scholarly journals NANOPARTICLE AS THE STRATEGY FOR THE DEVELOPMENT OF SARS-COV-2 ANTIVIRAL DRUGS

2021 ◽  
pp. 33-43
Author(s):  
SRI HARTATI YULIANI
Keyword(s):  
Antiviral Drug ◽  
Drug Repurposing ◽  
Antiviral Drugs ◽  
Nanostructured Lipid Carrier ◽  
Solid Lipid Nanoparticle ◽  
Metallic Nanoparticle ◽  
Drug Candidates ◽  
Polymeric Nanoparticle ◽  
Nanoparticle System ◽  
Selection Of

In just a matter of months, SARS-CoV-2 had spread around the world. Scientists collaborate to solve the problem. The development of antiviral drugs is a challenge in itself due to the rapidly changing nature of the virus. Selection of drug candidates can be done quickly through the repurposing drug method. Broad-spectrum antiviral drugs may be strong candidates for SARS-CoV-2 therapy. Nanotechnology is one solution in the development of antiviral drug delivery systems. The advantages possessed by the nanoparticle system can answer the need for an ideal antiviral drug. This article will focus on the development of nanoparticle preparations as a strategy in handling viruses, including SARS-CoV-2. The selection of article for the current review was searched from specialized databases such as Elsevier, Pubmed, Science Direct, Medscape and other credible databases using the keywords nanoparticle, SARS-CoV-2, Covid-19, drug repurposing, polymeric nanoparticle, micelle, liposome, solid lipid nanoparticle, nanostructured lipid carrier, dendrimer, metallic nanoparticle. The range of articles was 2007–2021.

scholarly journals Reinforcing the Supply Chain of Umifenovir and Other Antiviral Drugs with Retrosynthetic Software

2021 ◽  
Author(s):  
Yingfu Lin ◽  
Zirong Zhang ◽  
Babak Mahjour ◽  
Di Wang ◽  
Rui Zhang ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Raw Materials ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Antiviral Drugs ◽  
Multiple Drug ◽  
General Strategy ◽  
Inflammatory Drugs ◽  
Anti Inflammatory

Abstract The global disruption caused by the 2020 coronavirus pandemic stressed the supply chain of many products, including pharmaceuticals. Multiple drug repurposing studies for COVID-19 are now underway. If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it, will be available in the quantities required. We used retrosynthetic software to arrive at alternate chemical supply chains for the antiviral drug umifenovir, as well as eleven other antiviral and anti-inflammatory drugs. We have experimentally validated four routes to umifenovir and one route to bromhexine. In several instances, the software utilizes C–H functionalization logic, and one route to umifenovir employs functionalization of six C–H bonds. The general strategy we apply can be used to identify distinct starting materials, and relieve stress on existing supply chains.

scholarly journals The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation

10.2196/21169 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e21169
Author(s):  
Lyndsey Elaine Gates ◽  
Ahmed Abdeen Hamed
Keyword(s):  
Clinical Trials ◽  
Language Processing ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Biomedical Literature ◽  
Drug Candidates ◽  
Fast Development ◽  
Drug Knowledge ◽  
Biomedical Publications ◽  
Multiple Drugs

