In Silico Prediction and Molecular Docking of SNPs in NRP1 Gene Associated with SARS-COV-2.

Neuropilin-1 (NRP1) which is a main transmembrane cell surface receptor acts as a host cell mediator resulting in increasing the SARS-Cov-2 infectivity and also plays a role in neuronal development, angiogenesis and axonal outgrowth. The goal of this study is to estimate the impact of single nucleotide polymorphisms (SNPs) in the NRP1 gene on the function, structure and stabilization of protein as well as on the miRNA-mRNA binding regions using bioinformatical tools. It is also aimed to investigate the changes caused by SNPs in NRP1 on interactions with drug molecule and spike protein. The missense type of SNPs was analyzed using SIFT, PolyPhen-2, SNAP2, PROVEAN, Mutation Assessor, SNPs&GO, PhD-SNP, I-Mutant 3.0, MUpro, STRING, Project HOPE, ConSurf, and PolymiRTS. Docking analyses were conducted by AutoDock Vina program. As a result, a total of 733 missense SNPs were determined within the NRP1 gene and nine SNPs were specified as damaging to the protein. The modelling results showed that wild and mutant type amino acids had some different properties such as size, charge, and hydrophobicity. Additionally, their three-dimensional structures of protein were utilized for confirmation of these differences. After evaluating the results, nine polymorphisms rs141633354, rs142121081, rs145954532, rs200028992, rs200660300, rs369312020, rs370117610, rs370551432, rs370641686 were determined to be damaging on the structure and function of NRP1 protein and located in conserved regions. The results of molecular docking showed that the binding affinity values are nearly the same for wild-type and mutant structures support that the mutations carried out are not in the focus of the binding site, therefore the ligand does not affect the binding energy. It is expected that the results will be useful for future studies.

In Silico Analysis of SARS-CoV-2 Spike Proteins of Different Field Variants.

Coronaviruses belong to the group of RNA family of viruses that trigger diseases in birds, humans, and mammals, which can cause respiratory tract infections. The COVID-19 pandemic has badly affected every part of the world. Our study aimed to explore the genome of SARS-CoV-2, followed by in silico analysis of its proteins. Different nucleotide and protein variants of SARS-CoV-2 were retrieved from NCBI. Contigs and consensus sequences were developed to identify these variants using SnapGene. Data of the variants that significantly differed from each other was run through Predict Protein software to understand the changes produced in the protein structure. The SOPMA web server was used to predict the secondary structure of the proteins. Tertiary structure details of the selected proteins were analyzed using the web server SWISS-MODEL. Sequencing results showed numerous single nucleotide polymorphisms in the surface glycoprotein, nucleocapsid, ORF1a, and ORF1ab polyprotein while the envelope, membrane, ORF3a, ORF6, ORF7a, ORF8, and ORF10 genes had no or few SNPs. Contigs were used to identify variations in the Alpha and Delta variants of SARS-CoV-2 with the reference strain (Wuhan). Some of the secondary structures of the SARS-CoV-2 proteins were predicted by using Sopma software and were further compared with reference strains of SARS-CoV-2 (Wuhan) proteins. The tertiary structure details of only spike proteins were analyzed through the SWISS-MODEL and Ramachandran plots. Through the Swiss-model, a comparison of the tertiary structure model of the SARS-CoV-2 spike protein of the Alpha and Delta variants was made with the reference strain (Wuhan). Alpha and Delta variants of the SARS-CoV-2 isolates submitted in GISAID from Pakistan with changes in structural and nonstructural proteins were compared with the reference strain, and 3D structure mapping of the spike glycoprotein and mutations in the amino acids were seen. The surprisingly increased rate of SARS-CoV-2 transmission has forced numerous countries to impose a total lockdown due to an unusual occurrence. In this research, we employed in silico computational tools to analyze the SARS-CoV-2 genomes worldwide to detect vital variations in structural proteins and dynamic changes in all SARS-CoV-2 proteins, mainly spike proteins, produced due to many mutations. Our analysis revealed substantial differences in the functionality, immunological, physicochemical, and structural variations in the SARS-CoV-2 isolates. However, the real impact of these SNPs can only be determined further by experiments. Our results can aid in vivo and in vitro experiments in the future.

