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1.
Artigo em Inglês | MEDLINE | ID: mdl-36099967

RESUMO

In the protein-protein interactome, we have previously identified a significant overlap between schizophrenia risk genes and genes associated with cognitive performance. Here, we further studied this overlap to identify potential candidate drugs for repurposing to treat the cognitive symptoms in schizophrenia. We first defined a cognition-related schizophrenia interactome from network propagation analyses, and identified drugs known to target more than one protein within this network. Thereafter, we used gene expression data to further select drugs that could counteract schizophrenia-associated gene expression perturbations. Additionally, we stratified these analyses by sex to identify sex-specific pharmacological treatment options for the cognitive symptoms in schizophrenia. After excluding drugs contraindicated in schizophrenia, we identified 12 drug repurposing candidates, most of which have anti-inflammatory and neuroprotective effects. Sex-stratified analyses showed that out of these 12 drugs, four were identified in females only, three were identified in males only, and five were identified in both sexes. Based on our bioinformatics analyses of disease genetics, we suggest 12 candidate drugs that warrant further examination for repurposing to treat the cognitive symptoms in schizophrenia, and suggest that these symptoms could be addressed by sex-specific pharmacological treatment options.


Assuntos
Fármacos Neuroprotetores , Esquizofrenia , Masculino , Feminino , Humanos , Esquizofrenia/complicações , Esquizofrenia/tratamento farmacológico , Esquizofrenia/genética , Reposicionamento de Medicamentos , Fármacos Neuroprotetores/uso terapêutico , Cognição , Biologia Computacional , Proteínas
2.
Reproduction ; 165(1): R9-R23, 2023 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-36305709

RESUMO

In brief: Preterm birth is the leading cause of perinatal morbidity and mortality; however, current therapies offer limited efficacy to delay birth and improve neonatal outcomes. This review explores the potential of repurposing drugs with known safety profiles to quench uterine contractions and inflammation, identifying promising agents for clinical trials. Abstract: Preterm birth is the leading cause of neonatal morbidity and mortality globally. Despite extensive research into the underlying pathophysiology, rates of preterm birth have not significantly reduced. Currently, preterm labour management is based on optimising neonatal outcomes. Treatment involves administering drugs (tocolytics) to suppress uterine contractions to allow sufficient time for transfer to an appropriate facility and administration of antenatal corticosteroids for fetal lung maturation. Current tocolytics are limited as they are associated with adverse maternal and fetal effects and only delay delivery for a short period. There has been a serious lack of therapeutic development for preterm birth, and new approaches to protect against or delay preterm birth are urgently needed. Repurposing drugs for the prevention of preterm birth presents as a promising approach by reducing the time and costs associated with pharmaceutical drug development. In this review, we explore the evidence for the potential of therapies, specifically proton pump inhibitors, tumour necrosis factor inhibitors, prostaglandin receptor antagonists, aspirin, and statins, to be repurposed as preventatives and/or treatments for preterm birth. Importantly, many of these innovative approaches being explored have good safety profiles in pregnancy. We also review how delivery of these drugs can be enhanced, either through targeted delivery systems or via combination therapy approaches. We aim to present innovative strategies capable of targeting multiple aspects of the complex pathophysiology that underlie preterm birth. There is an urgent unmet need for preterm birth therapeutic development, and these strategies hold great promise for improving neonatal outcomes.


Assuntos
Trabalho de Parto Prematuro , Nascimento Prematuro , Tocolíticos , Recém-Nascido , Feminino , Gravidez , Humanos , Nascimento Prematuro/prevenção & controle , Tocolíticos/uso terapêutico , Preparações Farmacêuticas , Reposicionamento de Medicamentos , Trabalho de Parto Prematuro/tratamento farmacológico , Trabalho de Parto Prematuro/prevenção & controle
3.
J Mol Graph Model ; 118: 108348, 2023 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-36257147

