A Review on the Novel Coronavirus Disease based on In-silico Analysis of Various Drugs and Target Proteins

Coronavirus Disease (COVID-19) is a new disease that emerged in Wuhan, China which spreads through close contact of people, often by small droplets produced during coughing or sneezing. Detail mechanism by which it spreads between people are under investigation. The World Health Organization (WHO) declared this disease as a pandemic after the severity of the disease increased. Many scientific reports gathered have suggested many drugs that could be potential candidates for the treatment. Although, clinical effectiveness has not been fully evaluated. In this review, we have aggregated the data from few research articles, official news websites and few review papers regarding its phylogenetic relation, genomic constitution, transmission, replication and in-silico analysis done by researchers for few potent drugs that are currently used to cure COVID-19. SARS-CoV-2 belongs to Betacoronavirus genus with Genome structure consists 14 Open Reading Frames (ORFs) that encode 27 proteins. Coronavirus replicates into the host cells having unique mechanisms like ribosome frame-shifting and synthesis of genomic and sub genomic RNAs. In-silico methods have the advantage that they can make fast predictions for a large set of compounds in a high-throughput mode and also make their prediction based on the structure of a compound even before it has been synthesized. In-silico softwares have been used to find or to improve a novel bioactive compound, which may exhibit a strong affinity to a particular target in the drug development process.

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In Silico Analysis the Complementarity of Tomato MicroRNA/MicroRNA* Sequences with Cucumber Mosaic Virus (CMV) Genomic RNAs

Journal of Nanoscience and Nanotechnology ◽

10.1166/jnn.2013.7161 ◽

2013 ◽

Vol 13 (6) ◽

pp. 4421-4426 ◽

Cited By ~ 6

Author(s):

Junli Feng ◽

Jishuang Chen

Keyword(s):

Cucumber Mosaic Virus ◽

Mosaic Virus ◽

In Silico ◽

In Silico Analysis ◽

Genomic Rnas ◽

Tomato Microrna ◽

Silico Analysis

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Sea Urchin Pigments as Potential Therapeutic Agents Against the Spike Protein of SARS-CoV-2 Based on in Silico Analysis

10.26434/chemrxiv.12568595.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Elena Susana Barbieri ◽

Tamara Rubilar ◽

Ayelén Gázquez ◽

Marisa Avaro ◽

Erina Noé Seiler ◽

...

Keyword(s):

Sea Urchin ◽

In Silico ◽

In Silico Analysis ◽

Protein S ◽

Host Cells ◽

Spike Protein ◽

Therapeutic Drug ◽

The Novel ◽

Novel Coronavirus ◽

Silico Analysis

Several studies have been published regarding the interaction between the spike protein of the novel coronavirus SARS-CoV-2 and ACE2 receptor in the host cells. In the presente work, we evaluated the in silico properties of two sea urchin pigments, Echinochrome A (EchA) and Spinochromes (SpinA) against the Spike protein (S) towards finding a potential therapeutic drug against the disease caused by the novel coronavirus (COVID-19). The best ensemble docking pose of EchaA and SpinA showed a binding affinity of -5.9 and -6.7 kcal mol-1, respectively. The linked aminoacids (T505, G496 and Y449 for EchA and Y449, Q493 and G496 for SpinA) are in positions involved in ACE2 binding in both RBDs frim SARS-CoV and SARS-CoV-2 suggesting that EchA and SpinA may interact with Spike proteins drom both viruses. The results suggest that these pigments could act as inhibitors of S protein, pointing them as antiviral drugs for SARS-CoV-2.<br>

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An in silico analysis of early SARS-CoV-2 variant B.1.1.529 (Omicron) genomic sequences and their epidemiological correlates

10.1101/2021.12.18.21267908 ◽

2021 ◽

Author(s):

Ashutosh Kumar ◽

Adil Asghar ◽

Himanshu N. Singh ◽

Muneeb A. Faiq ◽

Sujeet Kumar ◽

...

Keyword(s):