Further quantitative in silico analysis of SARS-CoV-2 S-RBD Omicron BA.4, BA.5, BA.2.75, BQ.1, and BQ.1.1 transmissibility.

The Covid-19 variants' transmissibility was further quantitatively analyzed in silico to study the binding strength with ACE-2 and find the binding inhibitors. The molecular interaction energy values of their optimized complex structures (MIFS) demonstrated that Omicron BA.4 and 5's MIFS value (344.6 kcal mol-1) was equivalent to wild-type MIFS (346.1 kcal mol-1), that of Omicron BQ.1 and BQ. 1.1's MIFS value (309.9 and 364.6 kcal mol-1). Furthermore, the MIFS value of Omicron BA.2.75 (515.1 kcal mol-1) was about Delta-plus (511.3 kcal mol-1). The binding strength of Omicron BA.4, BA. 5, and BQ.1.1 may be neglectable, but that of Omicron BA.2.75 was urging. Furthermore, the 79 medicine candidates were analyzed as the binding inhibitors from binding strength with ACE-2. Only carboxy compounds were repulsed from the ACE-2 binding site indicating that further modification of medical treatment candidates may produce an effective binding inhibitor.

In Silico Prediction of Hub Genes Involved in Diabetic Kidney and COVID-19 Related Disease by Differential Gene Expression and Interactome Analysis.

Diabetic kidney disease (DKD) is a frequently chronic kidney pathology derived from diabetes comorbidity. This condition has irreversible damage and its risk factor increases with SARS-CoV-2 infection. The prognostic outcome for diabetic patients with COVID-19 is dismal, even with intensive medical treatment. However, there is still scarce information on critical genes involved in the pathophysiological impact of COVID-19 on DKD. Herein, we characterize differential expression gene (DEG) profiles and determine hub genes undergoing transcriptional reprogramming in both disease conditions. Out of 995 DEGs, we identified 42 shared with COVID-19 pathways. Enrichment analysis elucidated that they are significantly induced with implications for immune and inflammatory responses. By performing a protein-protein interaction (PPI) network and applying topological methods, we determine the following five hub genes: STAT1, IRF7, ISG15, MX1 and OAS1. Then, by network deconvolution, we determine their co-expressed gene modules. Moreover, we validate the conservancy of their upregulation using the Coronascape database (DB). Finally, tissue-specific regulation of the five predictive hub genes indicates that OAS1 and MX1 expression levels are lower in healthy kidney tissue. Altogether, our results suggest that these genes could play an essential role in developing severe outcomes of COVID-19 in DKD patients.

Preliminary Computational Analysis of Pyrazinamide-Based Derivatives Reveals Possible Inhibition of SARS-CoV-2 RNA-Dependent RNA Polymerase, and Their Possible Use as Antiviral Agents

Pyrazinamide is a pyrazine analog currently used to treat tuberculosis. It shares a core structure similar to that of favipiravir, which is a promising drug candidate that may inhibit the SARS-CoV-2 RNA-dependent RNA polymerase. This feature could be an opportunity for further drug development of anti-COVID-19 medication starting from a pyrazinamide core structure. This study aimed to determine and predict the most effective pyrazinamide-based analogs against the SARS-CoV-2 RNA-dependent RNA polymerase by using combined ligand-and structure-based computational analysis. This study performed a rational in silico study to screen pyrazinamide-like molecules from a commercially available ZINC database, with a similarity score higher than 0.40, and then these screened for acceptable pharmacokinetic properties, and then to further conduct molecular docking analysis with SARS-CoV-2 RNA-dependent RNA polymerase. The results showed that compound 12, having a dichloropyrimidine core structure had a similarity score of 0.446. It exerted the most binding affinity with RNA-dependent RNA polymerase, with estimated docking scores of −5.72, −5.25, −7.06, −7.00 and −4.63 kcal/mol in intact, ribosylated, mono-phosphoribosylated, di-phosphoribosylated and tri-phosphoribosylated forms, respectively. Watson-Crick base-pairing of compound 12 indicated that it favored binding with the uracil nucleoside of the RNA template. Compound 12 was confirmed as the lead compound, being a pyrazinamide-like molecule, and so might be a most promising candidate molecule, as an adenine analog RNA-dependent RNA polymerase inhibitor. It is suggested that the antiviral effect of this lead compound should be studied further as part of a drug discovery and development process. © 2022, Walailak University. All rights reserved.

