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1.
BMC Biol ; 19(1): 156, 2021 08 02.
Artigo em Inglês | MEDLINE | ID: mdl-34334126

RESUMO

BACKGROUND: The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections. RESULTS: We combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. CONCLUSIONS: The phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery.


Assuntos
Antivirais/farmacologia , Descoberta de Drogas/métodos , Fenômica/métodos , SARS-CoV-2/efeitos dos fármacos , Linhagem Celular , Relação Dose-Resposta a Droga , Avaliação Pré-Clínica de Medicamentos/métodos , Humanos , SARS-CoV-2/fisiologia
2.
Elife ; 102021 08 03.
Artigo em Inglês | MEDLINE | ID: mdl-34340747

RESUMO

The discovery of a drug requires over a decade of intensive research and financial investments - and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch resource, which incorporates 250,000 bioactive molecules, and studied their enzymatic metabolic targets, fate, and toxicity. NICEdrug.ch includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs. We validated the application, scope, and performance of NICEdrug.ch over similar methods in the field on golden standard datasets describing drugs and metabolites sharing reactivity, drug toxicities, and drug targets. We use NICEdrug.ch to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, NICEdrug.ch suggests over 1300 candidate drugs and food molecules to target COVID-19 and explains their inhibitory mechanism for further experimental screening. The NICEdrug.ch database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.


Assuntos
Desenho de Fármacos , Descoberta de Drogas/métodos , Reposicionamento de Medicamentos , Preparações Farmacêuticas/metabolismo , Animais , Antimetabólitos Antineoplásicos/química , Antimetabólitos Antineoplásicos/metabolismo , Antivirais/química , Antivirais/farmacologia , COVID-19/tratamento farmacológico , Bases de Dados de Produtos Farmacêuticos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/etiologia , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/metabolismo , Fluoruracila/química , Fluoruracila/metabolismo , Humanos , Preparações Farmacêuticas/química , Fluxo de Trabalho
3.
Sci Rep ; 11(1): 16174, 2021 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-34376712

RESUMO

Oncostatin M (OSM) is a pleiotropic, interleukin-6 family inflammatory cytokine that plays an important role in inflammatory diseases, including inflammatory bowel disease, rheumatoid arthritis, and cancer progression and metastasis. Recently, elevated OSM levels have been found in the serum of COVID-19 patients in intensive care units. Multiple anti-OSM therapeutics have been investigated, but to date no OSM small molecule inhibitors are clinically available. To pursue a high-throughput screening and structure-based drug discovery strategy to design a small molecule inhibitor of OSM, milligram quantities of highly pure, bioactive OSM are required. Here, we developed a reliable protocol to produce highly pure unlabeled and isotope enriched OSM from E. coli for biochemical and NMR studies. High yields (ca. 10 mg/L culture) were obtained in rich and minimal defined media cultures. Purified OSM was characterized by mass spectrometry and circular dichroism. The bioactivity was confirmed by induction of OSM/OSM receptor signaling through STAT3 phosphorylation in human breast cancer cells. Optimized buffer conditions yielded 1H, 15N HSQC NMR spectra with intense, well-dispersed peaks. Titration of 15N OSM with a small molecule inhibitor showed chemical shift perturbations for several key residues with a binding affinity of 12.2 ± 3.9 µM. These results demonstrate the value of bioactive recombinant human OSM for NMR-based small molecule screening.


Assuntos
Descoberta de Drogas/métodos , Oncostatina M/antagonistas & inibidores , Bibliotecas de Moléculas Pequenas/farmacologia , Sítios de Ligação , Linhagem Celular Tumoral , Humanos , Espectroscopia de Ressonância Magnética/métodos , Simulação de Acoplamento Molecular , Oncostatina M/química , Oncostatina M/metabolismo , Fosforilação , Ligação Proteica , Fator de Transcrição STAT3/metabolismo , Bibliotecas de Moléculas Pequenas/química
4.
Int J Mol Sci ; 22(15)2021 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-34360991

RESUMO

The possibility to reproduce key tissue functions in vitro from induced pluripotent stem cells (iPSCs) is offering an incredible opportunity to gain better insight into biological mechanisms underlying development and disease, and a tool for the rapid screening of drug candidates. This review attempts to summarize recent strategies for specification of iPSCs towards hepatobiliary lineages -hepatocytes and cholangiocytes-and their use as platforms for disease modeling and drug testing. The application of different tissue-engineering methods to promote accurate and reliable readouts is discussed. Space is given to open questions, including to what extent these novel systems can be informative. Potential pathways for improvement are finally suggested.


