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1,352 result(s) for "Antiviral Agents - classification"
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A SARS-CoV-2 protein interaction map reveals targets for drug repurposing
A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption . There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein-protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19.
The pandemic pipeline
Companies are doing their best to accelerate experimental drugs and vaccines for COVID-19 through the pipeline. Each faces its own set of challenges, but all agree on the need for a radical rethink of the clinical development process for pandemics. Companies are doing their best to accelerate experimental drugs and vaccines for COVID-19 through the pipeline. Each faces its own set of challenges, but all agree on the need for a radical rethink of the clinical development process for pandemics.
A painful lesson from the COVID-19 pandemic: the need for broad-spectrum, host-directed antivirals
While the COVID-19 pandemic has spurred intense research and collaborative discovery worldwide, the development of a safe, effective, and targeted antiviral from the ground up is time intensive. Therefore, most antiviral discovery efforts are focused on the re-purposing of clinical stage or approved drugs. While emerging data on drugs undergoing COVID-19 repurpose are intriguing, there is an undeniable need to develop broad-spectrum antivirals to prevent future viral pandemics of unknown origin. The ideal drug to curtail rapid viral spread would be a broad-acting agent with activity against a wide range of viruses. Such a drug would work by modulating host-proteins that are often shared by multiple virus families thereby enabling preemptive drug development and therefore rapid deployment at the onset of an outbreak. Targeting host-pathways and cellular proteins that are hijacked by viruses can potentially offer broad-spectrum targets for the development of future antiviral drugs. Such host-directed antivirals are also likely to offer a higher barrier to the development and selection of drug resistant mutations. Given that most approved antivirals do not target host-proteins, we reinforce the need for the development of such antivirals that can be used in pre- and post-exposure populations.
Biochemical and Computational Approach of Selected Phytocompounds from Tinospora crispa in the Management of COVID-19
A pandemic caused by the novel coronavirus (SARS-CoV-2 or COVID-19) began in December 2019 in Wuhan, China, and the number of newly reported cases continues to increase. More than 19.7 million cases have been reported globally and about 728,000 have died as of this writing (10 August 2020). Recently, it has been confirmed that the SARS-CoV-2 main protease (Mpro) enzyme is responsible not only for viral reproduction but also impedes host immune responses. The Mpro provides a highly favorable pharmacological target for the discovery and design of inhibitors. Currently, no specific therapies are available, and investigations into the treatment of COVID-19 are lacking. Therefore, herein, we analyzed the bioactive phytocompounds isolated by gas chromatography–mass spectroscopy (GC-MS) from Tinospora crispa as potential COVID-19 Mpro inhibitors, using molecular docking study. Our analyses unveiled that the top nine hits might serve as potential anti-SARS-CoV-2 lead molecules, with three of them exerting biological activity and warranting further optimization and drug development to combat COVID-19.
noncovalent class of papain-like protease/deubiquitinase inhibitors blocks SARS virus replication
We report the discovery and optimization of a potent inhibitor against the papain-like protease (PLpro) from the coronavirus that causes severe acute respiratory syndrome (SARS-CoV). This unique protease is not only responsible for processing the viral polyprotein into its functional units but is also capable of cleaving ubiquitin and ISG15 conjugates and plays a significant role in helping SARS-CoV evade the human immune system. We screened a structurally diverse library of 50,080 compounds for inhibitors of PLpro and discovered a noncovalent lead inhibitor with an IC₅₀ value of 20 μM, which was improved to 600 nM via synthetic optimization. The resulting compound, GRL0617, inhibited SARS-CoV viral replication in Vero E6 cells with an EC₅₀ of 15 μM and had no associated cytotoxicity. The X-ray structure of PLpro in complex with GRL0617 indicates that the compound has a unique mode of inhibition whereby it binds within the S4-S3 subsites of the enzyme and induces a loop closure that shuts down catalysis at the active site. These findings provide proof-of-principle that PLpro is a viable target for development of antivirals directed against SARS-CoV, and that potent noncovalent cysteine protease inhibitors can be developed with specificity directed toward pathogenic deubiquitinating enzymes without inhibiting host DUBs.