Background Driven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments. Objective The aims of this study are to identify off-label drugs that may have benefits for the coronavirus disease pandemic, present a novel ranking algorithm called CovidX to recommend existing drugs for potential repurposing, and validate the literature-based outcome with drug knowledge available in clinical trials. Methods To achieve such objectives, we applied natural language processing techniques to identify drugs and linked entities (eg, disease, gene, protein, chemical compounds). When such entities are linked, they form a map that can be further explored using network science tools. The CovidX algorithm was based upon a notion that we called “diversity.” A diversity score for a given drug was calculated by measuring how “diverse” a drug is calculated using various biological entities (regardless of the cardinality of actual instances in each category). The algorithm validates the ranking and awards those drugs that are currently being investigated in open clinical trials. The rationale behind the open clinical trial is to provide a validating mechanism of the PubMed results. This ensures providing up to date evidence of the fast development of this disease. Results From the analyzed biomedical literature, the algorithm identified 30 possible drug candidates for repurposing, ranked them accordingly, and validated the ranking outcomes against evidence from clinical trials. The top 10 candidates according to our algorithm are hydroxychloroquine, azithromycin, chloroquine, ritonavir, losartan, remdesivir, favipiravir, methylprednisolone, rapamycin, and tilorone dihydrochloride. Conclusions The ranking shows both consistency and promise in identifying drugs that can be repurposed. We believe, however, the full treatment to be a multifaceted, adjuvant approach where multiple drugs may need to be taken at the same time.

scholarly journals Elucidation on the Physicochemical Properties of Potential and Clinically Approved Antiviral Drugs: A Search for Effective Therapies against SARS-CoV-2 Infection

2020 ◽  
Vol 14 (suppl 1) ◽  
pp. 1025-1034
Author(s):  
Derick Erl P. Sumalapao
Keyword(s):  
Antiviral Activity ◽  
Physicochemical Properties ◽  
Vaccine Development ◽  
Heavy Atom ◽  
Antiviral Drug ◽  
Principal Component ◽  
Antiviral Drugs ◽  
Medical Emergency ◽  
Drug Candidates ◽  
Additional Information

COVID-19 has been confirmed in millions of individuals worldwide, rendering it a global medical emergency. In the absence of vaccines and the unavailability of effective drugs for the SARS-CoV-2 infection, vaccine development is being continuously explored and several antiviral compounds and immunotherapies are currently being investigated. Given the high similarity in genetic identity between SARS-CoV and SARS-CoV-2, the present investigation identified the interaction between the physicochemical properties and the antiviral activity of different potential and clinically approved antiviral drugs against SARS-CoV using hierarchically weighted principal component analysis. Representative drugs from the classes of neuraminidase inhibitors, reverse transcriptase inhibitors, protease inhibitors, nucleoside analogues, and other compounds with potential antiviral activity were examined. The pharmacologic classification and the biological activity of the different antiviral drugs were described using indices, namely, rotatable bond count, molecular weight, heavy atom count, and molecular complexity (92.32% contribution rate). The physicochemical properties and inhibitory action against SARS-CoV-2 of lopinavir, chloroquine, ivermectin, and ciclesonide validated the adequacy of the current computational approach. The findings of the present study provide additional information, although further investigation is warranted to identify potential targets and establish exact mechanisms, in the emergent search and design of antiviral drug candidates and their subsequent synthesis as effective therapies for COVID-19.

scholarly journals A phenomics approach for antiviral drug discovery

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jonne Rietdijk ◽  
Marianna Tampere ◽  
Aleksandra Pettke ◽  
Polina Georgiev ◽  
Maris Lapins ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Viral Infection ◽  
Drug Screening ◽  
Viral Infections ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Host Cells ◽  
Lung Fibroblasts ◽  
Morphological Properties ◽  
Drug Candidates

Abstract 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.

scholarly journals ENNAVIA is an innovative new method which employs neural networks for antiviral and anti-coronavirus activity prediction for therapeutic peptides

2021 ◽  
Author(s):  
Patrick Brendan Timmons ◽  
Chandralal M. Hewage
Keyword(s):  
In Silico ◽  
Antiviral Drug ◽  
Area Under The Curve ◽  
Antiviral Drugs ◽  
Test Accuracy ◽  
Sequencing Data ◽  
Drug Candidates ◽  
Therapeutic Peptides ◽  
Antiviral Activities ◽  
External Test

