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Integrative multi-kinase approach for the identification of potent antiplasmodial hits
(2019) Lima, Marilia Nunes do Nascimento; Cassiano, Gustavo Capatti; Tomaz, Kaira Cristina Peralis; Silva, Arthur de Carvalho e; Sousa, Bruna Katiele de Paula; Ferreira, Letícia Tiburcio; Tavella, Tatyana Almeida; Paim, Juliana Calit; Bargieri, Daniel Youssef; Neves, Bruno Junior; Costa, Fabio Trindade Maranhão; Andrade, Carolina Horta
Malaria is a tropical infectious disease that affects over 219 million people worldwide. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new antimalarial drugs is a global health priority. Multi-target drug discovery is a promising and innovative strategy for drug discovery and it is currently regarded as one of the best strategies to face drug resistance. Aiming to identify new multi-target antimalarial drug candidates, we developed an integrative computational approach to select multi-kinase inhibitors for Plasmodium falciparum calcium-dependent protein kinases 1 and 4 (CDPK1 and CDPK4) and protein kinase 6 (PK6). For this purpose, we developed and validated shape-based and machine learning models to prioritize compounds for experimental evaluation. Then, we applied the best models for virtual screening of a large commercial database of drug-like molecules. Ten computational hits were experimentally evaluated against asexual blood stages of both sensitive and multi-drug resistant P. falciparum strains. Among them, LabMol-171, LabMol-172, and LabMol-181 showed potent antiplasmodial activity at nanomolar concentrations (EC50 ≤ 700 nM) and selectivity indices >15 folds. In addition, LabMol-171 and LabMol-181 showed good in vitro inhibition of P. berghei ookinete formation and therefore represent promising transmission-blocking scaffolds. Finally, docking studies with protein kinases CDPK1, CDPK4, and PK6 showed structural insights for further hit-to-lead optimization studies.
Deep learning-driven research for drug discovery: tackling malaria
(2020) Neves, Bruno Junior; Braga, Rodolpho de Campos; Alves, Vinícius de Medeiros; Lima, Marília Nunes do Nascimento; Cassiano, Gustavo Capatti; Muratov, Eugene; Costa, Fabio Trindade Maranhão; Andrade, Carolina Horta
Malaria is an infectious disease that affects over 216 million people worldwide, killing over 445,000 patients annually. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new drug candidates is a major global health priority. Aiming to make the drug discovery processes faster and less expensive, we developed binary and continuous Quantitative Structure-Activity Relationships (QSAR) models implementing deep learning for predicting antiplasmodial activity and cytotoxicity of untested compounds. Then, we applied the best models for a virtual screening of a large database of chemical compounds. The top computational predictions were evaluated experimentally against asexual blood stages of both sensitive and multi-drug-resistant Plasmodium falciparum strains. Among them, two compounds, LabMol-149 and LabMol-152, showed potent antiplasmodial activity at low nanomolar concentrations (EC50 <500 nM) and low cytotoxicity in mammalian cells. Therefore, the computational approach employing deep learning developed here allowed us to discover two new families of potential next generation antimalarial agents, which are in compliance with the guidelines and criteria for antimalarial target candidates.
Flavonoids from Brazilian Cerrado: biosynthesis, chemical and biological profile
(2019) Peixoto, Josana de Castro; Neves, Bruno Junior; Vasconcelos, Flávia Gonçalves; Napolitano, Hamilton Barbosa; Barbalho, Maria Gonçalves da Silva; Silva, Sandro Dutra e; Rosseto, Lucimar Pinheiro
Flavonoids are highly bioactive compounds with very low toxicity, which makes them attractive starting points in drug discovery. This study aims to provide information on plant species containing flavonoids, which are found in the Brazilian Cerrado. First, we present the characterization and plant diversity with emphasis on the families of flavonoid-producing plants, and then we describe the phenylpropanoid pathway which represents the flavonoids’ main route biosynthesis—generally conserved in all species. Chemical structures and biological activities of flavonoids isolated from the Cerrado’s plant species are also described based on examples from the relevant literature studies. Finally, research on the biodiversity of the Cerrado biome should be encouraged, due to the discovery of new sources of flavonoids which can provide several benefits to human health and the possibility of developing new drugs by the pharmaceutical industry.
