Reporting dinaciclib and theodrenaline as a multitargeted inhibitor against SARS-CoV-2: an in-silico study.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is one of the rapid spreading coronaviruses that belongs to the Coronaviridae family. The rapidly evolving nature of SARS-CoV-2 results in a variety of variants with a capability of evasion to existing therapeutics and vaccines. So, there is an imperative need to discover potent drugs that can able to disrupt the function of multiple drug targets to tackle the SARS-CoV-2 menace. Here in this study, we took the different targets of SARS-CoV-2 prepared in the Schrodinger maestro. The library of the DrugBank database is screened against the selected crucial targets. Our molecular docking, Molecular Mechanics/Generalized Born Surface Area (MMGBSA), and molecular dynamics simulation studies led to identifying dinaciclib and theodrenaline as potential drugs against multiple drug targets: main protease, NSP15-endoribonuclease and papain-like-protease, of SARS-CoV-2. Dinaciclib with papain-like protease and NSP15-endoribonuclease show the docking score of -7.015 and -8.737, respectively, while the theodrenaline with NSP15-endoribonuclease and main protease produced the docking score of -8.507 and -7.289, respectively. Furthermore, the binding free energy calculations with MM/GBSA and molecular dynamics simulation studies of the complexes confirm the reliability of the drugs. The selected drugs are capable of binding to multiple targets simultaneously, thus withstanding their activity of target disruption in different variants of SARS-CoV-2. Although, the repurposed drugs are showing potent activity, but may need further in-vitro and in-vivo validations.Communicated by Ramaswamy H. Sarma.

SARS-CoV-2 Variants Show a Gradual Declining Pathogenicity and Pro-Inflammatory Cytokine Stimulation, an Increasing Antigenic and Anti-Inflammatory Cytokine Induction, and Rising Structural Protein Instability: A Minimal Number Genome-Based Approach.

Hyper-transmissibility with decreased disease severity is a typical characteristic of the SARS-CoV-2 Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from December 15 to 31, 2021. We report that the pathogenicity of SARS-CoV-2 variants decreases in the order of Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order of Omicron > Gamma > Wuhan > Delta. The Omicron spike RBD shows lower pathogenicity but higher antigenicity than other variants. The reported decreased disease severity by the Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-γ and IL-4 induction efficacy. The mutations in the N protein are probably associated with this decreased IL-6 induction and human DDX21-mediated increased IL-4 production for Omicron. Due to the mutations, the stability of S, M, N, and E proteins decreases in the order of Omicron > Gamma > Delta > Wuhan. Although a stronger spike RBD-hACE2 binding of Omicron increases its transmissibility, the lowest stability of its spike protein makes spike RBD-hACE2 interaction weak for systemic infection and for causing severe disease. Finally, the highest instability of the Omicron E protein may also be associated with decreased viral maturation and low viral load, leading to less severe disease and faster recovery. Our findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants. This minimal genome-based method may be used for other similar viruses avoiding robust analysis.

Predictive modeling and therapeutic repurposing of natural compounds against the receptor-binding domain of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a member of the Coronaviridae family, causing major destructions to human life directly and indirectly to the economic crisis around the world. Although there is significant reporting on the whole genome sequences and updated data for the different receptors are widely analyzed and screened to find a proper medication. Only a few bioassay experiments were completed against SARS-CoV-2 spike protein. We collected the compounds dataset from the PubChem Bioassay database having 1786 compounds and split it into the ratio of 80-20% for model training and testing purposes, respectively. Initially, we have created 11 models and validated them using a fivefold validation strategy. The hybrid consensus model shows a predictive accuracy of 95.5% for training and 94% for the test dataset. The model was applied to screen a virtual chemical library of Natural products of 2598 compounds. Our consensus model has successfully identified 75 compounds with an accuracy range of 70-100% as active compounds against SARS-CoV-2 RBD protein. The output of ML data (75 compounds) was taken for the molecular docking and dynamics simulation studies. In the complete analysis, the Epirubicin and Daunorubicin have shown the docking score of -9.937 and -9.812, respectively, and performed well in the molecular dynamics simulation studies. Also, Pirarubicin, an analogue of anthracycline, has widely been used due to its lower cardiotoxicity. It shows the docking score of -9.658, which also performed well during the complete analysis. Hence, after the following comprehensive pipeline-based study, these drugs can be further tested in vivo for further human utilization.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation and docking analysis of NF-κB protein binding with sulindac acid.

It is of interest to document the Molecular Dynamics Simulation and docking analysis of NF-κB target with sulindac sodium in combating COVID-19 for further consideration. Sulindac is a nonsteroidal anti-inflammatory drug (NSAID) of the arylalkanoic acid class that is marketed by Merck under the brand name Clinoril. We show the binding features of sulindac sodium with NF-κB that can be useful in drug repurposing in COVID-19 therapy.

Unveiling the multitargeted potential of N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) against SARS CoV-2: a virtual screening and molecular dynamics simulation study.