A two-step process for in silico screening to assess the performance of qRTPCR kits against variant strains of SARS-CoV-2.

BACKGROUND: Since inception of the COVID-19 pandemic, early detection and isolation of positive cases is one of the key strategies to restrict disease transmission. Real time reverse transcription polymerase chain reaction (qRTPCR) has been the mainstay of diagnosis. Most of the qRTPCR kits were designed against the target genes of original strain of SARS-CoV-2. However, with the emergence of variant strains of SARS-CoV-2, sensitivity of the qRTPCR assays has reportedly reduced. In view of this, it is critical to continuously monitor the performance of the qRTPCR kits in the backdrop of variant strains of SARS-CoV-2. Real world monitoring of assay performance is challenging. Therefore, we developed a two-step in-silico screening process for evaluating the performance of various qRTPCR kits used in India. RESULTS: We analysed 73 qRT-PCR kits marketed in India, against the two SARS-CoV-2 VoCs. Sequences of both Delta (B.1.617.2) and Omicron (B.1.1.529) VoCs submitted to GISAID within a specific timeframe were downloaded, clustered to identify unique sequences and aligned with primer and probe sequences. Results were analysed following a two-step screening process. Out of 73 kits analysed, seven were unsatisfactory for detection of both Delta and Omicron VoCs, 10 were unsatisfactory for Delta VoC whereas 2 were unsatisfactory for only Omicron VoC. CONCLUSION: Overall, we have developed a useful screening process for evaluating the performance of qRTPCR assays against Delta and Omicron VoCs of SARS-CoV-2 which can be used for detecting SARS-CoV-2 VoCs that may emerge in future and can also be redeployed for other evolving pathogens of public health importance.

An in silico pipeline approach uncovers a potentially intricate network involving spike SARS-CoV-2 RNA, RNA vaccines, host RNA-binding proteins (RBPs), and host miRNAs at the cellular level.

BACKGROUND: In the last 2 years, we have been fighting against SARS-CoV-2 viral infection, which continues to claim victims all over the world. The entire scientific community has been mobilized in an attempt to stop and eradicate the infection. A well-known feature of RNA viruses is their high mutational rate, particularly in specific gene regions. The SARS-CoV-2 S protein is also affected by these changes, allowing viruses to adapt and spread more easily. The vaccines developed using mRNA coding protein S undoubtedly contributed to the "fight" against the COVID-19 pandemic even though the presence of new variants in the spike protein could result in protein conformational changes, which could affect vaccine immunogenicity and thus vaccine effectiveness. RESULTS: The study presents the findings of an in silico analysis using various bioinformatics tools finding conserved sequences inside SARS-CoV-2 S protein (encoding mRNA) same as in the vaccine RNA sequences that could be targeted by specific host RNA-binding proteins (RBPs). According to the results an interesting scenario emerges involving host RBPs competition and subtraction. The presence of viral RNA in cytoplasm could be a new tool in the virus's armory, allowing it to improve its chances of survival by altering cell gene expression and thus interfering with host cell processes. In silico analysis was used also to evaluate the presence of similar human miRNA sequences within RBPs motifs that can modulate human RNA expression. Increased cytoplasmic availability of exogenous RNA fragments derived from RNA physiological degradation could potentially mimic the effect of host human miRNAs within the cell, causing modulation of the host cell network. CONCLUSIONS: Our in silico analysis could aid in shedding light on the potential effects of exogenous RNA (i.e. viruses and vaccines), thereby improving our understanding of the cellular interactions between virus and host biomolecules. Finally, using the computational approach, it is possible to obtain a safety assessment of RNA-based vaccines as well as indications for use in specific clinical conditions.

