Dengue Structural Proteins as Antiviral Drug Targets: Current Status in the Drug Discovery & Development

2021 ◽  
pp. 113527
Author(s):  
Akshatha H. S ◽  
Gurubasavaraj V. Pujar ◽  
Arun Kumar Sethu ◽  
Meduri Bhagyalalitha ◽  
Manisha Singh
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Antiviral Drug ◽  
Structural Proteins ◽  
Current Status

Coronavirus Disease 2019: Virology and Drug Targets

2020 ◽  
Vol 20 ◽  
Author(s):  
Praveen Thaggikuppe Krishnamurthy
Keyword(s):  
High Throughput Screening ◽  
Drug Targets ◽  
Vaccine Development ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Structural Proteins ◽  
Current Status ◽  
Approved Drugs ◽  
Viral Target ◽  
Fda Approved Drugs

: The Coronavirus Disease 2019, a pandemic caused by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is seriously affecting global health and the economy. As the vaccine development takes time, the current research is focused on repurposing FDA approved drugs against the viral target proteins. This review discusses the current understanding of SARS-CoV-2 virology, its target structural proteins (S- glycoprotein), non-structural proteins (3- chymotrypsin-like protease, papain-like protease, RNA-dependent RNA polymerase, and helicase) and accessory proteins, drug discovery strategies (drug repurposing, artificial intelligence, and high-throughput screening), and the current status of antiviral drug development.

scholarly journals The current status and future directions of hepatitis B antiviral drug discovery

2016 ◽  
Vol 12 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Liudi Tang ◽  
Qiong Zhao ◽  
Shuo Wu ◽  
Junjun Cheng ◽  
Jinhong Chang ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Hepatitis B ◽  
Antiviral Drug ◽  
Current Status ◽  
Future Directions

scholarly journals Intracellular Life Cycle Kinetics of SARS-CoV-2 Predicted Using Mathematical Modelling

Viruses ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1735
Author(s):  
Dmitry Grebennikov ◽  
Ekaterina Kholodareva ◽  
Igor Sazonov ◽  
Antonina Karsonova ◽  
Andreas Meyerhans ◽  
...  
Keyword(s):  
Life Cycle ◽  
Drug Targets ◽  
Deterministic Model ◽  
Antiviral Drug ◽  
Computational Modelling ◽  
Structural Proteins ◽  
Model Parameters ◽  
Translation Rate ◽  
Infection Dynamics ◽  
Negative Effect

SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contributing to the observed disease phenotypes. In our study here, we formulate and calibrate a deterministic model of the SARS-CoV-2 life cycle. It provides a kinetic description of the major replication stages of SARS-CoV-2. Sensitivity analysis of the net viral progeny with respect to model parameters enables the identification of the life cycle stages that have the strongest impact on viral replication. These three most influential parameters are (i) degradation rate of positive sense vRNAs in cytoplasm (negative effect), (ii) threshold number of non-structural proteins enhancing vRNA transcription (negative effect), and (iii) translation rate of non-structural proteins (positive effect). The results of our analysis could be used for guiding the search for antiviral drug targets to combat SARS-CoV-2 infection.

scholarly journals Network-based Drug Repurposing for Human Coronavirus

2020 ◽  
Author(s):  
Yadi Zhou ◽  
Yuan Hou ◽  
Jiayu Shen ◽  
Yin Huang ◽  
William Martin ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
De Novo ◽  
Antiviral Drug ◽  
Drug Repurposing ◽  
Drug Combinations ◽  
Human Protein ◽  
High Morbidity ◽  
Potential Drug ◽  
Protein Interactome

AbstractHuman Coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle east respiratory syndrome coronavirus (MERS-CoV), and 2019 novel coronavirus (2019-nCoV), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV. Drug repurposing, represented as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV has the highest nucleotide sequence identity with SARS-CoV (79.7%) among the six other known pathogenic HCoVs. Specifically, the envelope and nucleocapsid proteins of 2019-nCoV are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and known HCoV-host interactions in the human protein-protein interactome, we computationally identified 135 putative repurposable drugs for the potential prevention and treatment of HCoVs. In addition, we prioritized 16 potential anti-HCoV repurposable drugs (including melatonin, mercaptopurine, and sirolimus) that were further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. Finally, we showcased three potential drug combinations (including sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the ‘Complementary Exposure’ pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human protein-protein interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations toward future clinical trials for HCoVs.

