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Currently, there is no approved drug to combat dengue. Various quinoline derivatives are known for potential antimalarial, antiviral activities, etc. In the present work docking between 4-Amino-7-Chloroquinoline analogs was performed with dengue virus NS2B/NS3 protease using CB dock, a web server. Lys74, Ile165, Val147, Asn152, Asn167, Trp83 and Leu149 amino acid residues were found to be in contact with designed 4-Amino-7-Chloroquinoline analogs. Different modes of binding like hydrogen bonding, hydrophobic interactions, etc with designed compounds improve potential anti-dengue characteristics in silico. ADME results are in acceptable range.
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Currently, there is no approved drug to combat dengue. Various quinoline derivatives are known for potential antimalarial, antiviral activities, etc. In the present work docking between 4-Amino-7-Chloroquinoline analogs was performed with dengue virus NS2B/NS3 protease using CB dock, a web server. Lys74, Ile165, Val147, Asn152, Asn167, Trp83 and Leu149 amino acid residues were found to be in contact with designed 4-Amino-7-Chloroquinoline analogs. Different modes of binding like hydrogen bonding, hydrophobic interactions, etc with designed compounds improve potential anti-dengue characteristics in silico. ADME results are in acceptable range.
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@#In recent years, artificial intelligence (AI) has been widely applied in the field of drug discovery and development.In particular, natural language processing technology has been significantly improved after the emergence of the pre-training model.On this basis, the introduction of graph neural network has also made drug development more accurate and efficient.In order to help drug developers more systematically and comprehensively understand the application of artificial intelligence in drug discovery, this article introduces cutting-edge algorithms in AI, and elaborates on the various applications of AI in drug development, including drug small molecule design, virtual screening, drug repurposing, and drug property prediction, finally discusses the opportunities and challenges of AI in future drug development.
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@#Artificial intelligence (AI) has developed rapidly in the twentieth century, and has substantialy changed the modern way of life.At the same time, AI has greatly contributed to the development of the pharmaceutical industry, playing a key role in precision medicine, intelligent diagnosis, computer-aided drug design, and clinical trial decision-making, and has also greatly developed itself through its integration with the pharmaceutical industry.This paper outlines the key issues in research, describes the key applications of AI in the health and pharmaceutical industries, and finally analyzes the opportunities and challenges of AI in the health pharmaceutical industry to provide reference for the development of AI in the health and pharmaceutical fields.
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In this study, we explored the mechanism of Huganning tablet (HGNP) in the treatment of nonalcoholic fatty liver disease (NAFLD) based on network pharmacology and computer-aided drug design. Firstly, the potential ingredients and targets of HGNP were identified from TCMSP database, Swiss Target Prediction database, Chinese pharmacopoeia (2015) and literatures, and then the targets of HGNP intersected with NAFLD disease targets that obtained in GeneCards database to acquired potential targets. The bioconductor bioinformatics package of R software was used for gene ontology (GO) enrichment and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. The network of “potential ingredient-key target-pathway” was formed in Cytoscape software to study the interactions between potential ingredients of HGNP, key targets, pathways and NAFLD. Based on the results of network pharmacology, the molecular docking analysis of the key targets and potential active ingredients in HGNP tablets with top degree in the network was conducted using Discovery Studio 2020 software, followed by molecular dynamics simulations, binding free energy calculation, drug-likeness properties analysis and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties prediction. In vitro, HepG2 cells were used to establish steatosis model, and the effects of five key compounds on hepatocyte steatosis were analyzed by oil red O staining and triglyceride (TG) content determination. The results showed that 141 ingredients and 151 potential targets were obtained. A total of 2 526 items and 151 pathways were identified by GO and KEGG enrichment analysis. The molecular docking suggested that five components, isorhamnetin, salvianolic acid B, emodin, resveratrol and rhein, exhibited strong binding ability with key targets [retinoic acid receptor RXR-alpha (RXRA), tumor necrosis factor (TNF), glycogen synthase kinase-3 beta (GSK3B), serine/threonine-protein kinase 1 (AKT1)]. It was further verified that isorhamnetin and salvianolic acid B bind to key targets with good structural stability and binding affinity based on molecular dynamics simulations and binding free energy calculations. The drug-likeness properties, pharmacokinetic properties and toxicity of five key compounds were more comprehensively analyzed through drug-likeness properties analysis and ADMET properties prediction. In vitro, all five compounds, isorhamnetin, salvianolic acid B, emodin, resveratrol, and rhein, improved hepatocyte steatosis of HepG2 cells, confirming the reliability of the present study. In conclusion, based on network pharmacology, computer-aided drug design and in vitro validation, this study investigated the mechanism of HGNP for the treatment of NAFLD at multiple levels and provided a basis for its clinical application.