The influence of new SARS-CoV-2 variant Omicron (B.1.1.529) on vaccine efficacy, its correlation to Delta variants: A computational approach.

The newly discovered COVID variant B.1.1.529 in Botswana has more than 30 mutations in spike and many other in non-spike proteins, far more than any other SARS-CoV-2 variant accepted as a variant of concern by the WHO and officially named Omicron, and has sparked concern among scientists and the general public. Our findings provide insights into structural modification caused by the mutations in the Omicrons receptor-binding domain and look into the effects on interaction with the hosts neutralizing antibodies CR3022, B38, CB6, P2B-2F6, and REGN, as well as ACE2R using an in silico approach. Computational analysis revealed that the Omicron variant has a higher binding affinity for the human ACE2 receptor than the wild and Delta (AY.1 and AY.2 strains), but lower than the Delta AY.3 strain. MD simulation and docking analysis suggest that the omicron and Delta AY.3 were found to have relatively unstable RBD structures and hampered interactions with antibodies more than wild and Delta (AY.1 and AY.2), which may lead to relatively more pathogenicity and antibody escape. In addition, we observed lower binding affinity of Omicron for human monoclonal antibodies (CR3022, B38, CB6, and P2B2F6) when compared to wild and Delta (AY.1 & AY.2). However, the binding affinity of Omicron RBD variants for CR3022, B38, and P2B2F6 antibodies is lower as compared to Delta AY.3, which might promote immune evasion and reinfection and needs further experimental investigation.

Serum microRNAs targeting ACE2 and RAB14 genes distinguish asymptomatic from critical COVID-19 patients.

Despite the extraordinary advances achieved to beat COVID-19 disease, many questions remain unsolved, including the mechanisms of action of SARS-CoV-2 and which factors determine why individuals respond so differently to the viral infection. Herein, we performed an in silico analysis to identify host microRNA targeting ACE2, TMPRSS2, and/or RAB14, all genes known to participate in viral entry and replication. Next, the levels of six microRNA candidates previously linked to viral and respiratory-related pathologies were measured in the serum of COVID-19-negative controls (n = 16), IgG-positive COVID-19 asymptomatic individuals (n = 16), and critical COVID-19 patients (n = 17). Four of the peripheral microRNAs analyzed (hsa-miR-32-5p, hsa-miR-98-3p, hsa-miR-423-3p, and hsa-miR-1246) were upregulated in COVID-19 critical patients compared with COVID-19-negative controls. Moreover, hsa-miR-32-5p and hsa-miR-1246 levels were also altered in critical versus asymptomatic individuals. Furthermore, these microRNA target genes were related to viral infection, inflammatory response, and coagulation-related processes. In conclusion, SARS-CoV-2 promotes the alteration of microRNAs targeting the expression of key proteins for viral entry and replication, and these changes are associated with disease severity. The microRNAs identified could be taken as potential biomarkers of COVID-19 progression as well as candidates for future therapeutic approaches against this disease.

COVID-19 and alcohol use disorder: putative differential gene expression patterns that might be associated with neurological complications.

BACKGROUND: Several lines of evidence suggest that SARS-CoV-2 invasion of the central nervous system leads to meningitis and encephalopathy syndromes. Additionally, chronic alcoholics were found to be at a higher risk of developing mental health problems and serious neurological manifestations, if exposed to SARS-CoV-2 infection. METHODS: Herein, we studied RNA seq data from alcoholics' brain tissue and COVID-19 patient's brain tissue to identify the common differentially expressed genes. RESULTS: Overlap analysis depicted the expression of seven genes (GHRL, SLN, VGF, IL1RL1, NPTX2, PDYN, and RPRML) that were significantly upregulated in both groups. Along with these, protein-protein interaction analysis revealed 10 other key molecules with strong interactions with the aforementioned genes. CONCLUSIONS: Taken together with the functional effect of these genes, we suggest a strong molecular link between COVID-19-induced severities and neurological impairment in patients suffering from alcohol abuse disorder. These findings emphasize the importance of identifying chronic alcoholism as a risk factor for developing cognitive and memory impairment in COVID-19 patients.