A computational chemistry perspective on the current status and future direction of hepatitis B antiviral drug discovery

2015 ◽  
Vol 123 ◽  
pp. 204-215 ◽  
Author(s):  
Dante Morgnanesi ◽  
Eric J. Heinrichs ◽  
Anthony R. Mele ◽  
Sean Wilkinson ◽  
Suzanne Zhou ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Hepatitis B ◽  
Computational Chemistry ◽  
Antiviral Drug ◽  
Current Status ◽  
Future Direction

Current Status and Future Perspective for Research on Medicinal Plants with Anticancerous Activity and Minimum Cytotoxic Value

2019 ◽  
Vol 20 (12) ◽  
pp. 1227-1243
Author(s):  
Hina Qamar ◽  
Sumbul Rehman ◽  
D.K. Chauhan
Keyword(s):  
Side Effects ◽  
Medicinal Plants ◽  
Anticancer Agents ◽  
Drug Targets ◽  
Psidium Guajava ◽  
Current Status ◽  
Future Perspective ◽  
Wide Range

Cancer is the second leading cause of morbidity and mortality worldwide. Although chemotherapy and radiotherapy enhance the survival rate of cancerous patients but they have several acute toxic effects. Therefore, there is a need to search for new anticancer agents having better efficacy and lesser side effects. In this regard, herbal treatment is found to be a safe method for treating and preventing cancer. Here, an attempt has been made to screen some less explored medicinal plants like Ammania baccifera, Asclepias curassavica, Azadarichta indica, Butea monosperma, Croton tiglium, Hedera nepalensis, Jatropha curcas, Momordica charantia, Moringa oleifera, Psidium guajava, etc. having potent anticancer activity with minimum cytotoxic value (IC50 >3μM) and lesser or negligible toxicity. They are rich in active phytochemicals with a wide range of drug targets. In this study, these medicinal plants were evaluated for dose-dependent cytotoxicological studies via in vitro MTT assay and in vivo tumor models along with some more plants which are reported to have IC50 value in the range of 0.019-0.528 mg/ml. The findings indicate that these plants inhibit tumor growth by their antiproliferative, pro-apoptotic, anti-metastatic and anti-angiogenic molecular targets. They are widely used because of their easy availability, affordable price and having no or sometimes minimal side effects. This review provides a baseline for the discovery of anticancer drugs from medicinal plants having minimum cytotoxic value with minimal side effects and establishment of their analogues for the welfare of mankind.

Covid 19 – Structural proteins and prospective drug candidates (Preprint)

2020 ◽  
Author(s):  
A.N Anoopkumar ◽  
Sharrel Rebello ◽  
Embalil Mathachan Aneesh
Keyword(s):  
Causative Agent ◽  
Protein Level ◽  
Drug Targets ◽  
Current Paper ◽  
Structural Proteins ◽  
Drug Candidates ◽  
Propagation Properties

UNSTRUCTURED Covid 19 the causative agent of the current devastating pandemic has turned out to be a notorious virus to all men-irrespective of either common to scientific calibre. Attempts to combat this deadly virus are the need of the hour and quite often the best way to defeat an opponent is to keenly study about its structural and propagation properties. The current paper describes briefly Covid 19 at the genomic, structural and protein level to the best of our knowledge. Furthermore, the prospects of possible drug targets that could aid in the control of this virus are also discussed.

scholarly journals Genomics-driven drug discovery based on disease-susceptibility genes

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Kyuto Sonehara ◽  
Yukinori Okada
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Drug Repurposing ◽  
Susceptibility Genes ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Associations

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

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