In silico strategies to support fragment-to-lead optimization in drug discovery
(2020) Souza Neto, Lauro Ribeiro de; Moreira Filho, José Teófilo; Neves, Bruno Junior; Riveros Maidana, Rocío Lucía Beatriz; Guimarães, Ana Carolina Ramos; Furnham, Nicholas; Andrade, Carolina Horta; Silva Junior, Floriano Paes
Fragment-based drug (or lead) discovery (FBDD or FBLD) has developed in the last two decades to become a successful key technology in the pharmaceutical industry for early stage drug discovery and development. The FBDD strategy consists of screening low molecular weight compounds against macromolecular targets (usually proteins) of clinical relevance. These small molecular fragments can bind at one or more sites on the target and act as starting points for the development of lead compounds. In developing the fragments attractive features that can translate into compounds with favorable physical, pharmacokinetics and toxicity (ADMET—absorption, distribution, metabolism, excretion, and toxicity) properties can be integrated. Structure-enabled fragment screening campaigns use a combination of screening by a range of biophysical techniques, such as differential scanning fluorimetry, surface plasmon resonance, and thermophoresis, followed by structural characterization of fragment binding using NMR or X-ray crystallography. Structural characterization is also used in subsequent analysis for growing fragments of selected screening hits. The latest iteration of the FBDD workflow employs a high-throughput methodology of massively parallel screening by X-ray crystallography of individually soaked fragments. In this review we will outline the FBDD strategies and explore a variety of in silico approaches to support the follow-up fragment-to-lead optimization of either: growing, linking, and merging. These fragment expansion strategies include hot spot analysis, druggability prediction, SAR (structure-activity relationships) by catalog methods, application of machine learning/deep learning models for virtual screening and several de novo design methods for proposing synthesizable new compounds. Finally, we will highlight recent case studies in fragment-based drug discovery where in silico methods have successfully contributed to the development of lead compounds.
Computational chemogenomics drug repositioning strategy enables the discovery of epirubicin as a new repurposed hit for Plasmodium falciparum and P. vivax
(2020) Ferreira, Letícia Tiburcio; Rodrigues, Juliana; Cassiano, Gustavo Capatti; Tavella, Tatyana Almeida; Tomaz, Kaira Cristina Peralis; Silva, Djane Clarys Baia da; Souza, Macejane Ferreira de; Lima, Marília Nunes do Nascimento; Mottin, Melina; Almeida, Ludimila Dias; Paim, Juliana Calit; Puça, Maria Carolina Silva de Barros; Melo, Gisely Cardoso de; Bargieri, Daniel Youssef; Neves , Bruno Junior
Widespread resistance against antimalarial drugs thwarts current efforts for controlling the disease and urges the discovery of new effective treatments. Drug repositioning is increasingly becoming an attractive strategy since it can re duce costs, risks, and time-to-market. Herein, we have used this strategy to iden tify novel antimalarial hits. We used a comparative in silico chemogenomics approach to select Plasmodium falciparum and Plasmodium vivax proteins as potential drug targets and analyzed them using a computer-assisted drug repositioning pipeline to iden tify approved drugs with potential antimalarial activity. Among the seven drugs identified as promising antimalarial candidates, the anthracycline epirubicin was selected for further experimental validation. Epirubicin was shown to be potent in vitro against sensitive and multidrug-resistant P. falciparum strains and P. vivax field isolates in the nanomolar range, as well as being effective against an in vivo murine model of Plasmodium yoelii. Transmission-blocking activity was ob served for epirubicin in vitro and in vivo. Finally, using yeast-based haploinsuffi- ciency chemical genomic profiling, we aimed to get insights into the mechanism of action of epirubicin. Beyond the target predicted in silico (a DNA gyrase in the apicoplast), functional assays suggested a GlcNac-1-P-transferase (GPT) enzyme as a potential target. Docking calculations predicted the binding mode of epiru bicin with DNA gyrase and GPT proteins. Epirubicin is originally an antitumoral agent and presents associated toxicity. However, its antiplasmodial activity against not only P. falciparum but also P. vivax in different stages of the parasite life cycle supports the use of this drug as a scaffold for hit-to-lead optimization in malaria drug discovery
Natural compounds as non-nucleoside inhibitors of Zika virus polymerase through integration of in silico and in vitro approaches