Design of SARS-CoV-2 Variant-Specific PCR Assays Considering Regional and Temporal Characteristics.

Monitoring the prevalence of SARS-CoV-2 variants is necessary to make informed public health decisions during the COVID-19 pandemic. PCR assays have received global attention, facilitating a rapid understanding of variant dynamics because they are more accessible and scalable than genome sequencing. However, as PCR assays target only a few mutations, their accuracy could be reduced when these mutations are not exclusive to the target variants. Here we introduce PRIMES, an algorithm that evaluates the sensitivity and specificity of SARS-CoV-2 variant-specific PCR assays across different geographical regions by incorporating sequences deposited in the GISAID database. Using PRIMES, we determined that the accuracy of several PCR assays decreased when applied beyond the geographic scope of the study in which the assays were developed. Subsequently, we used this tool to design Alpha and Delta variant-specific PCR assays for samples from Illinois, USA. In silico analysis using PRIMES determined the sensitivity/specificity to be 0.99/0.99 for the Alpha variant-specific PCR assay and 0.98/1.00 for the Delta variant-specific PCR assay in Illinois, respectively. We applied these two variant-specific PCR assays to six local sewage samples and determined the dominant SARS-CoV-2 variant of either the wild type, the Alpha variant, or the Delta variant. Using next-generation sequencing (NGS) of the spike (S) gene amplicons of the Delta variant-dominant samples, we found six mutations exclusive to the Delta variant (S:T19R, S:Δ156/157, S:L452R, S:T478K, S:P681R, and S:D950N). The consistency between the variant-specific PCR assays and the NGS results supports the applicability of PRIMES. IMPORTANCE Monitoring the introduction and prevalence of variants of concern (VOCs) and variants of interest (VOIs) in a community can help the local authorities make informed public health decisions. PCR assays can be designed to keep track of SARS-CoV-2 variants by measuring unique mutation markers that are exclusive to the target variants. However, the mutation markers may not be exclusive to the target variants because of regional and temporal differences in variant dynamics. We introduce PRIMES, an algorithm that enables the design of reliable PCR assays for variant detection. Because PCR is more accessible, scalable, and robust for sewage samples than sequencing technology, our findings will contribute to improving global SARS-CoV-2 variant surveillance.

Exploring the Link Between Vitamin D Deficiency and Cytokine Storms in COVID-19 Patients: An In Silico Analysis.

COVID-19 has become a global infectious pandemic affecting the entire world with complications related to the lungs and compromised immune systems. Recently, cytokine storms, which are hallmarks of the disease, have been identified in most COVID-19 patients. In addition, vitamin D deficiency is increasingly appearing to be another element exposing COVID-19 patients to a preferential increase in their symptoms. In an effort to identify a possible link between cytokine storms and vitamin D deficiency to streamline a possible treatment, an in silico analysis using bioinformatics approach was performed using collections of highly expressed cytokines in both severe acute respiratory syndrome and COVID-19 patients (commonly elevated cytokines) as well as vitamin D deficiency-associated genes (VD). Gene Multiple Association Network Integration Algorithm was used for network interactions, whereas the Enrichr enrichment analysis tool was used for biological functions. The network analysis GLay clustering results indicated the vitamin D receptor as a possible link between these two groups. Furthermore, cell chemotaxis and chemotactic-related features were identified as significantly affected pathways, which serve as possible key players mitigating cytokine storms under low vitamin D availability.