A new advanced in silico drug discovery method for novel coronavirus (SARS-CoV-2) with tensor decomposition-based unsupervised feature extraction
COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Although there are a large number of candidate drug compounds that may be useful for treating COVID-19, the evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary. In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE. Numerous drugs were successfully screened, including many known antiviral drug compounds such as C646, chelerythrine chloride, canertinib, BX-795, sorafenib, sorafenib, QL-X-138, radicicol, A-443654, CGP-60474, alvocidib, mitoxantrone, QL-XII-47, geldanamycin, fluticasone, atorvastatin, quercetin, motexafin gadolinium, trovafloxacin, doxycycline, meloxicam, gentamicin, and dibromochloromethane. The screen also identified ivermectin, which was first identified as an anti-parasite drug and recently the drug was included in clinical trials for SARS-CoV-2. The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.
Bioactive Natural Antivirals: An Updated Review of the Available Plants and Isolated Molecules
Viral infections and associated diseases are responsible for a substantial number of mortality and public health problems around the world. Each year, infectious diseases kill 3.5 million people worldwide. The current pandemic caused by COVID-19 has become the greatest health hazard to people in their lifetime. There are many antiviral drugs and vaccines available against viruses, but they have many disadvantages, too. There are numerous side effects for conventional drugs, and active mutation also creates drug resistance against various viruses. This has led scientists to search herbs as a source for the discovery of more efficient new antivirals. According to the World Health Organization (WHO), 65% of the world population is in the practice of using plants and herbs as part of treatment modality. Additionally, plants have an advantage in drug discovery based on their long-term use by humans, and a reduced toxicity and abundance of bioactive compounds can be expected as a result. In this review, we have highlighted the important viruses, their drug targets, and their replication cycle. We provide in-depth and insightful information about the most favorable plant extracts and their derived phytochemicals against viral targets. Our major conclusion is that plant extracts and their isolated pure compounds are essential sources for the current viral infections and useful for future challenges.
Enhancing HCV NS3 Inhibitor Classification with Optimized Molecular Fingerprints Using Random Forest
The classification of Hepatitis C virus (HCV) NS3 inhibitors is essential for identifying potential antiviral agents through computational methods. This study aims to develop an optimized machine learning (ML) model using random forest (RF) and molecular fingerprints to accurately classify HCV NS3 inhibitors. A dataset of 965 molecules was retrieved from the ChEMBL database, and 290 bioactive compounds were selected for model training. Twelve molecular fingerprint descriptors were tested, and the CDK graph-only fingerprint yielded the best performance. In addition to RF, performance comparisons of other classifiers such as instance-based k-nearest neighbor (IBk), logistic regression (LR), AdaBoost, and OneR were conducted using WEKA with various molecular fingerprint descriptors. The optimized RF model achieved an accuracy of 89.6552%, a mean absolute error (MAE) of 0.2114, a root mean square error (RMSE) of 0.3304, and a Matthews correlation coefficient (MCC) of 0.7950 on the test set. These results highlight the effectiveness of optimized molecular fingerprints in enhancing virtual screening (VS) for HCV inhibitors. This approach offers a data-driven method for drug discovery.
Nanoparticles as a novel and promising antiviral platform in veterinary medicine
Traditional veterinary virus vaccines, such as inactivated and live-attenuated vaccines, have achieved tremendous success in controlling many viral diseases of livestock and chickens worldwide. However, many recent viral outbreaks caused by different emerging and re-emerging viruses continue to be reported annually worldwide. It is therefore necessary to develop new control regimens. Nanoparticle research has received considerable attention in the last two decades as a promising platform with significant success in veterinary medicine, replacing traditional viral vector vaccines. However, the field of nanoparticle applications is still in its initial phase of growth. Here, we discuss various preparation methods, characteristics, physical properties, antiviral effects, and pharmacokinetics of well-developed nanoparticles and the potential of nanoparticles or nano-vaccines as a promising antiviral platform for veterinary medicine.
RECOVERY 1 year on: a rare success in the COVID-19 clinical trial landscape
Peter Horby, co-lead on the RECOVERY platform trial, discusses the origins, lessons learned and future plans for one of the most informative studies of COVID-19 therapeutics.Peter Horby, co-lead on the RECOVERY platform trial, discusses the origins, lessons learned and future plans for one of the most informative studies of COVID-19 therapeutics.