(2022) Ramos, Paulo Ricardo Pimenta da Silva; Mottin, Melina; Lima, Caroline Sprengel; Assis, Leticia Ribeiro de; Oliveira, Ketllyn Zagato de; Mesquita, Nathalya Cristina de Moraes Roso; Cassani, Natasha Marques; Santos, Igor de Andrade; Borba, Joyce Villa Verde Bastos; Costa, Vinícius Alexandre Fiaia; Neves, Bruno Junior
Although the past epidemic of Zika virus (ZIKV) resulted in severe neurological conse quences for infected infants and adults, there are still no approved drugs to treat ZIKV infection. In this study, we applied computational approaches to screen an in-house database of 77 natural and semi-synthetic compounds against ZIKV NS5 RNA-dependent RNA-polymerase (NS5 RdRp), an essential protein for viral RNA elongation during the replication process. For this purpose, we integrated computational approaches such as binding-site conservation, chemical space analysis and molecular docking. As a result, we prioritized nine virtual hits for experimental evaluation. Enzymatic assays confirmed that pedalitin and quercetin inhibited ZIKV NS5 RdRp with IC50 values of 4.1 and 0.5 µM, respectively. Moreover, pedalitin also displayed antiviral activity on ZIKV infection with an EC50 of 19.28 µM cell-based assays, with low toxicity in Vero cells (CC50 = 83.66 µM) and selectivity index of 4.34. These results demonstrate the potential of the natural compounds pedal itin and quercetin as candidates for structural optimization studies towards the discovery of new anti-ZIKV drug candidates.
Starting anti-covid-19 drug discovery with natural products
(2021) Silva, Osmar Nascimento; Neves, Bruno Junior; Rosseto, Lucimar Pinheiro; Moura, Rodrigo Scaliant; Napolitano, Hamilton Barbosa; Brito, Wesley de Almeida; Fajemiroye, James Oluwagbamigbe; Pinto, Emerith Mayra Hungria; Perjési, Pál; Martins, José Luís Rodrigues
Antimalarial drugs with novel modes of action and wide therapeutic potential are needed to pave the way for malaria eradication. Violacein is a natural compound known for its biological activity against cancer cells and several pathogens, including the malaria parasite, Plasmodium falciparum (Pf). Herein, using chemical genomic profiling (CGP), we found that violacein affects protein homeostasis. Mechanistically, violacein binds Pf chaperones, PfHsp90 and PfHsp70-1, compromising the latter's ATPase and chaperone activities. Additionally, violacein-treated parasites exhibited increased protein unfolding and proteasomal degradation. The uncoupling of the parasite stress response reflects the multistage growth inhibitory effect promoted by violacein. Despite evidence of proteotoxic stress, violacein did not inhibit global protein synthesis via UPR activation-a process that is highly dependent on chaperones, in agreement with the notion of a violacein-induced proteostasis collapse. Our data highlight the importance of a functioning chaperone-proteasome system for parasite development and differentiation. Thus, a violacein-like small molecule might provide a good scaffold for development of a novel probe for examining the molecular chaperone network and/or antiplasmodial drug design.
DNA-based electrodes and computational approaches on the intercalation study of antitumoral drugs
(2021) Rodrigues, Edson Silvio Batista; Macêdo, Isaac Yves Lopes de; Silva, Giovanna Nascimento de Mello e; Silva, Arthur de Carvalho e; Gil, Henric Pietro Vicente; Neves, Bruno Junior; Gil, Eric de Souza
The binding between anticancer drugs and double-stranded DNA (dsDNA) is a key issue to understand their mechanism of action, and many chemical methods have been explored on this task. Molecular docking techniques successfully predict the affinity of small molecules into the DNA binding sites. In turn, various DNA-targeted drugs are electroactive; in this regard, their electrochemical behavior may change according to the nature and strength of interaction with DNA. A carbon paste electrode (CPE) modified with calf thymus ds-DNA (CPDE) and computational methods were used to evaluate the drug–DNA intercalation of doxorubicin (DOX), daunorubicin (DAU), idarubicin (IDA), dacarbazine (DAR), mitoxantrone (MIT), and methotrexate (MTX), aiming to evaluate eventual correlations. CPE and CPDE were immersed in pH 7 0.1 mM solutions of each drug with different incubation times. As expected, the CPDE response for all DNA-targeted drugs was higher than that of CPE, evidencing the drug–DNA interaction. A peak current increase of up to 10-fold was observed; the lowest increase was seen for MTX, and the highest increase for MIT. Although this increase in the sensitivity is certainly tied to preconcentration effects of DNA, the data did not agree entirely with docking studies, evidencing the participation of other factors, such as viscosity, interfacial electrostatic interactions, and coefficient of diffusion.