In Silico Analysis of Scopoletin Interaction with Potential SARS-CoV-2 Target

SARS-CoV-2 virus belongs to the family Coronaviridae, genus Betacoronavirus that appeared in late 2019 in Wuhan, China caused the historically remembered pandemic of COVID-19 which is still not subsiding. The main protease, or Mpro, plays a key role in the expression and replication of viral genes and is therefore an extremely attractive target for the design of antiviral drugs against SARS-CoV-2. Numerous herbal components have been studied for their natural ability to be effective antiviral agents. Scopoletin (6-methoxy-7-hydroxycoumarin) is a coumarin compound with antimicrobial, anti-inflammatory, antioxidant, antitumor and hepatoprotective properties that has been isolated from several plant species (Scopolia japonica Maxim. - Japanese belladonna, Artemisia scoparia Waldst. & Kit. - wormwood and Viburnum prunifolium L. - black haw). The objectives of this study were to examine the interaction of scopoletin with the main protease Mpro SARS-CoV-2 and to determine its potential antiviral activity. The research covers the virtual interaction of scopoletin and main proteases Mpro of SARS-CoV-2 virus using AutoDock Vina version 1.1.2. The three-dimensional structure of the main protease Mpro of SARS-CoV-2 (PDB ID: 6Y84), taken from Protein Data Bank, and the scopoletin structure taken from the PubChem chemical database, which was used in SDF form and converted using the online software Online SMILES Translator and Structure File Generator in PDB 3D form, were used for analysis. The final result of the analysis was visualized using Pymol 2.4. As positive control of binding affinity and proven therapeutic effect, we used hydroxychloroquine. Our results point out that scopoletin has a potential to bind to and inhibit the SARS-CoV-2 3Clpro main protease similarly to hydroxychloroquine that have been proven as antiviral in previous preclinical and clinical studies. After successful docking analysis it was shown that scopoletin has a binding affinity for the main protease SARS-CoV-2 at −6.9 kcal/mol. This result indicates that scopoletin, as well as other coumarin derivatives, can potentially be used in the fight against COVID-19, but further in vitro and in vivo studies are certainly necessary. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Modeling SARS-CoV-2 spike/ACE2 protein-protein interactions for predicting the binding affinity of new spike variants for ACE2, and novel ACE2 structurally related human protein targets, for COVID-19 handling in the 3PM context.

Aims: The rapid spread of new SARS-CoV-2 variants has highlighted the crucial role played in the infection by mutations occurring at the SARS-CoV-2 spike receptor binding domain (RBD) in the interactions with the human ACE2 receptor. In this context, it urgently needs to develop new rapid tools for quickly predicting the affinity of ACE2 for the SARS-CoV-2 spike RBD protein variants to be used with the ongoing SARS-CoV-2 genomic sequencing activities in the clinics, aiming to gain clues about the transmissibility and virulence of new variants, to prevent new outbreaks and to quickly estimate the severity of the disease in the context of the 3PM. Methods: In our study, we used a computational pipeline for calculating the interaction energies at the SARS-CoV-2 spike RBD/ACE2 protein-protein interface for a selected group of characterized infectious variants of concern/interest (VoC/VoI). By using our pipeline, we built 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for the VoC B.1.1.7-United Kingdom (carrying the mutations of concern/interest N501Y, S494P, E484K at the RBD), P.1-Japan/Brazil (RBD mutations: K417T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 (RBD mutations: N439K), and the recent B.1.617.1-India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Then, we used the obtained 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for predicting the interaction energies at the protein-protein interface. Results: Along SARS-CoV-2 mutation database screening and mutation localization analysis, it was ascertained that the most dangerous mutations at VoC/VoI spike proteins are located mainly at three regions of the SARS-CoV-2 spike "boat-shaped" receptor binding motif, on the RBD domain. Notably, the P.1 Japan/Brazil variant present three mutations, K417T, E484K, N501Y, located along the entire receptor binding motif, which apparently determines the highest interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein-protein interface, among those calculated. Conversely, it was also observed that the replacement of a single acidic/hydrophilic residue with a basic residue (E484K or N439K) at the "stern" or "bow" regions, of the boat-shaped receptor binding motif on the RBD, appears to determine an interaction energy with ACE2 receptor higher than that observed with single mutations occurring at the "hull" region or with other multiple mutants. In addition, our pipeline allowed searching for ACE2 structurally related proteins, i.e., THOP1 and NLN, which deserve to be investigated for their possible involvement in interactions with the SARS-CoV-2 spike protein, in those tissues showing a low expression of ACE2, or as a novel receptor for future spike variants. A freely available web-tool for the in silico calculation of the interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein-protein interface, starting from the sequences of the investigated spike and/or ACE2 variants, was made available for the scientific community at: https://www.mitoairm.it/covid19affinities. Conclusion: In the context of the PPPM/3PM, the employment of the described pipeline through the provided webservice, together with the ongoing SARS-CoV-2 genomic sequencing, would help to predict the transmissibility of new variants sequenced from future patients, depending on SARS-CoV-2 genomic sequencing activities and on the specific amino acid replacement and/or on its location on the SARS-CoV-2 spike RBD, to put in play all the possible counteractions for preventing the most deleterious scenarios of new outbreaks, taking into consideration that a greater transmissibility has not to be necessarily related to a more severe manifestation of the disease. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-021-00267-w.

