develop a QSAR model, a library of 196 known hsTYR inhibitors was gathered, and compounds were divided into 6 groups according to their scaffold structure. A total of 33 QSAR models were prepared using different combinations of the defined groups and different pools of molecular descriptors. QSAR model 32 was selected for further use as it presented good statistical robustness and had the highest number of compounds, 41 in total. Of the 28,933 molecular descriptors calculated by the OCHEM platform for the 41 compounds used, PyQSAR selected 4 to be used in the model: C-026; DISSM2C; MaxdssC; WHALES90_Rem. The statistical data obtained after the validation of the QSAR model by cross-validation was excellent, namely the determination coefficient (R2CV=0.9147), the value of the square root of the mean error (RMSE CV=0.1878) and the mean value of the score of the multiple linear regression method (Q2CV=0.8922). This QSAR model originates a mathematical equation that allows the prediction of hsTYR inhibition activity by new compounds with similar structures. A library of natural compounds, with a structure similar to those used to develop QSAR model 32, was created using the COCONUT database of natural compounds. A total of 1,628 natural compounds were gathered, their molecular descriptors were calculated, and the QSAR model 32 equation was applied. The results are displayed on a website and can be viewed by accessing the URL http://esa.ipb.pt/qsar/. The ZINC15 database was used to determine which of the compounds in the developed natural compound library would be available for purchase after predicting the hsTYR inhibitory activity of each compound in the library. A total of 18 different compounds were bought from different companies. To evaluate these compounds experimental ability to inhibit hsTYR and thus validate QSAR model 32, the compounds will be tested against this enzyme. If those compounds activity is confirmed, they may be used in cosmeceutical applications.
- Study of the anti-diabetic potential of a Fungi Marine Compounds library by virtual screening against 11β- HSD1Publication . Marques, Filipe Mendanha; Abreu, Rui M.V.; Shiraishi, CarlosType 2 diabetes mellitus (DM) is a chronic metabolic disease whose prevalence has been steadily increasing worldwide. Type 2 DM (formerly known as non-insulin-dependent DM) is the most common form of DM, characterized by hyperglycemia, insulin resistance, and relative insulin deficiency. This metabolic disease results from the interaction between genetic, environmental and behavioral risk factors. One of the proteins involved in this disease is 11β-hydroxysteroid dehydrogenase type 1 (11β- HSD1), an enzyme responsible for the reduction of cortisone to its active form, cortisol, which can lead to metabolic alterations such as insulin resistance and hyperglycemia. Thus, inhibition of 11β-HSD1 may offer a novel therapeutic approach for type 2 diabetes mellitus. Marine fungi (MF) compounds have been the subject of great attention in drug discovery because of their promise as therapeutic agents and because they possess a range of activities, including antibacterial, antiviral, and anticancer agents. This study prepared a virtual library of 157 compounds in marine fungi (MF). The potential of the compounds in the MF library as inhibitors of the 11β-HSD1 was then evaluated. Molecular docking of the MF library was performed against the 3D structure of 11β-HSD1 using VINA and YASARA software. Out of the 157 compounds, the 3 compounds that presented lower predicted binding energies (ΔG) values were Brevione A, Brevione I and Ilicicolin H with ΔG values of -11.6, -11.4 and -10.9 (kcal/mol), respectively. Brevione A and Brevione I are present in marine fungi Penicillium sp, while Ilicicolin H is present in Campylocarpon sp. HDN13-308. A detailed analysis of the predicted binding conformation of the 3 compounds was performed, and the main residues involved in the predicted binding conformation were analyzed in detail. Although experimental validation is needed, the 3 highlighted compounds, especially Brevione I, can be considered promising leads for developing potential anti-diabetic therapeutics. Also, the MF library prepared will be made available for researchers in general and will eventually be used to virtually screen other protein targets of interest.