Assuntos
Técnicas de Reprogramação Celular/métodos , Doenças do Sistema Digestório/terapia , Descoberta de Drogas/métodos , Hepatócitos/citologia , Células-Tronco Pluripotentes Induzidas/citologia , Medicina de Precisão/métodos , Animais , Linhagem da Célula , Doenças do Sistema Digestório/metabolismo , Doenças do Sistema Digestório/patologia , Hepatócitos/metabolismo , Humanos , Engenharia Tecidual/métodos
5.
Molecules ; 26(15)2021 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-34361624

RESUMO

Prediction of molecular properties plays a critical role towards rational drug design. In this study, the Molecular Topographic Map (MTM) is proposed, which is a two-dimensional (2D) map that can be used to represent a molecule. An MTM is generated from the atomic features set of a molecule using generative topographic mapping and is then used as input data for analyzing structure-property/activity relationships. In the visualization and classification of 20 amino acids, differences of the amino acids can be visually confirmed from and revealed by hierarchical clustering with a similarity matrix of their MTMs. The prediction of molecular properties was performed on the basis of convolutional neural networks using MTMs as input data. The performance of the predictive models using MTM was found to be equal to or better than that using Morgan fingerprint or MACCS keys. Furthermore, data augmentation of MTMs using mixup has improved the prediction performance. Since molecules converted to MTMs can be treated like 2D images, they can be easily used with existing neural networks for image recognition and related technologies. MTM can be effectively utilized to predict molecular properties of small molecules to aid drug discovery research.


Assuntos
Desenho de Fármacos , Descoberta de Drogas/métodos , Algoritmos , Conformação Molecular , Redes Neurais de Computação , Relação Estrutura-Atividade
6.
Proc Natl Acad Sci U S A ; 118(36)2021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34426525

RESUMO

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration-approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (Mpro) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [K i] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of Mpro (K i = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (K i = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets.


Assuntos
Proteases 3C de Coronavírus/antagonistas & inibidores , Proteases 3C de Coronavírus/genética , Descoberta de Drogas/métodos , Inibidores de Proteases/química , Inibidores de Proteases/farmacologia , SARS-CoV-2/efeitos dos fármacos , SARS-CoV-2/genética , Animais , COVID-19/tratamento farmacológico , COVID-19/virologia , Células Cultivadas , Proteases 3C de Coronavírus/metabolismo , Relação Dose-Resposta a Droga , Ativação Enzimática , Engenharia Genética , Humanos , Modelos Moleculares , Conformação Molecular , Estrutura Molecular , SARS-CoV-2/metabolismo , Relação Estrutura-Atividade , Replicação Viral
7.
Int J Mol Sci ; 22(15)2021 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-34360966

RESUMO

Neurodegenerative diseases affect millions of people worldwide and are characterized by the chronic and progressive deterioration of neural function. Neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD), represent a huge social and economic burden due to increasing prevalence in our aging society, severity of symptoms, and lack of effective disease-modifying therapies. This lack of effective treatments is partly due to a lack of reliable models. Modeling neurodegenerative diseases is difficult because of poor access to human samples (restricted in general to postmortem tissue) and limited knowledge of disease mechanisms in a human context. Animal models play an instrumental role in understanding these diseases but fail to comprehensively represent the full extent of disease due to critical differences between humans and other mammals. The advent of human-induced pluripotent stem cell (hiPSC) technology presents an advantageous system that complements animal models of neurodegenerative diseases. Coupled with advances in gene-editing technologies, hiPSC-derived neural cells from patients and healthy donors now allow disease modeling using human samples that can be used for drug discovery.