Quantitative in silico analysis of SARS-CoV-2 S-RBD omicron mutant transmissibility.

Covid-19 variants transmissibility was quantitatively analyzed in silico to understand the reaction mechanisms and to find the reaction inhibitors. Especially, SARS-CoV-2 omicron mutant (omicron S-RBD) binding affinity with human angiotensin-converting enzyme-2 (ACE-2) was quantitatively analyzed using molecular interaction (MI) energy values (kcal.mol-1) between the S-RBD and ACE-2. The MI of their optimized complex structures demonstrated that omicron's MI value (749.8) was 1.4 times delta MI (538.1) and 2.7 times alfa MI (276.9). The omicron S-RBD demonstrated the most vital transmissible strength. The 14 currently proposed medical treatment compounds did not show as the inhibitors to block the omicron S-RBD and ACE-2 binding; instead, they adsorbed at the ACE-2 active site and may inhibit the ACE-2 activity. A modified candidate (Gallo catechin gallate) whose two phenolic hydroxy groups were replaced with two carboxy groups was repulsed from ACE-2, indicating that further modification of medical treatment candidates may produce an effective docking inhibitor.

Evaluating In Silico the Potential Health and Environmental Benefits of Houseplant Volatile Organic Compounds for an Emerging 'Indoor Forest Bathing' Approach.

The practice of spending time in green areas to gain the health benefits provided by trees is well known, especially in Asia, as 'forest bathing', and the consequent protective and experimentally detectable effects on the human body have been linked to the biogenic volatile organic compounds released by plants. Houseplants are common in houses over the globe and are particularly appreciated for aesthetic reasons as well for their ability to purify air from some environmental volatile pollutants indoors. However, to the best of our knowledge, no attempt has been made to describe the health benefits achievable from houseplants thanks to the biogenic volatile organic compounds released, especially during the day, from some of them. Therefore, we performed the present study, based on both a literature analysis and in silico studies, to investigate whether the volatile compounds and aerosol constituents emitted by some of the most common houseplants (such as peace lily plant, Spathiphyllum wallisii, and iron plant, Aspidistra eliator) could be exploited in 'indoor forest bathing' approaches, as proposed here for the first time not only in private houses but also public spaces, such as offices, hospitals, and schools. By using molecular docking (MD) and other in silico methodologies for estimating vapor pressures and chemico-physical/pharmacokinetic properties prediction, we found that ß-costol is an organic compound, emitted in appreciable amounts by the houseplant Spathiphyllum wallisii, endowed with potential antiviral properties as emerged by our MD calculations in a SARS-CoV-2 Mpro (main protease) inhibition study, together with sesquirosefuran. Our studies suggest that the anti-COVID-19 potential of these houseplant-emitted compounds is comparable or even higher than known Mpro inhibitors, such as eugenol, and sustain the utility of houseplants as indoor biogenic volatile organic compound emitters for immunity boosting and health protection.

Review on Multiple Facets of Drug Resistance: A Rising Challenge in the 21st Century.