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Various c-mesenchymal-to-epithelial transition (c-MET) inhibitors are effective in the treatment of non-small cell lung cancer; however, the inevitable drug resistance remains a challenge, limiting their clinical efficacy. Therefore, novel strategies targeting c-MET are urgently required. Herein, through rational structure optimization, we obtained novel exceptionally potent and orally active c-MET proteolysis targeting chimeras (PROTACs) namely D10 and D15 based on thalidomide and tepotinib. D10 and D15 inhibited cell growth with low nanomolar IC50 values and achieved picomolar DC50 values and >99% of maximum degradation (Dmax) in EBC-1 and Hs746T cells. Mechanistically, D10 and D15 dramatically induced cell apoptosis, G1 cell cycle arrest and inhibited cell migration and invasion. Notably, intraperitoneal administration of D10 and D15 significantly inhibited tumor growth in the EBC-1 xenograft model and oral administration of D15 induced approximately complete tumor suppression in the Hs746T xenograft model with well-tolerated dose-schedules. Furthermore, D10 and D15 exerted significant anti-tumor effect in cells with c-METY1230H and c-METD1228N mutations, which are resistant to tepotinib in clinic. These findings demonstrated that D10 and D15 could serve as candidates for the treatment of tumors with MET alterations.
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With the advances in medicine, people have deeply understood the complex pathogenesis of diseases. Revealing the mechanism of action and therapeutic effect of drugs from an overall perspective has become the top priority of drug design. However, the traditional drug design methods cannot meet the current needs. In recent years, with the rapid development of systems biology, a variety of new technologies including metabolomics, genomics, and proteomics have been used in drug research and development. As a bridge between traditional pharmaceutical theory and modern science, computer-aided drug design(CADD) can shorten the drug development cycle and improve the success rate of drug design. The application of systems biology and CADD provides a methodological basis and direction for revealing the mechanism and action of drugs from an overall perspective. This paper introduces the research and application of systems biology in CADD from different perspectives and proposes the development direction, providing reference for promoting the application.
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Humans , Systems Biology , Drug Design , Drug Development , Genomics , MedicineABSTRACT
Self-assembly refers to the spontaneous process where basic units such as molecules and nanostructured materials form a stable and compact structure. Peptides can self-assemble by non-covalent driving forces to form various morphologies such as nanofibers, nano layered structures, and micelles. Peptide self-assembly technology has become a hot research topic in recent years due to the advantages of definite amino acid sequences, easy synthesis and design of peptides. It has been shown that the self-assembly design of certain peptide drugs or the use of self-assembled peptide materials as carriers for drug delivery can solve the problems such as short half-life, poor water solubility and poor penetration due to physiological barrier. This review summarizes the formation mechanism of self-assembled peptides, self-assembly morphology, influencing factors, self-assembly design methods and major applications in biomedical field, providing a reference for the efficient use of peptides.