RESUMO

A drug repositioning computational approach was carried to search inhibitors for human thymidylate synthase. An ensemble-based virtual screening of FDA-approved drugs showed the drugs Imatinib, Lumacaftor and Naldemedine to be likely candidates for repurposing. The role of water in the drug-receptor interactions was revealed by the application of an extended AutoDock scoring function that included the water forcefield. The binding affinity scores when hydrated ligands were docked were improved in the drugs considered. Further binding free energy calculations based on the Molecular Mechanics Poisson-Boltzmann Surface Area method revealed that Imatinib, Lumacaftor and Naldemedine scored -130.7 ± 28.1, -210.6 ± 29.9 and -238.0 ± 25.4 kJ/mol, respectively, showing good binding affinity for the candidates considered. Overall, the analysis of the molecular dynamics trajectory of the receptor-drug complexes revealed stable structures for Imatinib, Lumacaftor and Naldemedine, for the entire simulation time.


Assuntos
Reposicionamento de Medicamentos , Timidilato Sintase , Humanos , Reposicionamento de Medicamentos/métodos , Simulação de Acoplamento Molecular , Água/química , Mesilato de Imatinib , Simulação de Dinâmica Molecular
4.
FASEB J ; 37(1): e22660, 2023 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-36468661

RESUMO

Conventional drug discovery requires identifying a protein target believed to be important for disease mechanism and screening compounds for those that beneficially alter the target's function. While this approach has been an effective one for decades, recent data suggest that its continued success is limited largely owing to the highly prevalent irreducibility of biologically complex systems that govern disease phenotype to a single primary disease driver. Network medicine, a new discipline that applies network science and systems biology to the analysis of complex biological systems and disease, offers a novel approach to overcoming these limitations of conventional drug discovery. Using the comprehensive protein-protein interaction network (interactome) as the template through which subnetworks that govern specific diseases are identified, potential disease drivers are unveiled and the effect of novel or repurposed drugs, used alone or in combination, is studied. This approach to drug discovery offers new and exciting unbiased possibilities for advancing our knowledge of disease mechanisms and precision therapeutics.


Assuntos
Descoberta de Drogas , Reposicionamento de Medicamentos , Mapas de Interação de Proteínas , Biologia de Sistemas , Conhecimento
5.
Signal Transduct Target Ther ; 7(1): 387, 2022 Dec 05.
Artigo em Inglês | MEDLINE | ID: mdl-36464706

RESUMO

The outbreak of COVID-19 has become a global crisis, and brought severe disruptions to societies and economies. Until now, effective therapeutics against COVID-19 are in high demand. Along with our improved understanding of the structure, function, and pathogenic process of SARS-CoV-2, many small molecules with potential anti-COVID-19 effects have been developed. So far, several antiviral strategies were explored. Besides directly inhibition of viral proteins such as RdRp and Mpro, interference of host enzymes including ACE2 and proteases, and blocking relevant immunoregulatory pathways represented by JAK/STAT, BTK, NF-κB, and NLRP3 pathways, are regarded feasible in drug development. The development of small molecules to treat COVID-19 has been achieved by several strategies, including computer-aided lead compound design and screening, natural product discovery, drug repurposing, and combination therapy. Several small molecules representative by remdesivir and paxlovid have been proved or authorized emergency use in many countries. And many candidates have entered clinical-trial stage. Nevertheless, due to the epidemiological features and variability issues of SARS-CoV-2, it is necessary to continue exploring novel strategies against COVID-19. This review discusses the current findings in the development of small molecules for COVID-19 treatment. Moreover, their detailed mechanism of action, chemical structures, and preclinical and clinical efficacies are discussed.


Assuntos
COVID-19 , Humanos , COVID-19/tratamento farmacológico , SARS-CoV-2 , Reposicionamento de Medicamentos , Terapia Combinada
6.
Life Sci Space Res (Amst) ; 35: 30-35, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36336366

RESUMO

The discovery of safe and effective radiation countermeasures (MCM) for long-duration spaceflight is challenging due to the complexity of the space radiation biology and high safety requirements. There are few if any clinically-validated molecular targets for this use case, and preclinical models have several known limitations. These challenges make the evaluation of existing FDA-approved drugs for this indication, or drug repurposing, an attractive strategy to accelerate space radiation countermeasure development. Drug repurposing offers several advantages over de novo drug discovery including established manufacturing methods, human clinical safety data, and well-understood dosing and pharmacokinetic considerations. There are limitations working with a fixed set of possible candidate compounds, but some properties of repurposed drugs can be tailored for well-defined new indications through reformulation and development of drug combinations. Drug repurposing is thus an attractive strategy for mitigating the high risks and costs of drug development and delivering new countermeasures to protect human from space radiation in long-term missions.