BeeToxAI: an artificial intelligence-based web app to assess acute toxicity of chemicals to honey bees
(2021) Moreira Filho, José Teófilo; Braga, Rodolpho de Campos; Lemos, Jade Milhomem; Alves, Vinicius de Medeiros; Borba, Joyce Villa Verde Bastos; Costa, Wesley dos Santos; Kleinstreuer, Nicole; Muratov, Eugene; Andrade, Carolina Horta; Neves, Bruno Junior
An innovative artificial intelligence-based web app (BeeToxAI) for assessing the acute toxicity of chemicals to Apis mellifera. Initially, we developed and externally validated QSAR models for classification (external set accu racy ∼91%) through the combination of Random Forest and molecular fingerprints to predict the potential for chemicals to cause acute contact toxicity and acute oral toxicity to honey bees. Then, we developed and exter nally validated regression QSAR models (𝑅2 = 0.75) using Feedforward Neural Networks (FNNs). Afterward, the best models were implemented in the publicly available BeeToxAI web app (http://beetoxai.labmol.com.br/). The outputs of BeeToxAI are: toxicity predictions with estimated confidence, applicability domain estimation, and color-coded maps of relative structure fragment contributions to toxicity. As an additional assessment of BeeToxAI performance, we collected an external set of pesticides with known bee toxicity that were not included in our modeling dataset. BeeToxAI classification models were able to predict four out of five pesticides correctly. The acute contact toxicity model correctly predicted all of the eight pesticides. Here we demonstrate that Bee ToxAI can be used as a rapid new approach methodology for predicting acute toxicity of chemicals in honey bees.
Drug repurposing for paracoccidioidomycosis through a computational chemogenomics framework
(2019) Oliveira, Amanda Alves de; Neves, Bruno Junior; Soares, Célia Maria de Almeida; Andrade, Carolina Horta; Pereira, Maristela
Malaria is an infectious disease that affects over 216 million people worldwide, killing over 445,000 patients annually. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new drug candidates is a major global health priority. Aiming to make the drug discovery processes faster and less expensive, we developed binary and continuous Quantitative Structure-Activity Relationships (QSAR) models implementing deep learning for predicting antiplasmodial activity and cytotoxicity of untested compounds. Then, we applied the best models for a virtual screening of a large database of chemical compounds. The top computational predictions were evaluated experimentally against asexual blood stages of both sensitive and multi-drug-resistant Plasmodium falciparum strains. Among them, two compounds, LabMol-149 and LabMol-152, showed potent antiplasmodial activity at low nanomolar concentrations (EC50 <500 nM) and low cytotoxicity in mammalian cells. Therefore, the computational approach employing deep learning developed here allowed us to discover two new families of potential next generation antimalarial agents, which are in compliance with the guidelines and criteria for antimalarial target candidates.
Déjà vu: stimulating open drug discovery for SARS-CoV-2
(2020) Ekins, Sean; Mottin, Melina; Ramos, Paulo Ricardo Pimenta da Silva; Sousa, Bruna Katiele de Paula; Neves, Bruno Junior; Foil, Daniel H.; Zorn, Kimberley Marie; Braga, Rodolpho de Campos; Coffee, Megan; South, Christopher
In the past decade we have seen two major Ebola virus outbreaks in Africa, the Zika virus in Brazil and the Americas and the current pandemic of coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is a strong sense of déjà vu because there are still no effective treatments. In the COVID-19 pandemic, despite being a new virus, there are already drugs suggested as active in in vitro assays that are being repurposed in clinical trials. Promising SARS-CoV-2 viral targets and computational approaches are described and discussed. Here, we propose, based on open antiviral drug discovery approaches for previous outbreaks, that there could still be gaps in our approach to drug discovery.