AbstractViruses represent one of the greatest threats to human health, necessitating the development of new antiviral drug candidates. Antiviral peptides often possess excellent biological activity and a favourable toxicity profile, and therefore represent a promising field of novel antiviral drugs. As the quantity of sequencing data grows annually, the development of an accurate in silico method for the prediction of peptide antiviral activities is important. This study leverages advances in deep learning and cheminformatics to produce a novel sequence-based deep neural network classifier for the prediction of antiviral peptide activity. The method out-performs the existent best-in-class, with an external test accuracy of 93.9%, Matthews correlation coefficient of 0.87 and an Area Under the Curve of 0.93 on the dataset of experimentally validated peptide activities. This cutting-edge classifier is available as an online web server at https://research.timmons.eu/ennavia, facilitating in silico screening and design of peptide antiviral drugs by the wider research community.

scholarly journals Entrectinib - a SARS-CoV-2 inhibitor in Human Lung Tissue (HLT) cells

2021 ◽  
Author(s):  
Alejandro Peralta-Garcia ◽  
Mariona Torrens-Fontanals ◽  
Tomasz Maciej Stepniewski ◽  
Judit Grau-Expósito ◽  
David Perea ◽  
...  
Keyword(s):  
Lung Tissue ◽  
Human Lung ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Pharmaceutical Companies ◽  
Research Groups ◽  
Specific Mechanism ◽  
Human Lung Tissue ◽  
Drug Candidates

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify potential drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a promising antiviral drug. We found that part of the antiviral action of entrectinib is mediated by a non-specific mechanism, likely occurring at the viral membrane level. Such a profile could provide entrectinib with protection against the development of drug resistance by emerging SARS-CoV-2 variants.

scholarly journals Reinforcing the supply chain of umifenovir and other antiviral drugs with retrosynthetic software

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yingfu Lin ◽  
Zirong Zhang ◽  
Babak Mahjour ◽  
Di Wang ◽  
Rui Zhang ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Functional Groups ◽  
Raw Materials ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Antiviral Drugs ◽  
Multiple Drug ◽  
Search Results ◽  
Inflammatory Drugs

AbstractThe global disruption caused by the 2020 coronavirus pandemic stressed the supply chain of many products, including pharmaceuticals. Multiple drug repurposing studies for COVID-19 are now underway. If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it, will be available in the quantities required. Here, we utilize retrosynthetic software to arrive at alternate chemical supply chains for the antiviral drug umifenovir, as well as eleven other antiviral and anti-inflammatory drugs. We have experimentally validated four routes to umifenovir and one route to bromhexine. In one route to umifenovir the software invokes conversion of six C–H bonds into C–C bonds or functional groups. The strategy we apply of excluding known starting materials from search results can be used to identify distinct starting materials, for instance to relieve stress on existing supply chains.

scholarly journals Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

2021 ◽  
Author(s):  
Michael Sugiyama ◽  
Haotian Cui ◽  
Dar'ya S Redka ◽  
Mehran Karimzadeh ◽  
Edurne Rujas ◽  
...  
Keyword(s):  
Antiviral Activity ◽  
Drug Targets ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Human Coronavirus ◽  
Independent Manner ◽  
Drug Candidates ◽  
Convolutional Networks ◽  
Target Drug ◽  
Coronavirus Infection

The COVID-19 pandemic has led to an urgent need for the identification of new antiviral drug therapies that can be rapidly deployed to treat patients with this disease. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of COVID-19. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cell-based experimental assessment reveals several clinically-relevant repurposing drug candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.

scholarly journals Entrectinib—A SARS-CoV-2 Inhibitor in Human Lung Tissue (HLT) Cells

2021 ◽  
Vol 22 (24) ◽  
pp. 13592
Author(s):  
Alejandro Peralta-Garcia ◽  
Mariona Torrens-Fontanals ◽  
Tomasz Maciej Stepniewski ◽  
Judith Grau-Expósito ◽  
David Perea ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Lung Tissue ◽  
Human Lung ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Pharmaceutical Companies ◽  
Research Groups ◽  
Human Lung Tissue ◽  
Drug Candidates

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a potential antiviral drug.

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