Assuntos
Reposicionamento de Medicamentos , Voo Espacial , Humanos , Reposicionamento de Medicamentos/métodos
7.
J Mol Model ; 28(11): 374, 2022 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-36323986

RESUMO

Paracoccidioidomycosis is a systemic mycosis endemic in Latin America, and one of the etiological agents of the disease is Paracoccidioides brasiliensis. Currently, available treatments present adversities, such as duration, side effects, and drug interactions. In search of new therapy possibilities, this study evaluates drugs approved for use against the homoserine dehydrogenase enzyme, by an in silico approach, which performs an important biosynthesis phase for the fungus and is not present in the human body. The three-dimensional structure of the homoserine dehydrogenase enzyme from Paracoccidioides brasiliensis was obtained by homology modeling. The model was validated, and simulations were performed for virtual screening of molecules of drugs approved from the Drugs-libs database by the MTiOpenScreen web server. Molecular dynamics in three replicas were used for four drugs with better results, and in two more molecules as a control, the HS9 with inhibition against enzyme and HON which shows inhibition against mold structure. Based on the results of molecular dynamics and the comparison of binding free energy, the drug that obtained the best result was Bemcentinib. In comparison with the controls, it presented a highly relevant affinity with - 44.63 kcal/mol, in addition to good structural stability and occupation of the active site. Therefore, Bemcentinib is a promising molecule for the inhibition of PbHSD protein (homoserine dehydrogenase of Paracoccidioides brasiliensis) and a therapeutic option to be investigated.


Assuntos
Paracoccidioides , Humanos , Paracoccidioides/metabolismo , Homosserina Desidrogenase , Reposicionamento de Medicamentos , Antifúngicos/farmacologia
8.
Front Immunol ; 13: 1020721, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36341423

RESUMO

Objective: Finding target genes and target pathways of existing drugs for drug repositioning in multiple sclerosis (MS) based on transcriptomic changes in MS immune cells. Materials and Methods: Based on transcriptome data from Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) in MS patients without treatment were identified by bioinformatics analysis according to the type of immune cells, as well as DEGs in MS patients before and after drug administration. Hub target genes of the drug for MS were analyzed by constructing the protein-protein interaction network, and candidate drugs targeting 2 or more hub target genes were obtained through the connectivity map (CMap) database and Drugbank database. Then, the enriched pathways of MS patients without treatment and the enriched pathways of MS patients before and after drug administration were intersected to obtain the target pathways of the drug for MS, and the candidate drugs targeting 2 or more target pathways were obtained through Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results: We obtained 50 hub target genes for CD4+ T cells in Fingolimod for MS, 15 hub target genes for Plasmacytoid dendritic cells (pDCs) and 7 hub target genes for Peripheral blood mononuclear cells (PBMC) in interferon-ß (IFN-ß) for MS. 6 candidate drugs targeting two or more hub targets (Fostamatinib, Copper, Artenimol, Phenethyl isothiocyanate, Aspirin and Zinc) were obtained. In addition, we obtained 4 target pathways for CD19+ B cells and 15 target pathways for CD4+ T cells in Fingolimod for MS, 7 target pathways for pDCs and 6 target pathways for PBMC in IFN-ß for MS, most of which belong to the immune system and viral infectious disease pathways. We obtained 69 candidate drugs targeting two target pathways. Conclusion: We found that applying candidate drugs that target both the "PI3K-Akt signaling pathway" and "Chemokine signaling pathway" (e.g., Nemiralisib and Umbralisib) or applying tyrosine kinase inhibitors (e.g., Fostamatinib) may be potential therapies for the treatment of MS.