Automated framework for developing predictive machine learning models for data-driven drug discovery
(2021) Neves, Bruno Junior; Moreira Filho, José Teófilo; Silva, Arthur de Carvalho e; Borba, Joyce Villa Verde Bastos; Mottin, Melina; Alves, Vinicius de Medeiro; Braga, Rodolpho de Campos; Muratov, Eugene; Andrade, Carolina Horta
The increasing availability of extensive collections of chemical compounds associated with experimental data provides an opportunity to build predictive quantitative structure-activity relationship (QSAR) models using machine learning (ML) algorithms. These models can promote data-driven decisions and have the potential to speed up the drug discovery process and reduce their failure rates. However, many essential aspects of data preparation and modeling are not available in any standalone program. Here, we developed an automated framework for the curation of chemogenomics data and to develop QSAR models for virtual screening using the open-source KoNstanz Information MinEr (KNIME) program. The workflow includes four modules: (i) dataset preparation and curation; (ii) chemical space analysis and structure-activity relationships (SAR) rules; (iii) modeling; and (iv) virtual screening (VS). As case studies, we applied these workflows to four datasets associated with different endpoints. The implemented protocol can efficiently curate chemical and biological data in public databases and generates robust QSAR models. We provide scientists a simple and guided cheminformatics workbench following the best practices widely accepted by the community, in which scientists can adapt to solve their research problems. The workflows are freely available for download at GitHub and LabMol web portals.
Violacein-induced chaperone system collapse underlies multistage antiplasmodial activity
(2021) Tavella, Tatyana Almeida Tavella; Silva, Noeli Soares Melo da; Spillman, Natalie; Andrade, Ana Carolina; Kayano, Vitor; Cassiano, Gustavo Capatti; Vasconcelos, Adrielle Ayumi; Camargo, Antônio Pedro de Castello Branco da Rocha; Silva, Djane Clarys Baia da; Fontinha, Diana; Salazar Alvarez, Luis Carlos; Neves, Bruno Junior
Antimalarial drugs with novel modes of action and wide therapeutic potential are needed to pave the way for malaria eradication. Violacein is a natural compound known for its biological activity against cancer cells and several pathogens, including the malaria parasite, Plasmodium falciparum (Pf). Herein, using chemical genomic profiling (CGP), we found that violacein affects protein homeostasis. Mechanistically, violacein binds Pf chaperones, Pf Hsp90 and Pf Hsp70-1, compromising the latter’s ATPase and chaperone activities. Additionally, violacein-treated parasites exhibited increased protein unfolding and proteasomal degradation. The uncoupling of the parasite stress response reflects the multistage growth inhibitory effect promoted by violacein. Despite evidence of proteotoxic stress, violacein did not inhibit global protein synthesis via UPR activationa process that is highly dependent on chaperones, in agreement with the notion of a violacein-induced proteostasis collapse. Our data highlight the importance of a functioning chaperone−proteasome system for parasite development and differentiation. Thus, a violacein-like small molecule might provide a good scaffold for development of a novel probe for examining the molecular chaperone network and/or antiplasmodial drug design.