Assuntos
Doença de Alzheimer/tratamento farmacológico , Descoberta de Drogas/métodos , Células-Tronco Pluripotentes Induzidas/efeitos dos fármacos , Humanos , Células-Tronco Pluripotentes Induzidas/citologia , Células-Tronco Pluripotentes Induzidas/metabolismo , Fármacos Neuroprotetores/farmacologia , Fármacos Neuroprotetores/uso terapêutico , Medicina de Precisão/métodos
8.
Int J Mol Sci ; 22(16)2021 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-34445321

RESUMO

Listeria monocytogenes is an important food-borne pathogen and a serious concern to food industries. Bacteriocins are antimicrobial peptides produced naturally by a wide range of bacteria mostly belonging to the group of lactic acid bacteria (LAB), which also comprises many strains used as starter cultures or probiotic supplements. Consequently, multifunctional strains that produce bacteriocins are an attractive approach to combine a green-label approach for food preservation with an important probiotic trait. Here, a collection of bacterial isolates from raw cow's milk was typed by 16S rRNA gene sequencing and MALDI-Biotyping and supernatants were screened for the production of antimicrobial compounds. Screening was performed with live Listeria monocytogenes biosensors using a growth-dependent assay and pHluorin, a pH-dependent protein reporting membrane damage. Purification by cation exchange chromatography and further investigation of the active compounds in supernatants of two isolates belonging to the species Pediococcus acidilactici and Lactococcus garvieae suggest that their antimicrobial activity is related to heat-stable proteins/peptides that presumably belong to the class IIa bacteriocins. In conclusion, we present a pipeline of methods for high-throughput screening of strain libraries for potential starter cultures and probiotics producing antimicrobial compounds and their identification and analysis.


Assuntos
Antibacterianos/farmacologia , Bacteriocinas/farmacologia , Descoberta de Drogas/métodos , Listeria monocytogenes/efeitos dos fármacos , Probióticos , Animais , Antibacterianos/biossíntese , Bacteriocinas/biossíntese , Lactococcus/isolamento & purificação , Lactococcus/metabolismo , Microbiota , Leite/microbiologia , Pediococcus acidilactici/isolamento & purificação , Pediococcus acidilactici/metabolismo
9.
Int J Mol Sci ; 22(16)2021 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-34445667

RESUMO

Spinal muscular atrophy (SMA), one of the leading inherited causes of child mortality, is a rare neuromuscular disease arising from loss-of-function mutations of the survival motor neuron 1 (SMN1) gene, which encodes the SMN protein. When lacking the SMN protein in neurons, patients suffer from muscle weakness and atrophy, and in the severe cases, respiratory failure and death. Several therapeutic approaches show promise with human testing and three medications have been approved by the U.S. Food and Drug Administration (FDA) to date. Despite the shown promise of these approved therapies, there are some crucial limitations, one of the most important being the cost. The FDA-approved drugs are high-priced and are shortlisted among the most expensive treatments in the world. The price is still far beyond affordable and may serve as a burden for patients. The blooming of the biomedical data and advancement of computational approaches have opened new possibilities for SMA therapeutic development. This article highlights the present status of computationally aided approaches, including in silico drug repurposing, network driven drug discovery as well as artificial intelligence (AI)-assisted drug discovery, and discusses the future prospects.


Assuntos
Atrofia Muscular Espinal/tratamento farmacológico , Atrofia Muscular Espinal/metabolismo , Atrofia Muscular Espinal/fisiopatologia , Animais , Biologia Computacional/métodos , Biologia Computacional/tendências , Modelos Animais de Doenças , Descoberta de Drogas/métodos , Descoberta de Drogas/tendências , Reposicionamento de Medicamentos/métodos , Reposicionamento de Medicamentos/tendências , Humanos , Neurônios Motores/metabolismo , Proteína 1 de Sobrevivência do Neurônio Motor/metabolismo
10.
Int J Mol Sci ; 22(16)2021 Aug 23.
Artigo em Inglês | MEDLINE | ID: mdl-34445773