Assuntos
Esclerose Múltipla , Transcriptoma , Humanos , Reposicionamento de Medicamentos , Leucócitos Mononucleares , Perfilação da Expressão Gênica , Esclerose Múltipla/tratamento farmacológico , Esclerose Múltipla/genética , Cloridrato de Fingolimode , Fosfatidilinositol 3-Quinases
9.
J Nutr Sci Vitaminol (Tokyo) ; 68(Supplement): S134-S136, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36436996

RESUMO

Repositioning is usually used to indicate drug repositioning, or the finding of new disease applications for existing, approved drugs. Nutrients can be ingested for nutritional as well as therapeutic purposes, acting much the same as drugs. Amino acids are organic compounds that possess both amino and carboxy group functionalities and are best known as building blocks of proteins in living organisms. Recent studies of individual amino acids have revealed them to be functional ingredients of new therapeutics, promoting health in addition to nutrition. Here, we propose "nutrient-repositioning", the discovery of effects different from the existing effects of nutrients. This review summarizes some recent discoveries of unexpected amino acid functions, especially in BCAAs, histidine and serine.


Assuntos
Aminoácidos , Reposicionamento de Medicamentos , Aminoácidos/química , Proteínas , Histidina , Aminas , Nutrientes
10.
Drug Deliv ; 29(1): 3414-3431, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36428290

RESUMO

Cutaneous fungal infection therapy confronts several issues concerning skin permeation in addition to drug resistance and adverse effects of conventional drugs. The repurposing strategy is supposed to overcome some of those therapeutic obstacles. Recently, atorvastatin (ATO) revealed antifungal activity. ATO is an antihyperlipidemic drug with pH-dependent solubility, which limits skin permeation. This study aims to improve ATO antifungal activity by encapsulation in an emulsomes (EMLs) system, which seeks to ameliorate skin penetration. Therefore, multiple factors were investigated according to the One-Factor-at-a-Time (OFAT) design to achieve the optimum formula with targeted characteristics. Minimizing particle-size and polydispersity-index, besides elevating zeta-potential (ZP) and entrapment-efficiency were the desirable responses during assessing 11 factors. The selected ATO-EMLs formula (E21) recorded 250.5 nm in particle size, polydispersity index of 0.4, ZP of -25.93 mV, and 83.12% of drug entrapped. Morphological study of E21 revealed spherical core-shell vesicles in nanosize. DSC, XRD, and FTIR were conducted to discover the physicochemical properties and confirm emulsomes formation. Optimized ATO-EMLs slowed drug release rate as only 75% of ATO was released after 72 h. Stability study recommended storage between 2 and 8 °C. The in vivo permeation study remarked a homogeneous penetration of EMLs in different skin layers. The in vivo skin irritation test revealed limited histopathological changes. The in vitro and in vivo microbiological studies demonstrated a good antifungal activity of ATO-EMLs. ATO-EMLs system improved antifungal activity as the MIC values reduced from 650 µg/mL for free ATO to 550 µg/mL for ATO-EMLs. These findings may shed light on ATO as an antifungal drug and nanosystems as a tool to support drug repurposing.


Assuntos
Antifúngicos , Reposicionamento de Medicamentos , Antifúngicos/química , Atorvastatina/farmacologia , Absorção Cutânea , Pele/metabolismo
11.
PLoS One ; 17(11): e0277328, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36383621