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Pharmaceutical Preparations , Peptides/chemistry , Amino Acid Sequence , Nanostructures/chemistry , Drug Delivery SystemsABSTRACT
Abstract Quantitative Structure-Activity Relationship (QSAR) is a computer-aided technology in the field of medicinal chemistry that seeks to clarify the relationships between molecular structures and their biological activities. Such technologies allow for the acceleration of the development of new compounds by reducing the costs of drug design. This work presents 3D-QSARpy, a flexible, user-friendly and robust tool, freely available without registration, to support the generation of QSAR 3D models in an automated way. The user only needs to provide aligned molecular structures and the respective dependent variable. The current version was developed using Python with packages such as scikit-learn and includes various techniques of machine learning for regression. The diverse techniques employed by the tool is a differential compared to known methodologies, such as CoMFA and CoMSIA, because it expands the search space of possible solutions, and in this way increases the chances of obtaining relevant models. Additionally, approaches for select variables (dimension reduction) were implemented in the tool. To evaluate its potentials, experiments were carried out to compare results obtained from the proposed 3D-QSARpy tool with the results from already published works. The results demonstrated that 3D-QSARpy is extremely useful in the field due to its expressive results.
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Drug Design , Quantitative Structure-Activity Relationship , Machine Learning/classification , Costs and Cost Analysis/classification , Health Services Needs and Demand/classificationABSTRACT
The binding of small molecule drugs to targets is mostly through non-covalent bonds, and hydrogen bond, electrostatic, hydrophobic and van der Waals interactions function to maintain the binding force. The more these binding factors lead to strong bindings and high activities. However, it is often accompanied by the increase of molecular size, resulting in pharmacokinetic problems such as membrane penetration and absorption, as well as metabolism, which ultimately affects the drug success. Fragment-based drug discovery (FBDD) is to screen high-quality fragment library to find hits. Combine with structural biology, FBDD generates lead compounds by means of fragment growth, linking and fusion, and finally drug candidates by the optimization operation. During the value chain FBDD is closely related to structure-based drug discovery (SBDD). In this paper, the principle of FBDD is briefly described by several launched drugs.
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In this study, we investigated the effect of Cigu Xiaozhi formula on HSC-T6 activity in hypoxic microenvironment based on network pharmacology and computer-aided drug design, and predicted and verified its possible targets and related signaling pathways. The potential active components and targets of Cigu Xiaozhi formula were screened by searching Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Encyclopaedia of Traditional Chinese Medicine (ETCM) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) databases, and the liver fibrosis related targets retrieved from Gene Cards and Pharm GK database were integrated to obtain the potential targets of Cigu Xiaozhi formula in the treatment of liver fibrosis. GO enrichment analysis and KEGG signaling pathway enrichment analysis were performed on Omic Share platform, and Cytoscape software was used to construct the "potential active ingredient-key target-pathway" network. The active components and target proteins were subjected to molecular docking analysis by Auto Dock software. According to the results of molecular dynamics simulation and binding free energy calculation, the top 5 active components with degree were scored. The active components stigmasterol and β-sitosterol were subjected to molecular docking. CoCl2 was used to induce HSC-T6 cells to construct hypoxia model in vitro. The cell viability was detected by CCK-8 assay, and the optimal time and concentration of hypoxia model of HSC-T6 cells was determined to be 100 µmol·L-1 CoCl2 for 24 h. Under hypoxia condition, HSC-T6 cells were activated, the wound healing rate was significantly increased, and the fluorescence signal of activation marker protein α-smooth muscle actin (α-SMA) was significantly enhanced. However, 6% drug-containing serum could inhibit the activation of HSC-T6 cells, and the wound healing rate was significantly decreased, and the fluorescence signal of α-SMA was significantly weakened. Further studies showed that the expressions of hypoxia-inducible factor-1α (HIF-1α), α-SMA and key proteins of Hedgehog (Hh) signaling pathway in HSC-T6 cells were up-regulated under hypoxia, while the expressions of HIF-1α, α-SMA, Patched-1 (Ptch-1) and glioma related oncogene homology-1 (Gli-1) were down-regulated in 6% drug-containing serum group, the YC-1 group and the cyclopamine group. These results indicated that HIF-1α and Hh signaling pathways were involved in the activation of HSC-T6 cells, and the traditional Chinese medicine Cigu Xiaozhi formula could inhibit the activation of HSC-T6 cells, and the mechanism may be related to the inhibition of HIF-1α expression and the blocking of Hh signaling pathway. In conclusion, Cigu Xiaozhi formula can inhibit the activation of HSC-T6 cells by directly acting on HIF-1α and Hh signaling pathway, and exert an anti-hepatic fibrosis effect. The animal experimental protocol has been reviewed and approved by Laboratory Animal Ethics Committee of Gansu University of Chinese Medicine, in compliance with the Institutional Animal Care Guidelines.
