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Background: With the rapid development of the genomic sequence data for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants Delta (B.1.617.2) and Omicron (B.1.1.529), it is vital to successfully identify mutations within the genome., Objective: The main objective of the study is to investigate the full-length genome mutation analysis of 157 SARS-CoV-2 and its variant Delta and Omicron isolates. This study also provides possible effects at the structural level to understand the role of mutations and new insights into the evolution of COVID-19 and evaluates the differential level analysis in viral genome sequence among different nations. We have also tried to offer a mutation snapshot for these differences that could help in vaccine formulation. This study utilizes a unique and efficient method of targeting the stable genes for the drug discovery approach., Methods: Complete genome sequence information of SARS-CoV-2, Delta, and Omicron from online resources were used to predict structure domain identification, data mining, and screening; employing different bioinformatics tools. BioEdit software was used to perform their genomic alignments across countries and a phylogenetic tree as per the confidence of 500 bootstrapping values was constructed. Heterozygosity ratios were determined in-silico. A minimum spanning network (MSN) of selected populations was determined by Bruvo's distance role-based framework., Results: Out of all 157 different strains of SARS-CoV-2 and its variants, and their complete genome sequences from different countries, Corona nucleoca and DUF5515 were observed to be the most conserved domains. All genomes obtained changes in comparison to the Wuhan-Hu-1 strain, mainly in the TRS region (CUAAAC or ACGAAC). We discovered 596 mutations in all genes, with the highest number (321) found in ORF1ab (QHD43415.1), or TRS site mutations found only in ORF7a (1) and ORF10 (2). The Omicron variant has 30 mutations in the Spike protein and has a higher alpha-helix shape (23.46%) than the Delta version (22.03%). T478 was also discovered to be a prevalent polymorphism in Delta and Omicron variations, as well as genomic gaps ranging from 45 to 65aa. All 157 sequences contained variations and conformed to Nei's Genetic distance. We discovered heterozygosity (Hs) 0.01, mean anticipated Hs 0.32, the genetic diversity index (GDI) 0.01943989, and GD within population 0.01266951. The Hedrick value was 0.52324978, the GD coefficient was 0.52324978, the average Hs was 0.01371452, and the GD coefficient was 0.52324978. Among other countries, Brazil has the highest standard error (SE) rate (1.398), whereas Japan has the highest ratio of Nei's gene diversity (0.01)., Conclusions: The study's findings will assist in comprehending the shape and kind of complete genome, their streaming genomic sequences, and mutations in various additions of SARS-CoV-2, as well as its different variant strains like Omicron. These results will provide a scientific basis to design the vaccines and understand the genomic study of these viruses., Competing Interests: Declaration of Competing Interest We have no conflict of interest to declare., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

This research is a recent effort to explore some new heterocyclic compounds as novel and potential nonstructural protein-16-nonstructural protein-10 (Nsp16-Nsp10) inhibitors for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibition. The SARS-CoV-2 is causative agent of coronavirus disease 2019 (COVID-19) pandemic. A set of 58 molecules belongs to the naphthyridine and quinoline derivatives have been recently synthesized and considered for structure-based virtual screening against Nsp16-Nsp10. Molecular docking was virtually performed to screen for anti-SARS-CoV-2 activity against Nsp16-Nsp10. Fourteen out of fifty-eight compounds were exhibited binding affinity higher than co-crystal bound ligand s-adenosylmethionine (SAM) toward Nsp16-Nsp10. Further, the in silico pharmacokinetics assessment was carried out and it was found that two molecules possess the acceptable pharmacokinetic profile, hence considered promising Nsp16-Nsp10 inhibitors. The binding interaction analysis was revealed some crucial binding interactions between the final selected two molecules and ligand-binding amino acid residues of Nsp16-Nsp10 protein. In order to explore the characteristics of the protein-ligand complex and how selected small molecules retained inside the receptor cavity in dynamic states, all-atoms conventional molecular dynamics (MD) simulation was performed. Several factors were obtained from the MD simulation trajectory evidently suggested the potentiality of the molecules and stability of the protein-ligand complex. Finally, the binding affinity of both molecules and SAM was explored through the MM-GBSA approach which explained that both molecules possess strong affection towards the Nsp16-Nsp10. Hence, from the pharmacoinformatics assessment, it can be concluded that both heterocyclic compounds might be crucial for SARS-CoV-2 inhibition, subjected to experimental validation.Communicated by Ramaswamy H. Sarma.

The novel coronavirus Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 has caused a worldwide pandemic. The fatal virus has affected the health of human beings as well as the socio-economic situation all over the world. To date, no concrete medicinal solution has been proposed to combat the viral infection, calling for an urgent, strategic, and cost-effective drug development approach that may be achievable by applying targeted computational and virtual screening protocols. Immunity is the body's natural defense against disease-causing pathogens, which can be boosted by consuming plant-based or natural food products. Active constituents derived from natural sources also scavenge the free radicals and have anti-inflammatory activities. Herbs and spices have been used for various medicinal purposes. In this study, 2,96 365 natural and synthetic derivatives (ligands) belonging to 102 classes of compounds were obtained from PubChem and assessed on Lipinski's parameters for their potential bioavailability. Out of all the derivatives, 3254 obeyed Lipinski's rule and were virtually screened. The 115 top derivatives were docked against SARS-CoV-2, SARS-CoV, MERS-CoV, and HCoV-HKV1 main proteases (M pro s) as receptors using AutoDock Vina, AutoDock, and iGEMDOCK 2.1. The lowest binding energy was exhibited by ligands 2 and 6 against all the four M pro s. The molecular dynamic simulation was also performed with ligand 6 using the GROMACS package. Good bioactivity scores, absorption, distribution, metabolism, excretion, and toxicity profile and drug-like pharmacokinetic parameters were also obtained. Hydroxychloroquine was used as the control drug., (© 2021 John Wiley & Sons Ltd.)