RESUMO

A therapy for COVID-19 (Coronavirus Disease 19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) remains elusive due to the lack of an effective antiviral therapeutic molecule. The SARS-CoV-2 main protease (Mpro), which plays a vital role in the viral life cycle, is one of the most studied and validated drug targets. In Several prior studies, numerous possible chemical entities were proposed as potential Mpro inhibitors; however, most failed at various stages of drug discovery. Repositioning of existing antiviral compounds accelerates the discovery and development of potent therapeutic molecules. Hence, this study examines the applicability of anti-dengue compounds against the substrate binding site of Mpro for disrupting its polyprotein processing mechanism. An in-silico structure-based virtual screening approach is applied to screen 330 experimentally validated anti-dengue compounds to determine their affinity to the substrate binding site of Mpro. This study identified the top five compounds (CHEMBL1940602, CHEMBL2036486, CHEMBL3628485, CHEMBL200972, CHEMBL2036488) that showed a high affinity to Mpro with a docking score > -10.0 kcal/mol. The best-docked pose of these compounds with Mpro was subjected to 100 ns molecular dynamic (MD) simulation followed by MM/GBSA binding energy. This showed the maximum stability and comparable ΔG binding energy against the reference compound (X77 inhibitor). Overall, we repurposed the reported anti-dengue compounds against SARS-CoV-2-Mpro to impede its polyprotein processing for inhibiting SARS-CoV-2 infection.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , COVID-19/tratamento farmacológico , Reposicionamento de Medicamentos , Poliproteínas , Proteínas não Estruturais Virais/metabolismo , Cisteína Endopeptidases/metabolismo , Inibidores de Proteases/química , Antivirais/farmacologia , Antivirais/química , Simulação de Dinâmica Molecular , Peptídeo Hidrolases/metabolismo , Simulação de Acoplamento Molecular
12.
Int J Mol Sci ; 23(21)2022 Oct 26.
Artigo em Inglês | MEDLINE | ID: mdl-36361765

RESUMO

Noise is a basic ingredient in data, since observed data are always contaminated by unwanted deviations, i.e., noise, which, in the case of overdetermined systems (with more data than model parameters), cause the corresponding linear system of equations to have an imperfect solution. In addition, in the case of highly underdetermined parameterization, noise can be absorbed by the model, generating spurious solutions. This is a very undesirable situation that might lead to incorrect conclusions. We presented mathematical formalism based on the inverse problem theory combined with artificial intelligence methodologies to perform an enhanced sampling of noisy biomedical data to improve the finding of meaningful solutions. Random sampling methods fail for high-dimensional biomedical problems. Sampling methods such as smart model parameterizations, forward surrogates, and parallel computing are better suited for such problems. We applied these methods to several important biomedical problems, such as phenotype prediction and a problem related to predicting the effects of protein mutations, i.e., if a given single residue mutation is neutral or deleterious, causing a disease. We also applied these methods to de novo drug discovery and drug repositioning (repurposing) through the enhanced exploration of huge chemical space. The purpose of these novel methods that address the problem of noise and uncertainty in biomedical data is to find new therapeutic solutions, perform drug repurposing, and accelerate and optimize drug discovery, thus reestablishing homeostasis. Finding the right target, the right compound, and the right patient are the three bottlenecks to running successful clinical trials from the correct analysis of preclinical models. Artificial intelligence can provide a solution to these problems, considering that the character of the data restricts the quality of the prediction, as in any modeling procedure in data analysis. The use of simple and plain methodologies is crucial to tackling these important and challenging problems, particularly drug repositioning/repurposing in rare diseases.


Assuntos
Inteligência Artificial , Reposicionamento de Medicamentos , Incerteza , Reposicionamento de Medicamentos/métodos , Descoberta de Drogas/métodos , Fenótipo
13.
Int J Mol Sci ; 23(21)2022 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-36362045

RESUMO

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces immune-mediated type 1 interferon (IFN-1) production, the pathophysiology of which involves sterile alpha motif and histidine-aspartate domain-containing protein 1 (SAMHD1) tetramerization and the cytosolic DNA sensor cyclic-GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. As a result, type I interferonopathies are exacerbated. Aspirin inhibits cGAS-mediated signaling through cGAS acetylation. Acetylation contributes to cGAS activity control and activates IFN-1 production and nuclear factor-κB (NF-κB) signaling via STING. Aspirin and dapsone inhibit the activation of both IFN-1 and NF-κB by targeting cGAS. We define these as anticatalytic mechanisms. It is necessary to alleviate the pathologic course and take the lag time of the odds of achieving viral clearance by day 7 to coordinate innate or adaptive immune cell reactions.