The coronaviridae family has caused the most destruction among all the viral families in modern sciences. It is one of the recently discovered and added members of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which has caused the global pandemic and significant destruction worldwide. However, scientists worldwide have developed vaccines, which are being given to humans. The mutated strain of the virus has caused various uncertainties about whether the discovered drug and vaccines affect it. Even after the World Health Organization's approval for the vaccines, their effectiveness and protection ratio are still a major concern. At the community level, to this date, there is no medicine available to cure the patients. In this study, we have screened the vast library from Drug Bank and identified N-(4-Aminobutanoyl)-S-(4-methoxybenzyl)-L-cysteinylglycine (NSL-CG) that can work against two major targets of SARS CoV-2, replication-transcription and RNA dependent polymerase. Further, we have performed the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and molecular dynamics simulation of the compound with both proteins individually, giving us enough evidence that the said drugs can work against the two targets together. Inhibiting the action of any of both proteins may lead to retaining the virus, and having a dual-targeted drug can be an extra precise measure for this process. The NSL-CG is an experimental drug belonging to the peptidomimetics class included in the small group of drugs with a docking score of -9.079 kcal/mol with replication-transcription -7.885 kcal/mol with RNA-dependent polymerase. Hence, through the complete flowed study, the NSL-CG can be further experimentally validated in in-vitro and in-vivo conditions before human utilisation.Communicated by Ramaswamy H. Sarma.

In-Silico Screening and Molecular Dynamics Simulation of Drug Bank Experimental Compounds against SARS-CoV-2.

For the last few years, the world has been going through a difficult time, and the reason behind this is severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), one of the significant members of the Coronaviridae family. The major research groups have shifted their focus towards finding a vaccine and drugs against SARS-CoV-2 to reduce the infection rate and save the life of human beings. Even the WHO has permitted using certain vaccines for an emergency attempt to cut the infection curve down. However, the virus has a great sense of mutation, and the vaccine's effectiveness remains questionable. No natural medicine is available at the community level to cure the patients for now. In this study, we have screened the vast library of experimental drugs of Drug Bank with Schrodinger's maestro by using three algorithms: high-throughput virtual screening (HTVS), standard precision, and extra precise docking followed by Molecular Mechanics/Generalized Born Surface Area (MMGBSA). We have identified 3-(7-diaminomethyl-naphthalen-2-YL)-propionic acid ethyl ester and Thymidine-5'-thiophosphate as potent inhibitors against the SARS-CoV-2, and both drugs performed impeccably and showed stability during the 100 ns molecular dynamics simulation. Both of the drugs are among the category of small molecules and have an acceptable range of ADME properties. They can be used after their validation in in-vitro and in-vivo conditions.

Hemi-Babim and Fenoterol as Potential Inhibitors of MPro and Papain-like Protease against SARS-CoV-2: An In-Silico Study.

The coronaviruses belong to the Coronaviridae family, and one such member, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is causing significant destruction around the world in the form of a global pandemic. Although vaccines have been developed, their effectiveness and level of protection is still a major concern, even after emergency approval from the World Health Organisation (WHO). At the community level, no natural medicine is currently available as a cure. In this study, we screened the vast library from Drug Bank and identified Hemi-Babim and Fenoterol as agents that can work against SARS-CoV-2. Furthermore, we performed molecular dynamics (MD) simulation for both compounds with their respective proteins, providing evidence that the said drugs can work against the MPro and papain-like protease, which are the main drug targets. Inhibiting the action of these targets may lead to retaining the virus. Fenoterol is a beta-2 adrenergic agonist used for the symptomatic treatment of asthma as a bronchodilator and tocolytic. In this study, Hemi-Babim and Fenoterol showed good docking scores of -7.09 and -7.14, respectively, and performed well in molecular dynamics simulation studies. Re-purposing the above medications has huge potential, as their effects are already well-proven and under public utilisation for asthma-related problems. Hence, after the comprehensive pipeline of molecular docking, MMGBSA, and MD simulation studies, these drugs can be tested in-vivo for further human utilisation.

Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) and Other Coronaviruses: A Genome-wide Comparative Annotation and Analysis.

Novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) causes mild to severe respiratory illness. The early symptoms may be fever, dry cough, sour throat, and difficulty in breathing which may lead to death in severe cases. Compared to previous outbreaks like SARS-CoV and Middle East Respiratory Syndrome (MERS), SARS-CoV2 disease (COVID-19) outbreak has been much distressing due to its high rate of infection but low infection fatality rate (IFR) with 1.4% around the world. World Health Organization (WHO) has declared (COVID-19) a pandemic on March 11, 2020. In the month of January 2020, the whole genome of SARS-CoV2 was sequenced which made work easy for researchers to develop diagnostic kits and to carry out drug repurposing to effectively alleviate the pandemic situation in the world. Now, it is important to understand why this virus has high rate of infectivity or is there any factor involved at the genome level which actually facilitates this virus infection globally? In this study, we have extensively analyzed the whole genomes of different coronaviruses infecting humans and animals in different geographical locations around the world. The main aim of the study is to identify the similarity and the mutational adaptation of the coronaviruses from different host and geographical locations to the SARS-CoV2 and provide a better strategy to understand the mutational rate for specific target-based drug designing. This study is focused to every annotation in a comparative manner which includes SNPs, repeat analysis with the different categorization of the short-sequence repeats and long-sequence repeats, different UTR's, transcriptional factors, and the predicted matured peptides with the specific length and positions on the genomes. The extensive analysis on SNPs revealed that Wuhan SARS-CoV2 and Indian SARS-CoV2 are having only eight SNPs. Collectively, phylogenetic analysis, repeat analysis, and the polymorphism revealed the genomic conserveness within the SARS-CoV2 and few other coronaviruses with very less mutational chances and the huge distance and mutations from the few other species.