RESUMO

Inadequate vessel maintenance or growth causes ischemia in diseases such as myocardial infarction, stroke, and neurodegenerative disorders. Therefore, developing an effective strategy to salvage ischemic tissues using a novel compound is urgent. Drug repurposing has become a widely used method that can make drug discovery more efficient and less expensive. Additionally, computational virtual screening tools make drug discovery faster and more accurate. This study found a novel drug candidate for pro-angiogenesis by in silico virtual screening. Using Gene Expression Omnibus (GEO) microarray datasets related to angiogenesis studies, differentially expressed genes were identified and characteristic direction signatures extracted from GEO2EnrichR were used as input data on L1000CDS2 to screen pro-angiogenic molecules. After a thorough review of the candidates, a list of compounds structurally similar to TWS-119 was generated using ChemMine Tools and its clustering toolbox. ChemMine Tools and ChemminR structural similarity search tools for small-molecule analysis and clustering were used for second screening. A molecular docking simulation was conducted using AutoDock v.4 to evaluate the physicochemical effect of secondary-screened chemicals. A cell viability or toxicity test was performed to determine the proper dose of the final candidate, ellipticine. As a result, we found ellipticine, which has pro-angiogenic effects, using virtual computational methods. The noncytotoxic concentration of ellipticine was 156.25 nM. The phosphorylation of glycogen synthase kinase-3ß was decreased, whereas the ß-catenin expression was increased in human endothelial cells treated with ellipticine. We concluded that ellipticine at sublethal dosage could be successfully repositioned as a pro-angiogenic substance by in silico virtual screening.


Assuntos
Elipticinas/farmacologia , Células Endoteliais da Veia Umbilical Humana/efeitos dos fármacos , Neovascularização Patológica/tratamento farmacológico , Sobrevivência Celular/efeitos dos fármacos , Células Cultivadas , Descoberta de Drogas/métodos , Reposicionamento de Medicamentos/métodos , Expressão Gênica/efeitos dos fármacos , Glicogênio Sintase Quinase 3 beta/metabolismo , Células Endoteliais da Veia Umbilical Humana/metabolismo , Humanos , Simulação de Acoplamento Molecular/métodos , Simulação de Dinâmica Molecular , Neovascularização Patológica/metabolismo , Ligação Proteica/efeitos dos fármacos , beta Catenina/metabolismo
11.
Int J Mol Sci ; 22(16)2021 Aug 11.
Artigo em Inglês | MEDLINE | ID: mdl-34445332

RESUMO

More than 85% of pre-clinically tested drugs fail during clinical trials, which results in a long, inefficient and costly process, suggesting that animal models are often poor predictors of human biology [...].


Assuntos
Descoberta de Drogas/métodos , Células-Tronco Pluripotentes Induzidas/fisiologia , Animais , Técnicas de Cultura de Células , Diferenciação Celular , Células Cultivadas , Descoberta de Drogas/tendências , Avaliação Pré-Clínica de Medicamentos/métodos , Humanos , Células-Tronco Pluripotentes Induzidas/citologia , Modelos Biológicos
12.
Molecules ; 26(15)2021 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-34361800

RESUMO

Thin-layer chromatography (TLC) bioautography is an evolving technology that integrates the separation and analysis technology of TLC with biological activity detection technology, which has shown a steep rise in popularity over the past few decades. It connects TLC with convenient, economic and intuitive features and bioautography with high levels of sensitivity and specificity. In this study, we discuss the research progress of TLC bioautography and then establish a definite timeline to introduce it. This review summarizes known TLC bioautography types and practical applications for determining antibacterial, antifungal, antitumor and antioxidant compounds and for inhibiting glucosidase, pancreatic lipase, tyrosinase and cholinesterase activity constitutes. Nowadays, especially during the COVID-19 pandemic, it is important to identify original, natural products with anti-COVID potential compounds from Chinese traditional medicine and natural medicinal plants. We also give an account of detection techniques, including in situ and ex situ techniques; even in situ ion sources represent a major reform. Considering the current technical innovations, we propose that the technology will make more progress in TLC plates with higher separation and detection technology with a more portable and extensive scope of application. We believe this technology will be diffusely applied in medicine, biology, agriculture, animal husbandry, garden forestry, environmental management and other fields in the future.