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Design of structurally-novel drug molecules with deep learning can overcome the technical bottleneck of classical computer-aided drug design. It has become the frontier of new technique research on drug design, and has shown great potential in drug research and development practice. This review starts from the basic principles of deep learning-driven de novo drug design, goes on with the brief introduction to deep molecular generation techniques as well as computational tools and the analysis on representative successful cases, and eventually provides our perspective for future direction and application prospect about this technique. This review will provide ideas on new technique research and references for new drug research and development practice to which this technique is applied.
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Vascular dementia (VaD) is the second commonest type of dementia which lacks of efficient treatments currently. Neuroinflammation as a prominent pathological feature of VaD, is highly involved in the development of VaD. In order to verify the therapeutic potential of PDE1 inhibitors against VaD, the anti-neuroinflammation, memory and cognitive improvement were evaluated in vitro and in vivo by a potent and selective PDE1 inhibitor 4a. Also, the mechanism of 4a in ameliorating neuroinflammation and VaD was systematically explored. Furthermore, to optimize the drug-like properties of 4a, especially for metabolic stability, 15 derivatives were designed and synthesized. As a result, candidate 5f, with a potent IC50 value of 4.5 nmol/L against PDE1C, high selectivity over PDEs, and remarkable metabolic stability, efficiently ameliorated neuron degeneration, cognition and memory impairment in VaD mice model by suppressing NF-κB transcription regulation and activating cAMP/CREB axis. These results further identified PDE1 inhibition could serve as a new therapeutic strategy for treatment of VaD.
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Artificial intelligence (AI) is often being touted as the means to bring about the fourth industrial revolution and its role in almost all sectors of our society is almost certain. This brings about an urgent need for evaluating the benefits and limitations of AI and machine learning (ML) across various sectors. Pharmaceutical industry has pioneered in embracing the use of AI in all its core areas but the success as of now seems very limited. The major advantage of AI is that it reduces the time that is needed for drug development, and in turn, it reduces the costs that are associated with drug development, enhances the returns on investment, and may even cause a decrease in cost for the end user along with improved drug safety. Hence, in this article, we will review the scope and limitations of AI in the pharmaceutical industry along with the brief review of how AI/ML can impact geriatric health care.
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Doenças negligenciadas impõem um fardo humano, social e econômico devastador a mais de um bilhão de pessoas em todo o mundo. Embora existam ferramentas para controlar e até mesmo eliminar muitas dessas doenças, novos produtos terapêuticos precisam urgentemente ser desenvolvidos. Este artigo se baseia em um estudo que buscou quantificar e caracterizar a produção científica global sobre desenvolvimento de novos medicamentos para doenças negligenciadas, por meio de uma análise bibliométrica. De modo a investigar a pesquisa relacionada ao desenvolvimento de novos medicamentos para as doenças negligenciadas em âmbito global na última década, foi utilizada a base de dados Scopus. Observou-se aumento da produção de conhecimento sobre o tema, com relevante participação de autores, instituições e financiamento brasileiros, sobretudo de instituições públicas. Contudo, os esforços realizados têm sido insuficientes, sendo necessária a implementação de estratégias futuras de pesquisa e de financiamento que propiciem maior produção científica e uma tradução da pesquisa básica para a prática clínica.
Neglected diseases impose a devastating human, social, and economic burden on more than one billion people worldwide. While tools exist to control and even eliminate many of these diseases, new therapeutic products urgently need to be developed. This article is based on a study that sought to quantify and characterize the global scientific production on new drug development for neglected diseases through a bibliometric analysis. The Scopus database was used to investigate the research related to the development of new drugs for neglected diseases globally in the last decade. An increase in the production of knowledge about the theme and the relevant participation of Brazilian authors, institutions and funding, especially from public institutions were observed. However, their efforts have been insufficient, and the implementation of future research and funding strategies that provide greater scientific production and a translation of basic research into clinical practice is necessary.