- The broad spectrum of bioactive properties of phenolic extracts: a prospective study in three different plantsPublication . Jabeur, Inès; Ferreira, Isabel C.F.R.; Abreu, Rui M.V.; Achour, LotfiNatural resources like plants are currently used all over developed and under developed countries of the world as traditional home remedies and are promising agents for drug discovery as they play crucial role in traditional medicine. The use of plants for medicinal purpose usually varies from country to country and region to region because their use depends on the history, culture, philosophy and personal attitudes of the users (Ahmad et al., 2015). The use of plants and plant products as drugs predates the written human history (Hayta et al., 2014). Plants are a very important resource for traditional drugs and around 80% of the population of the planet use plants for the treatment of many diseases and traditional herbal medicine accounts for 30-50% of the total medicinal consumption in China. In North America, Europe and other well-developed regions over 50% of the population have used traditional preparations at least once (Dos Santos Reinaldo et al., 2015). Medicinal plants have been used over years for multiple purposes, and have increasingly attract the interest of researchers in order to evaluate their contribution to health maintenance and disease’s prevention (Murray, 2004). Recently between 50,000 and 70,000 species of plants are known and are being used in the development of modern drugs. Plants were the main therapeutic agents used by humans from the 19th century, and their role in medicine is always topical (Hayta et al., 2014). The studies of medicinal plants are rapidly increasing due to the search for new active molecules, and to improve the production of plants or bioactive molecules for the pharmaceutical industries (Rates, 2001). Several studies have been reported, but numerous active compounds directly responsible for the observed bioactive properties remain unknown, while in other cases the mechanism of action is not fully understood. According to the WHO 25% of all modern medicines including both western and traditional medicine have been extracted from plants, while 75% of new drugs against infective diseases that have arrived between 1981 and 2002 originated from natural sources, it was reported that the world market for herbal medicines stood at over US $60 billion per year and is growing steadily (Bedoya et al., 2009). Traditional medicine has an important economic impact in the 21st century as it is used worldwide, taking advantage on the low cost, accessibility, flexibility and diversity of medicinal plants (Balunas & Kinghorn, 2005).
- Valorisation of wild mushrooms as functional foods: chemoinformatic studiesPublication . Froufe, Hugo J.C.; Ferreira, Isabel C.F.R.; Abreu, Rui M.V.As interacções intermoleculares desempenham um papel essencial nos diversos processos biológicos, sendo fundamental a compreensão destas interacções nos Sectores das Indústrias Farmacêuticas e de Alimentos Funcionais. Os cogumelos representam uma fonte ilimitada de compostos com propriedades antitumorais e imunoestimulantes, e o seu consumo foi já relacionado com a redução do risco de cancro da mama. No presente trabalho, foram desenvolvidos dois estudos in silico com o intuito de melhor compreender quais os mecanismos moleculares responsáveis por diferentes propriedades bioactivas dos cogumelos. Primeiro utilizou-se uma metodologia de modelação QCAR (Relações Quantitativas Composição – Actividade) para estudar e prever a actividade antioxidante de cogumelos. Num segundo estudo utilizaram-se ferramentas de “docking” molecular e “virtual ligand screening” (VLS) para tentar elucidar possíveis mecanismos de actividade dos cogumelos contra o cancro da mama. No estudo QCAR inicial foi utilizada a técnica estatística dos Mínimos Quadrados Parciais (PLS) para avaliar a relação entre o potencial antioxidante (efeitos bloqueadores de radicais livres e poder redutor) e a composição química de vinte e três amostras de dezassete espécies de cogumelos silvestres Portugueses. Estudaram-se vários parâmetros analíticos tais como cinzas, hidratos de carbono, proteínas, gorduras, ácidos gordos monoinsaturados, ácidos gordos polinsaturados, ácidos gordos saturados, fenóis, flavonóides, ácido ascórbico e β-caroteno, e os seus resultados foram