In Silico ◽

Immune Escape ◽

Mutational Analysis ◽

In Silico Analysis ◽

Spike Protein ◽

World Health ◽

Genomic Sequences ◽

Binding Motif ◽

New Variant ◽

Silico Analysis

Background: A newly emerged SARS-CoV-2 variant B.1.1.529 has worried health policymakers worldwide due to the presence of a large number of mutations in its genomic sequence, especially in the spike protein region. World Health Organization (WHO) has designated it as a global variant of concern (VOC) and has named as Omicron. A surge in new COVID-19 cases has been reported from certain geographical locations, primarily in South Africa (SA) following the emergence of Omicron. Materials and methods: We performed an in silico analysis of the complete genomic sequences of Omicron available on GISAID (until 2021-12-6) to predict the functional impact of the mutations present in this variant on virus-host interactions in terms of viral transmissibility, virulence/lethality, and immune escape. In addition, we performed a correlation analysis of the relative proportion of the genomic sequences of specific SARS-CoV-2 variants (in the period of 01 Oct-29 Nov 2021) with the current epidemiological data (new COVID-19 cases and deaths) from SA to understand whether the Omicron has an epidemiological advantage over existing variants. Results: Compared to the current list of global VOCs/VOIs (as per WHO) Omicron bears more sequence variation, specifically in the spike protein and host receptor-binding motif (RBM). Omicron showed the closest nucleotide and protein sequence homology with Alpha variant for the complete sequence as well as for RBM. The mutations were found primarily condensed in the spike region (28-48) of the virus. Further, the mutational analysis showed enrichment for the mutations decreasing ACE2-binding affinity and RBD protein expression, in contrast, increasing the propensity of immune escape. An inverse correlation of Omicron with Delta variant was noted (r=-0.99, p< .001, 95% CI: -0.99 to -0.97) in the sequences reported from SA post-emergence of the new variant, later showing a decrease. There has been a steep rise in the new COVID-19 cases in parallel with the increase in the proportion of Omicron since the first case (74-100%), on the contrary, the incidences of new deaths have not been increased (r=-0.04, p>0.05, 95% CI =-0.52 to 0.58). Conclusions: Omicron may have greater immune escape ability than the existing VOCs/VOIs. However, there are no clear indications coming out from the predictive mutational analysis that the Omicron may have higher virulence/lethality than other variants, including Delta. The higher ability for immune escape may be a likely reason for the recent surge in Omicron cases in SA.

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Sea Urchin Pigments as Potential Therapeutic Agents Against the Spike Protein of SARS-CoV-2 Based on in Silico Analysis

10.26434/chemrxiv.12568595 ◽

2020 ◽

Author(s):

Elena Susana Barbieri ◽

Tamara Rubilar ◽

Ayelén Gázquez ◽

Marisa Avaro ◽

Erina Noé Seiler ◽

...

Keyword(s):

Sea Urchin ◽

In Silico ◽

In Silico Analysis ◽

Protein S ◽

Host Cells ◽

Spike Protein ◽

Therapeutic Drug ◽

The Novel ◽

Novel Coronavirus ◽

Silico Analysis

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In Silico Analysis of High-Risk Missense Variants in Human ACE2 Gene and Susceptibility to SARS-CoV-2 Infection

BioMed Research International ◽

10.1155/2021/6685840 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Asmae Saih ◽

Hana Baba ◽

Meryem Bouqdayr ◽

Hassan Ghazal ◽

Salsabil Hamdi ◽

...

Keyword(s):

Protein Structure ◽

High Risk ◽

In Silico ◽

In Silico Analysis ◽

Host Cells ◽

Structure Stability ◽

Missense Variants ◽

Cumulative Score ◽

And Function ◽

Silico Analysis

SARS-CoV-2 coronavirus uses for entry to human host cells a SARS-CoV receptor of the angiotensin-converting enzyme (ACE2) that catalyzes the conversion of angiotensin II into angiotensin (1-7). To understand the effect of ACE2 missense variants on protein structure, stability, and function, various bioinformatics tools were used including SIFT, PANTHER, PROVEAN, PolyPhen2.0, I. Mutant Suite, MUpro, SWISS-MODEL, Project HOPE, ModPred, QMEAN, ConSurf, and STRING. All twelve ACE2 nsSNPs were analyzed. Six ACE2 high-risk pathogenic nsSNPs (D427Y, R514G, R708W, R710C, R716C, and R768W) were found to be the most damaging by at least six software tools (cumulative score between 6 and 7) and exert deleterious effect on the ACE2 protein structure and likely function. Additionally, they revealed high conservation, less stability, and having a role in posttranslation modifications such a proteolytic cleavage or ADP-ribosylation. This in silico analysis provides information about functional nucleotide variants that have an impact on the ACE2 protein structure and function and therefore susceptibility to SARS-CoV-2.

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A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

Seminars in Oncology ◽

10.1053/j.seminoncol.2020.02.012 ◽

2020 ◽

Vol 47 (6) ◽

pp. 398-408

Author(s):

Sonam Tulsyan ◽

Showket Hussain ◽

Balraj Mittal ◽

Sundeep Singh Saluja ◽

Pranay Tanwar ◽

...

Keyword(s):

Systematic Review ◽

Gallbladder Carcinoma ◽

In Silico ◽

In Silico Analysis ◽

Transcriptomic Profile ◽

Silico Analysis

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In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

10.1055/s-0039-1680245 ◽

2019 ◽

Author(s):

I. Farah ◽

A. El-Mubark ◽

M. Osman ◽

A. Soliman ◽

F. Ali ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Prothrombin Gene ◽

Silico Analysis

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Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

Current Medicinal Chemistry ◽

10.2174/0929867327666200727114410 ◽

2020 ◽

Vol 27 (38) ◽

pp. 6523-6535 ◽

Cited By ~ 3

Author(s):

Antreas Afantitis ◽

Andreas Tsoumanis ◽

Georgia Melagraki

Keyword(s):

Data Analysis ◽

Virtual Screening ◽

In Silico ◽

Model Development ◽

In Silico Analysis ◽

Material Design ◽

Efficient Solutions ◽

Biological Data ◽

Cost Efficient ◽

Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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