Setting new routes for antifungal drug discovery against pathogenic fungi
(2020) Silva, Kleber Santiago Freitas e; Silva, Lívia do Carmo; Gonçales, Relber Aguiar; Neves, Bruno Junior; Soares, Célia Maria de Almeida; Pereira, Maristela
Fungal diseases are life-threatening to human health and responsible for millions of deaths around the world. Fungal pathogens lead to a high number of morbidity and mortality. Current antifungal treatment comprises drugs, such as azoles, echinocandins, and polyenes and the cure is not guaranteed. In addition, such drugs are related to severe side effects and the treatment lasts for an extended period. Thus, setting new routes for the discovery of effective and safe antifungal drugs should be a priority within the health care system. The discovery of alternative and efficient antifungal drugs showing fewer side effects is time-consuming and remains a challenge. Natural products can be a source of antifungals and used in combinatorial therapy. The most important natural products are antifungal peptides, antifungal lectins, antifungal plants, and fungi secondary metabolites. Several proteins, enzymes, and metabolic pathways could be targets for the discovery of efficient inhibitor compounds and recently, heat shock proteins, calcineurin, salinomycin, the trehalose biosynthetic pathway, and the glyoxylate cycle have been investigated in several fungal species. HSP protein inhibitors and echinocandins have been shown to have a fungicidal effect against azole-resistant fungi strains. Transcriptomic and proteomic approaches have advanced antifungal drug discovery and pointed to new important specific-pathogen targets. Certain enzymes, such as those from the glyoxylate cycle, have been a target of antifungal compounds in several fungi species. Natural and synthetic compounds inhibited the activity of such enzymes and reduced the ability of fungal cells to transit from mycelium to yeast, proving to be promisor antifungal agents. Finally, computational biology has developed effective approaches, setting new routes for early antifungal drug discovery since normal approaches take several years from discovery to clinical use. Thus, the development of new antifungal strategies might reduce the therapeutic time and increase the quality of life of patients.
Acetaminophen treatment evokes anticontractile effects in rat aorta by blocking L-type calcium channels
(2022) Correia, Mikaelle Costa; Santos, Eder S. A.; Neves, Bruno Junior; Rocha, Matheus Lavorenti
Background Acetaminophen (APAP) is the most widely used analgesic and antipyretic in the world. However, in high or continuous doses, it can cause serious side effects including blood pressure variability and cardiovascular injuries, which are barely explored. This study aimed to evaluate the acute effect of APAP treatment on vascular tone focused on the blocking of Ca2+ channels. Methods Rats were treated with APAP orally by gavage (500 mg/kg/single dose). After 12 h, the aorta was isolated for vascular reactivity studies in an isolated organ bath. Vascular contraction and relaxation were measured after different stimuli. Moreover, molecular docking studies were performed to evaluate the action of NAPQI (APAP metabolite) on L-type calcium channels. Results Phenylephrine-induced maximal vascular contraction was reduced in the APAP group (138.4 ± 9.2%) compared to the control group (172.2 ± 11.1%). APAP treatment significantly reduced contraction induced by Ca2+ influx stimulated with phenylephrine or KCl and reduced contraction mediated by Ca2+ released from the sarcoplasmic reticulum induced by caffeine. There was no difference in vascular relaxation induced by acetylcholine or sodium nitroprusside. Computational molecular docking demonstrated that NAPQI is capable of blocking L-type Ca2+ channels (Cav1.2), which would limit the influx of Ca2+. Conclusion These results suggest that APAP treatment causes an anticontractile effect in rat aorta, possibly by blocking the influx of Ca2+ through L-type channels (Cav1.2).
A structure-based approach for the discovery of inhibitors against methylcitrate synthase of Paracoccidioides lutzii
(2021) Lima, Raisa Melo; Silva, Kleber Santiago Freitas e; Silva, Lívia do Carmo; Ribeiro, Jean Francisco Rosa; Neves, Bruno Junior; Brock, Matthias; Soares, Célia Maria de Almeida; Silva, Roosevelt Alves da; Pereira, Maristela
Paracoccidioidomycosis (PCM) is a systemic mycosis, endemic in Latin America, caused by fungi of the genus Paracoccidioides. The treatment of PCM is complex, requiring a long treatment period, which often results in serious side effects. The aim of this study was to screen for inhibitors of a specific target of the fungus that is absent in humans. Methylcitrate synthase (MCS) is a unique enzyme of microorganisms and is responsible for the synthesis of methylcitrate at the beginning of the propionate degradation pathway. This pathway is essential for several microorganisms, since the accumulation of propionyl-CoA can impair virulence and prevent the development of the pathogen. We performed the modeling and molecular dynamics of the structure of Paracoccidioides lutzii MCS (PlMCS) and performed a virtual screening on 89,415 compounds against the active site of the enzyme. The compounds were selected according to the affinity and efficiency criteria of in vitro tests. Six compounds were able to inhibit the enzymatic activity of recombinant PlMCS but only the compound ZINC08964784 showed fungistatic and fungicidal activity against Paracoccidioides spp. cells. The analysis of the interaction profile of this compound with PlMCS showed its effectiveness in terms of specificity and stability when compared to the substrate (propionyl-CoA) of the enzyme. In addition, this compound did not show cytotoxicity in mammalian cells, with an excellent selectivity index. Our results suggest that the compound ZINC08964784 may become a promising alternative antifungal against Paracoccidioides spp.