Assuntos
Cromatografia em Camada Delgada/métodos , Descoberta de Drogas/métodos , Medições Luminescentes/métodos , Animais , Anti-Infecciosos/isolamento & purificação , Antineoplásicos/isolamento & purificação , Antioxidantes/isolamento & purificação , Inibidores Enzimáticos/isolamento & purificação , Humanos , Testes de Sensibilidade Microbiana/métodos , Extratos Vegetais/química , Extratos Vegetais/farmacologia , Plantas Medicinais/química , Sensibilidade e Especificidade
13.
Lancet Oncol ; 22(8): e358-e368, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34339656

RESUMO

Epithelial-mesenchymal transition (EMT) is a process during which cells lose their epithelial characteristics, for instance apical-basal cell polarity and cell-cell contact, and gain mesenchymal properties, such as increased motility. In colorectal cancer, EMT has an important role in tumour progression, metastasis, and drug resistance. There has been accumulating evidence from preclinical and early clinical studies that show that EMT markers might serve as outcome predictors and potential therapeutic targets in colorectal cancer. This Review describes the fundamentals of EMT, including biology, newly partial EMT, and associated changes. We also provide a comprehensive summary of therapeutic compounds capable of targeting EMT markers, including drugs in preclinical and clinical trials and those with repurpose potential. Lastly, we explore the obstacles of EMT bench-to-bedside drug development.


Assuntos
Antineoplásicos/farmacologia , Neoplasias Colorretais/tratamento farmacológico , Neoplasias Colorretais/patologia , Transição Epitelial-Mesenquimal/efeitos dos fármacos , Transição Epitelial-Mesenquimal/fisiologia , Animais , Descoberta de Drogas/métodos , Humanos
14.
Int J Mol Sci ; 22(16)2021 Aug 22.
Artigo em Inglês | MEDLINE | ID: mdl-34445763

RESUMO

Unfortunately, COVID-19 is still a threat to humankind and has a dramatic impact on human health, social life, the world economy, and food security. With the limited number of suggested therapies under clinical trials, the discovery of novel therapeutic agents is essential. Here, a previously identified anti-SARS-CoV-2 compound named Compound 13 (1,2,5-Oxadiazole-3-carboximidic acid, 4,4'-(methylenediimino) bis,bis[[(2-hydroxyphenyl)methylene]hydrazide) was subjected to an iterated virtual screening against SARS-CoV-2 Mpro using a combination of Ligand Designer and PathFinder. PathFinder, a computational reaction enumeration tool, was used for the rapid generation of enumerated structures via default reaction library. Ligand designer was employed for the computerized lead optimization and selection of the best structural modification that resulted in a favorable ligand-protein complex. The obtained compounds that showed the best binding to Mpro were re-screened against TMPRSS2, leading to the identification of 20 shared compounds. The compounds were further visually inspected, which resulted in the identification of five shared compounds M1-5 with dual binding affinity. In vitro evaluation and enzyme inhibition assay indicated that M3, an analogue of Compound 13 afforded by replacing the phenolic moiety with pyridinyl, possesses an improved antiviral activity and safety. M3 displayed in vitro antiviral activity with IC50 0.016 µM and Mpro inhibition activity with IC50 0.013 µM, 7-fold more potent than the parent Compound 13 and potent than the antivirals drugs that are currently under clinical trials. Moreover, M3 showed potent activity against human TMPRSS2 and furin enzymes with IC50 0.05, and 0.08 µM, respectively. Molecular docking, WaterMap analysis, molecular dynamics simulation, and R-group analysis confirmed the superiority of the binding fit to M3 with the target enzymes. WaterMap analysis calculated the thermodynamic properties of the hydration site in the binding pocket that significantly affects the biological activity. Loading M3 on zinc oxide nanoparticles (ZnO NPs) increased the antiviral activity of the compound 1.5-fold, while maintaining a higher safety profile. In conclusion, lead optimized discovery following an iterated virtual screening in association with molecular docking and biological evaluation revealed a novel compound named M3 with promising dual activity against SARS-CoV-2. The compound deserves further investigation for potential clinical-based studies.