Las enfermedades desatendidas imponen una carga humana, social y económica devastadora a más de mil millones de personas en todo el mundo. A pesar de haber herramientas para controlar y incluso eliminar muchas de estas enfermedades, es necesario desarrollar con urgencia nuevos productos terapéuticos. Este artículo se basa en un estudio lo cual ha buscado cuantificar y caracterizar la producción científica global sobre el desarrollo de nuevos fármacos para enfermedades desatendidas, a través de un análisis bibliométrico. Para inspeccionar investigaciones relacionadas con el desarrollo de nuevos medicamentos para enfermedades desatendidas en ámbito mundial durante la última década se utilizó la base de datos Scopus. Hubo un aumento de la producción de conocimiento sobre el tema, con una participación relevante de autores, instituciones y financiamiento brasileños, especialmente de instituciones públicas. Sin embargo, los esfuerzos realizados siguen siendo insuficientes, requiriendo la implementación de futuras estrategias de investigación y financiamiento que propicien una mayor producción científica y una traducción de la investigación básica a la práctica clínica.
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Humans , Drug Design , Bibliometrics , Scientific Research and Technological Development , Neglected Diseases , Drug Development , Research Design , Therapeutics , Analysis of Situation , Research FinancingABSTRACT
MicroRNA-21(miRNA-21)is highly expressed in various tumors.Small-molecule inhibition of miRNA-21 is considered to be an attractive novel cancer therapeutic strategy.In this study,fluoroquinolone de-rivatives Al-A43 were synthesized and used as miRNA-21 inhibitors.Compound A36 showed the most potent inhibitory activity and specificity for miRNA-21 in a dual-luciferase reporter assay in HeLa cells.Compound A36 significantly reduced the expression of mature miRNA-21 and increased the protein expression of miRNA-21 target genes,including programmed cell death protein 4(PDCD4)and phos-phatase and tensin homology deleted on chromosome ten(PTEN),at 10 uM in HeLa cells.The Cell Counting Kit-8 assay(CCK-8)was used to evaluate the antiproliferative activity of A36;the results showed that the IC50 value range of A36 against six tumor cell lines was between 1.76 and 13.0 μM.Meanwhile,A36 did not display cytotoxicity in BEAS-2B cells(lung epithelial cells from a healthy human donor).Furthermore,A36 significantly induced apoptosis,arrested cells at the G0/G1 phase,and inhibited cell-colony formation in HeLa cells.In addition,mRNA deep sequencing showed that treatment with A36 could generate 171 dysregulated mRNAs in HeLa cells,while the expression of miRNA-21 target gene dual-specificity phosphatase 5(DUSP5)was significantly upregulated at both the mRNA and protein levels.Collectively,these findings demonstrated that A36 is a novel miRNA-21 inhibitor.
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BACKGROUND Gram-negative and Gram-positive bacteria produce beta-lactamase as factors to overcome beta-lactam antibiotics, causing their hydrolysis and impaired antimicrobial action. Class A beta-lactamase contains the chromosomal sulfhydryl reagent variable (SHV, point mutation variants of SHV-1), LEN (Klebsiella pneumoniae strain LEN-1), and other K. pneumoniae beta-lactamase (OKP) found mostly in Klebsiella's phylogroups. The SHV known as extended-spectrum β-lactamase can inactivate most beta-lactam antibiotics. Class A also includes the worrisome plasmid-encoded Klebsiella pneumoniae carbapenemase (KPC-2), a carbapenemase that can inactivate most beta-lactam antibiotics, carbapenems, and some beta-lactamase inhibitors. OBJECTIVES So far, there is no 3D crystal structure for OKP-B, so our goal was to perform structural characterisation and molecular docking studies of this new enzyme. METHODS We applied a homology modelling method to build the OKP-B-6 structure, which was compared with SHV-1 and KPC-2 according to their electrostatic potentials at the active site. Using the DockThor-VS, we performed molecular docking of the SHV-1 inhibitors commercially available as sulbactam, tazobactam, and avibactam against the constructed model of OKP-B-6. FINDINGS From the point of view of enzyme inhibition, our results indicate that OKP-B-6 should be an extended-spectrum beta-lactamase (ESBL) susceptible to the same drugs as SHV-1. MAIN CONCLUSIONS This conclusion advantageously impacts the clinical control of the bacterial pathogens encoding OKP-B in their genome by using any effective, broad-spectrum, and multitarget inhibitor against SHV-containing bacteria.