Assuntos
COVID-19 , Interferon Tipo I , Humanos , COVID-19/tratamento farmacológico , Acetilação , NF-kappa B/metabolismo , Reposicionamento de Medicamentos , Proteínas de Membrana/metabolismo , SARS-CoV-2 , Nucleotidiltransferases/metabolismo , Interferon Tipo I/metabolismo , Aspirina , Imunidade Inata/genética
14.
Drug Saf ; 45(12): 1517-1527, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36318419

RESUMO

INTRODUCTION: The US FDA required a Risk Evaluation and Mitigation Strategy (REMS) for phentermine/topiramate, an anti-obesity medication, to prevent congenital malformations. No REMS is required for single-ingredient topiramate, which may be used off-label for the same purpose. OBJECTIVE: The aim of this study was to evaluate the impact of phentermine/topiramate approval in 2012 on subsequent topiramate use among patients with obesity. METHODS: We used a national insurance claims database to conduct an interrupted time-series study (2009-2015). Enrollees aged 18-65 years in each examined calendar quarter had full insurance benefits during that quarter and the preceding 6 months. We required patients to have an obesity diagnosis and no other conditions warranting topiramate use. We calculated topiramate or comparator drug (atorvastatin, metformin) initiation rates and evaluated changes in trends before and after 2012 (transition period). RESULTS: Among topiramate users, 80% were female, and demographic characteristics remained consistent during the study period. Between 2009 and 2011, the topiramate initiation rate (95% confidence interval) among patients with obesity was 0.85 (0.73-0.98) per 1000 patients, with no significant upward or downward trend. In the first quarter of 2013, this rate had increased more than 2.5-fold (change: + 1.36 [1.19-1.52]). Metformin and atorvastatin initiation rates did not change. Topiramate initiation rates were threefold higher than phentermine/topiramate rates during the post-approval period. CONCLUSION: Phentermine/topiramate approval was associated with increased topiramate use among patients with obesity. Prescribers are encouraged to enhance patient education and monitoring in such clinical use since topiramate prescribing information, compared with REMS for phentermine/topiramate, has less emphasis on preventing prenatal exposure.


Assuntos
Fármacos Antiobesidade , Metformina , Gravidez , Humanos , Feminino , Masculino , Fentermina/efeitos adversos , Topiramato/uso terapêutico , Reposicionamento de Medicamentos , Atorvastatina , Frutose/efeitos adversos , Fármacos Antiobesidade/efeitos adversos , Obesidade/tratamento farmacológico , Obesidade/epidemiologia , Metformina/uso terapêutico , Aprovação de Drogas
15.
Int J Mol Sci ; 23(22)2022 Nov 18.
Artigo em Inglês | MEDLINE | ID: mdl-36430762

RESUMO

Monkeypox is caused by a DNA virus known as the monkeypox virus (MPXV) belonging to the Orthopoxvirus genus of the Poxviridae family. Monkeypox is a zoonotic disease where the primary significant hosts are rodents and non-human primates. There is an increasing global incidence with a 2022 outbreak that has spread to Europe in the middle of the COVID-19 pandemic. The new outbreak has novel, previously undiscovered mutations and variants. Currently, the US Food and Drug Administration (FDA) approved poxvirus treatment involving the use of tecovirimat. However, there has otherwise been limited research interest in monkeypox. Mitoxantrone (MXN), an anthracycline derivative, an FDA-approved therapeutic for treating cancer and multiple sclerosis, was previously reported to exhibit antiviral activity against the vaccinia virus and monkeypox virus. In this study, virtual screening, molecular docking analysis, and pharmacophore ligand-based modelling were employed on anthracene structures (1-13) closely related to MXN to explore the potential repurposing of multiple compounds from the PubChem library. Four chemical structures (2), (7), (10) and (12) show a predicted high binding potential to suppress viral replication.


Assuntos
COVID-19 , Varíola dos Macacos , Animais , Humanos , Vírus da Varíola dos Macacos , Varíola dos Macacos/diagnóstico , Varíola dos Macacos/tratamento farmacológico , Simulação de Acoplamento Molecular , Mitoxantrona/farmacologia , Reposicionamento de Medicamentos , Pandemias , Receptores de Droga , Primatas , Roedores
16.
Molecules ; 27(22)2022 Nov 10.
Artigo em Inglês | MEDLINE | ID: mdl-36431833