Vascular relaxing effect of Hydrocotyle umbellata L. is mediated by blocking of l-type Ca2+ channels
(2022) Bufáiçal, Daniela Medeiros Lobo de Andrade; Correia, Mikaelle Costa ; Oliveira, Matheus Gabriel de; Santos, Eder Soares de Almeida; Neves, Bruno Junior; Paula, José Realino de; Rocha, Matheus Lavorenti
Ethnopharmacological relevance Hydrocotyle umbellata L. is a medicinal herb for the treatment of some health problems including hypertension, according to traditional medicine. Even so, its vascular effects and the pharmacological action mechanisms have not been analyzed. Aim of the study This experiment aimed to analyze the effects of hydroalcoholic extract of Hydrocotyle umbellata L. (HEHU) on isolated vessels and verify the interaction of hibalactone (chemical marker) against Cav1.2 channels using molecular docking. Materials and methods Vascular reactivity experiments were performed using rat aortas with (E+) or without endothelium (E−) in an isolated organ bath. Computational molecular docking approaches were used to show the direct effect on L-type Ca2+ Channels. Results HEHU (0–560 μg/mL) induced relaxation of the pre-contracted arteries in a concentration-dependent manner. The maximum effect was higher in E+ (76.8 ± 4.1%) as compared to E− (47.3 ± 5.5%). Pre-treatment of E+ arteries with L-NAME or ODQ reduced the relaxation to similar level of E− arteries. The treatment of arteries with MDL-12,330 A, diclofenac, propranolol and atropine did not change the relaxation induced by HEHU. The contraction caused by internal Ca2+ release induced by caffeine was reduced after HEHU treatment. Moreover, the HEHU also impaired the contraction induced by Ca2+ influx stimulated with phenylephrine or high KCl. The docking study demonstrated the effectiveness of hibalactone in blocking the Cav1.2 channel. Conclusions These findings show that HEHU induces vascular relaxation which is potentiated (but not dependent) by endothelial cells. Blocking of Ca2+ influx seems to be the main mechanism for the vascular effects of HEHU.
Nitrogen catabolite repression in members of Paracoccidioides complex
(2020) Leite, Vanessa Rafaela Milhomem Cruz; Furlaneto, Silvia Maria Salem Izacc; Novaes, Evandro; Neves, Bruno Junior; Brito, Wesley de Almeida; Silva, Lana OHara Souza; Paccez, Juliano Domiraci; Rocha, Juliana Alves Parente; Pereira, Maristela; Soares, Célia Maria de Almeida; Borges, Clayton Luiz
Paracoccidioides complex is a genus that comprises pathogenic fungi which are responsible by systemic disease Paracoccidioidomycosis. In host tissues, pathogenic fungi need to acquire nutrients in order to survive, making the uptake of nitrogen essential for their establishment and dissemination. Nitrogen utilization is employed by the alleviation of Nitrogen Catabolite Repression (NCR) which ensures the use of non-preferential or alternative nitrogen sources when preferential sources are not available. NCR is controlled by GATA transcription factors which act through GATA binding sites on promoter regions in NCR-sensitive genes. This process is responsible for encoding proteins involved with the scavenge, uptake and catabolism of a wide variety of non-preferential nitrogen sources. In this work, we predict the existence of AreA GATA transcription factor and feature the zinc finger domain by three-dimensional structure in Paracoccidioides. Furthermore, we demonstrate the putative genes involved with NCR response by means of in silico analysis. The gene expression profile under NCR conditions was evaluated. Demonstrating that P. lutzii supported transcriptional regulation and alleviated NCR in non-preferential nitrogen-dependent medium. The elucidation of NCR in members of Paracoccidioides complex will provide new knowledge about survival, dissemination and virulence for these pathogens with regard to nitrogen-scavenging strategies in the interactions of host-pathogens.