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BACKGROUND Mycobacterium leprae, the causative agent of Hansen's disease, causes neural damage through the specific interaction between the external phenolic glycolipid-1 (PGL-1) and laminin subunit alpha-2 (LAMA2) from Schwann cells. OBJECTIVE To design a LAMA2-based peptide that targets PGL-1 from M. leprae. METHODS We retrieved the protein sequence of human LAMA2 and designed a specific peptide using the Antimicrobial Peptide Database and physicochemical parameters for antimycobacterial peptide-lipid interactions. We used the AlphaFold2 server to predict its three-dimensional structure, AUTODOCK-VINA for docking, and GROMACS programs for molecular dynamics simulations. FINDINGS We analysed 52 candidate peptides from LAMA2, and subsequent screening resulted in a single 60-mer peptide. The mapped peptide comprises four β-sheets and a random coiled region. This peptide exhibits a 45% hydrophobic ratio, in which one-third covers the same surface. Molecular dynamics simulations show that our predicted peptide is stable in aqueous solution and remains stable upon interaction with PGL-1 binding. In addition, we found that PGL-1 has a preference for one of the two faces of the predicted peptide, which could act as the preferential binding site of PGL-1. MAIN CONCLUSIONS Our LAMA2-based peptide targeting PGL-1 might have the potential to specifically block this key molecule, suggesting that the preferential region of the peptide is involved in the initial contact during the attachment of leprosy bacilli to Schwann cells.
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As doenças negligenciadas são causadas por agentes infecciosos e parasitários, como vírus, bactérias, protozoários e helmintos. Essas doenças são prevalentes em populações de baixa renda que vivem em países em desenvolvimento e são responsáveis por incapacitar e levar milhares de pessoas à morte. Este nome se dá pois, apesar de sua grande relevância médica, recebem pouca atenção dos governos e indústrias farmacêuticas. Dentre essas doenças podemos destacar a Doença de Chagas, doença infecciosa causada pelo parasita hemoflagelado Trypanosoma cruzi. Endêmica em 21 países, com 6 a 7 milhões de pessoas infectadas resultando em 7500 mortes por ano. A quimioterapia disponível contra essa parasitose é baseada em apenas dois medicamentos, o benznidazol e o nifurtimox, ativos principalmente na fase aguda da doença e com efeitos adversos graves que comprometem a adesão ao tratamento e, além disso, apesar dos enormes esforços na pesquisa de novos agentes antichagásicos em nível nacional e internacional, na maioria realizada academicamente, ainda não foram encontradas alternativas terapêuticas para a doença, persistindo, assim, a necessidade de descoberta e desenvolvimento de novos fármacos. O início de um planejamento de um novo fármaco se dá pela definição de um alvo bioquímico a ser utilizado na busca de moléculas que possam exercer a função de inibidores ou moduladores, conforme a atividade biológica desejada. Neste sentido, as sirtuínas 2 (Sir2) são enzimas que se mostraram essenciais para o crescimento in vitro do T. cruzi em suas formas amastigota e epimastigota. No caso de tripanossomatídeos, em geral, a superexpressão de Sir2 está relacionada à sobrevivência de formas amastigotas. Assim, essas evidências indicam que a Sir2 de tripanosomatídeos tem grande potencial como alvo biológico na busca e desenvolvimento de novos fármacos antichagásicos. O objetivo principal deste projeto foi identificar moléculas que apresentaram atividade inibitória para a sirtuína 2 de T. cruzi por meio da utilização da estratégia de Planejamento de Fármacos Baseada no Ligante - Ligand Based Drug Design (LBDD) e o desenvolvimento de análogos dos inibidores da Sir2. A modificação molecular está entre algumas das técnicas tradicionais usadas no desenvolvimento racional de um fármaco, e é usada principalmente no desenvolvimento de análogos, e busca melhorar as propriedades farmacocinéticas e/ou farmacodinâmicas de um protótipo, obter propriedades de interação semelhantes ao alvo e, em alguns casos, revelar uma atividade