RESUMO

The severe acute respiratory syndrome coronavirus 2, also known as SARS-CoV-2, is the causative agent of the COVID-19 global pandemic. SARS-CoV-2 has a highly conserved non-structural protein 12 (NSP-12) involved in RNA-dependent RNA polymerase (RdRp) activity. For the identification of potential inhibitors for NSP-12, computational approaches such as the identification of homologous proteins that have been previously targeted by FDA-approved antivirals can be employed. Herein, homologous proteins of NSP-12 were retrieved from Protein DataBank (PDB) and the evolutionary conserved sequence and structure similarity of the active site of the RdRp domain of NSP-12 was characterized. The identified homologous structures of NSP-12 belonged to four viral families: Coronaviridae, Flaviviridae, Picornaviridae, and Caliciviridae, and shared evolutionary conserved relationships. The multiple sequences and structural alignment of homologous structures showed highly conserved amino acid residues that were located at the active site of the RdRp domain of NSP-12. The conserved active site of the RdRp domain of NSP-12 was evaluated for binding affinity with the FDA-approved antivirals, i.e., Sofosbuvir and Dasabuvir in a molecular docking study. The molecular docking of Sofosbuvir and Dasabuvir with the active site that contains conserved motifs (motif A-G) of the RdRp domain of NSP-12 revealed significant binding affinity. Furthermore, MD simulation also inferred the potency of Sofosbuvir and Dasabuvir. In conclusion, targeting the active site of the RdRp domain of NSP-12 with Dasabuvir and Sofosbuvir might reduce viral replication and pathogenicity and could be further studied for the treatment of SARS-CoV-2.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , Reposicionamento de Medicamentos , Sofosbuvir , Simulação de Acoplamento Molecular , COVID-19/tratamento farmacológico , RNA Polimerase Dependente de RNA/genética , Antivirais/farmacologia , Antivirais/uso terapêutico
17.
BMC Bioinformatics ; 23(1): 459, 2022 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-36329406

RESUMO

BACKGROUND: Drug-target interactions (DTIs) prediction becomes more and more important for accelerating drug research and drug repositioning. Drug-target interaction network is a typical model for DTIs prediction. As many different types of relationships exist between drug and target, drug-target interaction network can be used for modeling drug-target interaction relationship. Recent works on drug-target interaction network are mostly concentrate on drug node or target node and neglecting the relationships between drug-target. RESULTS: We propose a novel prediction method for modeling the relationship between drug and target independently. Firstly, we use different level relationships of drugs and targets to construct feature of drug-target interaction. Then, we use line graph to model drug-target interaction. After that, we introduce graph transformer network to predict drug-target interaction. CONCLUSIONS: This method introduces a line graph to model the relationship between drug and target. After transforming drug-target interactions from links to nodes, a graph transformer network is used to accomplish the task of predicting drug-target interactions.


Assuntos
Algoritmos , Desenvolvimento de Medicamentos , Reposicionamento de Medicamentos , Interações Medicamentosas
18.
Pharm Dev Technol ; 27(9): 975-988, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36330998

RESUMO

This work investigates the synergistic potential of the nanostructured lipid carrier (NLC) gel of Ibrutinib with Curcumin as a repurposing strategy to treat psoriasis. In the present work, various components such as liquid lipid, solid lipid, and surfactant were selected and optimized based on the solubility of each drug, size, and polydispersity index. The optimized NLC consists of Capryol PGMC as liquid lipid, Glyceryl Mono Stearate as solid lipid, and Pluronics-F-127 as a surfactant. The prepared NLCs have a particle size of 95.12 ± 3.39 nm with PDI of 0.285 ± 0.009, exhibiting high entrapment efficiency (86.04 ± 2.86% for IBR and 87.25 ± 2.14% for CUR) with spherical geometry. CI value of 0.283 suggests synergism. Carbopol 940 was used as a gelling agent and has shown improved flux compared to plain drug gel. Anti-psoriatic studies in BALB/c mice indicated negligible skin irritation and improved histopathological features of psoriasis. Moreover, a reduced amount of inflammatory markers (TNF-alpha, IL-6, IL-22, and IL-23), and psoriasis severity score was observed with prepared gel than the IMQ group. The study suggested integrated benefits of repurposing Ibrutinib with Curcumin as NLC topical gel and it could possibly reduce remission of Psoriasis like inflammation and merit additional investigation.