Assuntos
Antivirais/farmacologia , COVID-19/tratamento farmacológico , Proteases 3C de Coronavírus/antagonistas & inibidores , Descoberta de Drogas/métodos , Inibidores de Proteases/farmacologia , Antivirais/uso terapêutico , COVID-19/virologia , Proteases 3C de Coronavírus/metabolismo , Ensaios Enzimáticos , Humanos , Concentração Inibidora 50 , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Inibidores de Proteases/uso terapêutico , SARS-CoV-2/efeitos dos fármacos , SARS-CoV-2/enzimologia , Serina Endopeptidases/metabolismo
15.
J Healthc Eng ; 2021: 6668985, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34326978

RESUMO

Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhance and speed up the process of medical research and development of vaccines, which is required for pandemics such as COVID-19. However, current drugs such as remdesivir and clinical trials of other chemical compounds have not shown many impressive results. Therefore, it can take more time to provide effective treatment or drugs. In this paper, a deep learning approach based on logistic regression, SVM, Random Forest, and QSAR modeling is suggested. QSAR modeling is done to find the drug targets with protein interaction along with the calculation of binding affinities. Then deep learning models were used for training the molecular descriptor dataset for the robust discovery of drugs and feature extraction for combating COVID-19. Results have shown more significant binding affinities (greater than -18) for many molecules that can be used to block the multiplication of SARS-CoV-2, responsible for COVID-19.


Assuntos
COVID-19/tratamento farmacológico , Simulação por Computador , Descoberta de Drogas/métodos , SARS-CoV-2/efeitos dos fármacos , Algoritmos , Aprendizado Profundo , Humanos , Pandemias , Preparações Farmacêuticas
16.
Nat Commun ; 12(1): 4607, 2021 07 29.
Artigo em Inglês | MEDLINE | ID: mdl-34326325

RESUMO

Drug combination discovery depends on reliable synergy metrics but no consensus exists on the correct synergy criterion to characterize combined interactions. The fragmented state of the field confounds analysis, impedes reproducibility, and delays clinical translation of potential combination treatments. Here we present a mass-action based formalism to quantify synergy. With this formalism, we clarify the relationship between the dominant drug synergy principles, and present a mapping of commonly used frameworks onto a unified synergy landscape. From this, we show how biases emerge due to intrinsic assumptions which hinder their broad applicability and impact the interpretation of synergy in discovery efforts. Specifically, we describe how traditional metrics mask consequential synergistic interactions, and contain biases dependent on the Hill-slope and maximal effect of single-drugs. We show how these biases systematically impact synergy classification in large combination screens, potentially misleading discovery efforts. Thus the proposed formalism can provide a consistent, unbiased interpretation of drug synergy, and accelerate the translatability of synergy studies.


Assuntos
Biologia Computacional/métodos , Descoberta de Drogas/métodos , Benchmarking/métodos , Benchmarking/normas , Consenso , Combinação de Medicamentos , Descoberta de Drogas/normas , Sinergismo Farmacológico , Humanos , Modelos Teóricos , Software
17.
Molecules ; 26(14)2021 Jul 11.
Artigo em Inglês | MEDLINE | ID: mdl-34299488

RESUMO

Nitrogen-containing heterocyclic rings are common structural components of marketed drugs. Among these heterocycles, imidazole/fused imidazole rings are present in a wide range of bioactive compounds. The unique properties of such structures, including high polarity and the ability to participate in hydrogen bonding and coordination chemistry, allow them to interact with a wide range of biomolecules, and imidazole-/fused imidazole-containing compounds are reported to have a broad spectrum of biological activities. This review summarizes recent reports of imidazole/fused imidazole derivatives as anticancer agents appearing in the peer-reviewed literature from 2018 through 2020. Such molecules have been shown to modulate various targets, including microtubules, tyrosine and serine-threonine kinases, histone deacetylases, p53-Murine Double Minute 2 (MDM2) protein, poly (ADP-ribose) polymerase (PARP), G-quadraplexes, and other targets. Imidazole-containing compounds that display anticancer activity by unknown/undefined mechanisms are also described, as well as key features of structure-activity relationships. This review is intended to provide an overview of recent advances in imidazole-based anticancer drug discovery and development, as well as inspire the design and synthesis of new anticancer molecules.