Antitrypanosomal activity of acetogenins isolated from the seeds of is associated with alterations in both plasma membrane electric potential and mitochondrial membrane potentia
(2019) Oliveira, Emerson Alves de; Brito, Ivanildo Afonso de; Lima, Marta Lopes; Silva, Maiara Maria Romanelli; Moreira Filho, José Teófilo; Neves, Bruno Junior; Andrade, Carolina Horta; Sartorelli, Patricia; Cardoso, André Gustavo Tempone; Silva, Thais Alves da Costa; Lago, João Henrique Ghilardi
As part of a drug discovery program aimed at the identification of anti-Trypanosoma cruzi metabolites from Brazilian flora, four acetogenins (1–4) were isolated from the seeds of Porcelia macrocarpa and were identified by NMR spectroscopy and HRESIMS. The new compounds 1 and 2 displayed activity against the trypomastigote (IC50 = 0.4 and 3.6 μM) and amastigote (IC50 = 23.0 and 27.7 μM) forms. The structurally related known compound 3 showed less potency to the amastigotes, with an IC50 value of 58 μM, while the known compound 4 was inactive. To evaluate the potential mechanisms for parasite death, parameters were evaluated by fluorometric assays: (i) plasma membrane permeability, (ii) plasma membrane electric potential (ΔΨp), (iii) reactive oxygen species production, and (iv) mitochondrial membrane potential (ΔΨm). The results obtained indicated that compounds 1 and 2 depolarize plasma membranes, affecting ΔΨp and ΔΨm and contributing to the observed cellular damage and disturbing the bioenergetic system. In silico studies of pharmacokinetics and toxicity (ADMET) properties predicted that all compounds were nonmutagenic, noncarcinogenic, nongenotoxic, and weak hERG blockers. Additionally, none of the isolated acetogenins 1–4 were predicted as pan-assay interference compounds.
Involvement of the gabaergic, serotonergic and glucocorticoid mechanism in the anxiolytic-like effect of mastoparan-L
(2020) Silva, Osmar Nascimento; Franco, Octávio Luiz; Neves, Bruno Junior; Morais, Álice Cristina Borges; Oliveira Neto, Jerônimo Raimundo de; Cunha, Luiz Carlos da; Pedrino, Gustavo Rodrigues; Naves, Lara Marques; Costa, Elson Alves; Fajemiroye, James Oluwagbamigbe
Mastoparan-L (mast-L) is a cell-penetrating tetradecapeptide and stimulator of monoamine exocytosis. In the present study, we evaluated the anxiolytic-like effect of mast-L. Preliminary pharmacological tests were conducted to determine the most appropriate route of administration, extrapolate dose and detect potential toxic effects of this peptide. Oral and intracerebroventricular administration of mast-L (0.1, 0.3 or 0.9 mg.kg−1), diazepam (1 or 5 mg.kg−1), buspirone (10 mg.kg−1) or vehicle 10 mL.kg−1 was carried out prior to the exposure of mice to the anxiety models: open field, light-dark box and elevated plus-maze. To characterize the mechanism underlying the antianxiety-like effect of mast-L, pharmacological antagonism, blood plasma analysis, molecular docking, and receptor binding assays were performed. The absence of a neurotoxic sign, animal's death as well as lack of significant changes in the relative organ weight, hematological and biochemical parameters suggest that mast-L is relatively safe. The anxiolytic-like effect of mast-L was attenuated by flumazenil (antagonist of benzodiazepine binding site) and WAY100635 (selective antagonist of 5-HT1A receptors) pretreatments. Mast-L reduced plasma corticosterone and lowered the scoring function at GABAA −18.48 kcal/mol (Ki = 155 nM), 5-HT1A −22.39 kcal/mol (Ki = 130 nM), corticotropin-releasing factor receptor subtype 1 (CRF1) −11.95 kcal/mol (Ki = 299 nM) and glucocorticoid receptors (GR) −14.69 kcal/mol (Ki = 3552 nM). These data fit the binding affinity (Ki) and demonstrate the involvement of gabaergic, serotonergic and glucocorticoid mechanisms in the anxiolytic-like property of mast-L.

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