Assuntos
Curcumina , Nanoestruturas , Psoríase , Camundongos , Animais , Portadores de Fármacos , Reposicionamento de Medicamentos , Psoríase/tratamento farmacológico , Psoríase/patologia , Camundongos Endogâmicos BALB C , Tamanho da Partícula , Géis , Excipientes , Lipídeos , Tensoativos , Inibidores de Proteínas Quinases
19.
Biomolecules ; 12(11)2022 10 26.
Artigo em Inglês | MEDLINE | ID: mdl-36358909

RESUMO

We present the Pharmacorank search tool as an objective means to obtain prioritized protein drug targets and their associated medications according to user-selected diseases. This tool could be used to obtain prioritized protein targets for the creation of novel medications or to predict novel indications for medications that already exist. To prioritize the proteins associated with each disease, a gene similarity profiling method based on protein functions is implemented. The priority scores of the proteins are found to correlate well with the likelihoods that the associated medications are clinically relevant in the disease's treatment. When the protein priority scores are plotted against the percentage of protein targets that are known to bind medications currently indicated to treat the disease, which we termed the pertinency score, a strong correlation was observed. The correlation coefficient was found to be 0.9978 when using a weighted second-order polynomial fit. As the highly predictive fit was made using a broad range of diseases, we were able to identify a general threshold for the pertinency score as a starting point for considering drug repositioning candidates. Several repositioning candidates are described for proteins that have high predicated pertinency scores, and these provide illustrative examples of the applications of the tool. We also describe focused reviews of repositioning candidates for Alzheimer's disease. Via the tool's URL, https://protein.som.geisinger.edu/Pharmacorank/, an open online interface is provided for interactive use; and there is a site for programmatic access.


Assuntos
Doença de Alzheimer , Reposicionamento de Medicamentos , Humanos , Reposicionamento de Medicamentos/métodos , Proteínas , Algoritmos , Doença de Alzheimer/tratamento farmacológico , Doença de Alzheimer/metabolismo , Biologia Computacional/métodos
20.
Biomolecules ; 12(11)2022 11 10.
Artigo em Inglês | MEDLINE | ID: mdl-36359016

RESUMO

Drug repositioning, an important method of drug development, is utilized to discover investigational drugs beyond the originally approved indications, expand the application scope of drugs, and reduce the cost of drug development. With the emergence of increasingly drug-disease-related biological networks, the challenge still remains to effectively fuse biological entity data and accurately achieve drug-disease repositioning. This paper proposes a new drug repositioning method named EMPHCN based on enhanced message passing and hypergraph convolutional networks (HGCN). It firstly constructs the homogeneous multi-view information with multiple drug similarity features and then extracts the intra-domain embedding of drugs through the combination of HGCN and channel attention mechanism. Secondly, inter-domain information of known drug-disease associations is extracted by graph convolutional networks combining node and edge embedding (NEEGCN), and a heterogeneous network composed of drugs, proteins and diseases is built as an important auxiliary to enhance the inter-domain message passing of drugs and diseases. Besides, the intra-domain embedding of diseases is also extracted through HGCN. Ultimately, intra-domain and inter-domain embeddings of drugs and diseases are integrated as the final embedding for calculating the drug-disease correlation matrix. Through 10-fold cross-validation on some benchmark datasets, we find that the AUPR of EMPHCN reaches 0.593 (T1) and 0.526 (T2), respectively, and the AUC achieves 0.887 (T1) and 0.961 (T2) respectively, which shows that EMPHCN has an advantage over other state-of-the-art prediction methods. Concerning the new disease association prediction, the AUC of EMPHCN through the five-fold cross-validation reaches 0.806 (T1) and 0.845 (T2), which are 4.3% (T1) and 4.0% (T2) higher than the second best existing methods, respectively. In the case study, EMPHCN also achieves satisfactory results in real drug repositioning for breast carcinoma and Parkinson's disease.


Assuntos
Algoritmos , Reposicionamento de Medicamentos , Reposicionamento de Medicamentos/métodos
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