Assuntos
Antineoplásicos/química , Antineoplásicos/farmacologia , Imidazóis/química , Imidazóis/farmacologia , Animais , Descoberta de Drogas/métodos , Humanos , Relação Estrutura-Atividade
18.
Chem Soc Rev ; 50(16): 9121-9151, 2021 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-34212944

RESUMO

COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the most severe disruptions to societies and economies since the Great Depression. Massive experimental and computational research effort to understand and characterize the disease and rapidly develop diagnostics, vaccines, and drugs has emerged in response to this devastating pandemic and more than 130 000 COVID-19-related research papers have been published in peer-reviewed journals or deposited in preprint servers. Much of the research effort has focused on the discovery of novel drug candidates or repurposing of existing drugs against COVID-19, and many such projects have been either exclusively computational or computer-aided experimental studies. Herein, we provide an expert overview of the key computational methods and their applications for the discovery of COVID-19 small-molecule therapeutics that have been reported in the research literature. We further outline that, after the first year the COVID-19 pandemic, it appears that drug repurposing has not produced rapid and global solutions. However, several known drugs have been used in the clinic to cure COVID-19 patients, and a few repurposed drugs continue to be considered in clinical trials, along with several novel clinical candidates. We posit that truly impactful computational tools must deliver actionable, experimentally testable hypotheses enabling the discovery of novel drugs and drug combinations, and that open science and rapid sharing of research results are critical to accelerate the development of novel, much needed therapeutics for COVID-19.


Assuntos
COVID-19/tratamento farmacológico , Simulação por Computador , Desenho de Fármacos , Descoberta de Drogas/métodos , Reposicionamento de Medicamentos , Antivirais/uso terapêutico , COVID-19/virologia , Ensaios Clínicos como Assunto , Humanos , Pandemias , SARS-CoV-2/efeitos dos fármacos
19.
Molecules ; 26(14)2021 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-34299458

RESUMO

Co-crystal innovation is an opportunity in drug development for both scientists and industry. In line with the "green pharmacy" concept for obtaining safer methods and advanced pharmaceutical products, co-crystallization is one of the most promising approaches to find novel patent drugs, including non-steroidal anti-inflammatory drugs (NSAID). This kind of multi-component system improves previously poor physicochemical and mechanical properties through non-covalent interactions. Practically, there are many challenges to find commercially viable co-crystal drugs. The difficulty in selecting co-formers becomes the primary problem, followed by unexpected results, such as decreased solubility and dissolution, spring and parachute effect, microenvironment pH effects, changes in instability, and polymorphisms, which can occur during the co-crystal development. However, over time, NSAID co-crystals have been continuously updated regarding co-formers selection and methods development.


Assuntos
Anti-Inflamatórios não Esteroides/química , Anti-Inflamatórios não Esteroides/uso terapêutico , Descoberta de Drogas/métodos , Anti-Inflamatórios não Esteroides/metabolismo , Química Farmacêutica/métodos , Cristalização/métodos , Preparações Farmacêuticas , Solubilidade
20.
Molecules ; 26(13)2021 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-34279369

RESUMO

In this review, a timeline starting at the willow bark and ending in the latest discoveries of analgesic and anti-inflammatory drugs will be discussed. Furthermore, the chemical features of the different small organic molecules that have been used in pain management will be studied. Then, the mechanism of different types of pain will be assessed, including neuropathic pain, inflammatory pain, and the relationship found between oxidative stress and pain. This will include obtaining insights into the cyclooxygenase action mechanism of nonsteroidal anti-inflammatory drugs (NSAID) such as ibuprofen and etoricoxib and the structural difference between the two cyclooxygenase isoforms leading to a selective inhibition, the action mechanism of pregabalin and its use in chronic neuropathic pain, new theories and studies on the analgesic action mechanism of paracetamol and how changes in its structure can lead to better characteristics of this drug, and cannabinoid action mechanism in managing pain through a cannabinoid receptor mechanism. Finally, an overview of the different approaches science is taking to develop more efficient molecules for pain treatment will be presented.


Assuntos
Descoberta de Drogas/métodos , Neuralgia/tratamento farmacológico , Manejo da Dor/métodos , Animais , Anti-Inflamatórios não Esteroides/química , Anti-Inflamatórios não Esteroides/uso terapêutico , Bloqueadores dos Canais de Cálcio/química , Bloqueadores dos Canais de Cálcio/farmacologia , Canabinoides/química , Canabinoides/uso terapêutico , Humanos
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