analisados por PLS de forma a estabelecer correlações entre todos os parâmetros. A actividade antioxidante mostrou estar correlacionada com o teor em fenóis e flavonóides. Foi construído um modelo QCAR, cuja robustez e capacidade de previsão foram verificadas por métodos de validação cruzada internos e externos. Finalmente, este modelo provou ser uma ferramenta útil na previsão do poder redutor de cogumelos. Nos estudos de VLS foi utilizado o software de “docking” molecular Autodock 4 com o objectivo de identificar compostos de baixo peso molecular (LMW), incluindo antioxidantes, presentes em cogumelos e potencialmente envolvidos na actividade contra o cancro da mama. Foi seleccionado um grupo representativo de 43 compostos de LMW (ácidos fenólicos, flavonóides, tocoferóis, carotenóides, açúcares e ácidos gordos) e efectuou-se “docking” molecular usando como alvo três proteínas envolvidas no cancro da mama (Aromatase, Esterona Sulfatase e 17-β-hidroxi-esteróide desidrogenase 1). Os compostos LMW foram classificados quanto à sua capacidade de inibição do cancro da mama. A informação obtida estabelece um bom ponto de partida para o desenvolvimento de inibidores das proteínas mencionadas. O ácido 4-o-cafeoilquínico, a naringina e o licopeno revelaram-se, respectivamente, os melhores inibidores para Aromatase, Esterona Sulfatase e 17β-HSD1. Os estudos de Química Computacional realizados permitiram a valorização dos cogumelos como alimentos funcionais, podendo ser muito úteis para Indústrias que visem o desenvolvimento de novos nutracêuticos ou alimentos funcionais.Intermolecular interactions play essential roles in several life processes and understanding these interactions is critical for pharmaceutical and functional foods industries. Mushrooms represent an unlimited source of compounds with antitumor and immunostimulating properties and mushroom intake has been shown to reduce the risk of breast cancer. In this work, two in silico studies were performed in an attempt to elucidate potential mechanisms of mushroom bioactivity. First, a QCAR (Quantitative Composition-Activity Relationships) modelling approach was used to study and predict mushroom antioxidant activity. Next, molecular docking and virtual ligand screening (VLS) studies were performed in an attempt to elucidate possible mechanisms of mushroom anti-breast cancer activity. For the initial QCAR study a PLS (Partial Least Square) statistical technique was applied to evaluate the relationship between antioxidant potential (scavenging effect on free radicals and reducing power) and chemical composition of twenty three samples from seventeen Portuguese wild mushroom species. A wide range of analytical parameters including ash, carbohydrates, proteins, fat, monounsaturated fatty acids, polyunsaturated fatty acids, saturated fatty acids, phenolics, flavonoids, ascorbic acid and β-carotene was studied and the data was analyzed by the PLS regression analysis to find correlations between all the parameters. Antioxidant activity correlated well with phenolic and flavonoid contents. A QCAR model was constructed, and its robustness and predictability was verified by internal and external cross-validation methods. This model proved to be a useful tool in the prediction of mushrooms reducing power. For the VLS study, molecular docking software AutoDock 4 was used in order to evaluate which wild mushroom low molecular weight (LMW) compounds, including antioxidants, could be involved in anti-breast cancer activity. A representative dataset of 43 LMW compounds (individual phenolic acids, flavonoids, tocopherols, carotenoids, sugars and fatty acids) was selected and molecular docking was carried out against three known protein targets involved in breast cancer (Aromatase, Estrone Sulfatase and 17-β-hydroxysteroid dehydrogenase 1). The top ranked LMW compounds with breast cancer inhibition activity was predicted and the information provided showed several interesting starting points for further development of inhibitors of the mentioned proteins. 4-O-caffeoylquinic acid, naringin and lycopene stand out as the top ranked potential inhibitors for Aromatase, Estrone Sulfatase and 17β-HSD-1, respectively. The performed chemoinformatic studies allowed valorisation of mushrooms as functional foods and could be used in Industries focused on developing new nutraceuticals or functional foods.