biológica. Com este intuito, análogos do sirtinol e da salermida foram sintetizados e uma nova rota sintética utilizando o microrreator em fluxo contínuo foi desenvolvida e apresentou rendimento superior quando comparado à síntese em bancada. A partir desta metodologia foram obtidos 20 compostos. Os ensaios in vitro contra formas amastigotas do T. cruzi indicaram que 8 compostos inibiram a atividade parasitária em mais de 50%, na dose de 10 µM, sendo que alguns destes apresentaram maior inibição parasitária quando comparados ao benznidazol, o fármaco de referência e único disponível no Brasil. Com estes resultados preliminares, novos ensaios estão sendo realizados para identificar potência e mecanismo de ação destes candidatos a agentes tripanomicidas
Neglected diseases are caused by infectious and parasitic agents such as viruses, bacteria, protozoa and helminths. These diseases are prevalent in low-income populations living in developing countries and are responsible for disabling and killing thousands of people. They get this name because, despite their great medical relevance, they end up receiving little attention from governments and pharmaceutical industries. Among these diseases, we can highlight Chagas disease, an infectious endemic disease caused by the hemoflagellate parasite Trypanosoma cruzi. This disease is endemic in 21 countries, with 6 to 7 million people infected resulting in 7,500 deaths per year. Chemotherapy is based on just two drugs, benznidazole and nifurtimox, which are mainly active in the acute phase of the disease. These drugs have adverse effects that compromise adherence, even more, considering that they are not effective from the point of view of the chronic phase of the disease. Despite the enormous efforts in researching new anti-chagasic agents at the national and international level, and mostly carried out academically, therapeutic alternatives for the disease have not yet been found, thus, the need for the discovery and development of new drugs persists. Sirtuins 2 (Sir2) are enzymes that have been shown to be essential for the in vitro growth of T. cruzi in its amastigote and epimastigote forms. In the case of trypanosomatids in general, Sir2 overexpression is related to the survival of amastigote forms. Sir2 inhibitors, such as sirtinol, have shown efficacy in leishmanicides. Thus, these evidences indicate that Sir2 from trypanosomatids can be considered as a biological target in the search and development of new anti-chagasic drugs. The beginning of a new drug planning study is the definition of a biochemical target to be used in the search for molecules that can play the role of inhibitors or modulators, according to the desired biological activity. The main objective of this project was to identify molecules that presented inhibitory activity to sirtuin 2 of T. cruzi using the Ligand Based Drug Design (LBDD) strategy of planning and the development of analogues of Sir2 inhibitors. Molecular modification is a traditional technique used in the rational development of a drug, as well as the use of natural products, combinatorial chemistry, high-throughput screening (HTS), among others. Mainly used in the development of analogues, molecular modification is applied for different purposes, among them, it seeks to improve the pharmacokinetic and/or pharmacodynamic properties of a prototype, obtain target-like interaction properties and, in some cases, reveal an activity biological. For this purpose, analogues of sirtinol and salermide were synthesized and a new synthetic route using the microreactor in continuous flow was developed and presented superior yield when compared to benchtop synthesis. From this methodology, 20 compounds were obtained. in vitro assays against amastigote forms of T. cruzi indicated that 8 compounds inhibited parasitic activity by more than 50% at a dose of 10 µM, and some of these showed greater parasitic inhibition when compared to benznidazole, the reference drug, and only available in Brazil. With these preliminary results, new assays are being carried out to identify the potency and mechanism of action of these candidate trypanocidal agents