With the advancements of science, antibiotics have emerged as an amazing gift to the human and animal healthcare sectors for the treatment of bacterial infections and other diseases. However, the evolution of new bacterial strains, along with excessive use and reckless consumption of antibiotics have led to the unfolding of antibiotic resistances to an excessive level. Multidrug resistance is a potential threat worldwide, and is escalating at an extremely high rate. Information related to drug resistance, and its regulation and control are still very little. To interpret the onset of antibiotic resistances, investigation on molecular analysis of resistance genes, their distribution and mechanisms are urgently required. Fine-tuned research and resistance profile regarding ESKAPE pathogen is also necessary along with other multidrug resistant bacteria. In the present scenario, the interaction of bacterial infections with SARS-CoV-2 is also crucial. Tracking and in-silico analysis of various resistance mechanisms or gene/s are crucial for overcoming the problem, and thus, the maintenance of relevant databases and wise use of antibiotics should be promoted. Creating awareness of this critical situation among individuals at every level is important to strengthen the fight against this fast-growing calamity. The review aimed to provide detailed information on antibiotic resistance, its regulatory molecular mechanisms responsible for the resistance, and other relevant information. In this article, we tried to focus on the correlation between antimicrobial resistance and the COVID-19 pandemic. This study will help in developing new interventions, potential approaches, and strategies to handle the complexity of antibiotic resistance and prevent the incidences of life-threatening infections.

Natural products for infectious microbes and diseases: an overview of sources, compounds, and chemical diversities.

As coronavirus disease 2019 (COVID-19) threatens human health globally, infectious disorders have become one of the most challenging problem for the medical community. Natural products (NP) have been a prolific source of antimicrobial agents with widely divergent structures and a range vast biological activities. A dataset comprising 618 articles, including 646 NP-based compounds from 672 species of natural sources with biological activities against 21 infectious pathogens from five categories, was assembled through manual selection of published articles. These data were used to identify 268 NP-based compounds classified into ten groups, which were used for network pharmacology analysis to capture the most promising lead-compounds such as agelasine D, dicumarol, dihydroartemisinin and pyridomycin. The distribution of maximum Tanimoto scores indicated that compounds which inhibited parasites exhibited low diversity, whereas the chemistries inhibiting bacteria, fungi, and viruses showed more structural diversity. A total of 331 species of medicinal plants with compounds exhibiting antimicrobial activities were selected to classify the family sources. The family Asteraceae possesses various compounds against C. neoformans, the family Anacardiaceae has compounds against Salmonella typhi, the family Cucurbitacea against the human immunodeficiency virus (HIV), and the family Ancistrocladaceae against Plasmodium. This review summarizes currently available data on NP-based antimicrobials against refractory infections to provide information for further discovery of drugs and synthetic strategies for anti-infectious agents.

Potential of NO donor furoxan as SARS-CoV-2 main protease (Mpro) inhibitors: in silico analysis.

The sharp spurt in positive cases of novel coronavirus-19 (SARS-CoV-2) worldwide has created a big threat to human. In view to expedite new drug leads for COVID-19, Main Proteases (Mpro) of novel Coronavirus (SARS-CoV-2) has emerged as a crucial target for this virus. Nitric oxide (NO) inhibits the replication cycle of SARS-CoV. Inhalation of nitric oxide is used in the treatment of severe acute respiratory syndrome. Herein, we evaluated the phenyl furoxan, a well-known exogenous NO donor to identify the possible potent inhibitors through in silico studies such as molecular docking as per target analysis for candidates bound to substrate binding pocket of SARS-COV-2 Mpro. Molecular dynamics (MD) simulations of most stable docked complexes (Mpro-22 and Mpro-26) helped to confirm the notable conformational stability of these docked complexes under dynamic state. Furthermore, Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations revealed energetic contributions of key residues of Mpro in binding with potent furoxan derivatives 22, 26. In the present study to validate the molecular docking, MD simulation and MM-PBSA results, crystal structure of Mpro bound to experimentally known inhibitor X77 was used as control and the obtained results are presented herein. We envisaged that spiro-isoquinolino-piperidine-furoxan moieties can be used as effective ligand for SARS-CoV-2 Mpro inhibition due to the presence of key isoquinolino-piperidine skeleton with additional NO effect.Communicated by Ramaswamy H. Sarma.

Synthesis and Characterization of a Minophosphonate Containing Chitosan Polymer Derivatives: Investigations of Cytotoxic Activity and in Silico Study of SARS-CoV-19.

Chitosan is broadly used as a biological material since of its excellent biological activities. This work describes investigations of chitosan interaction with SARS-CoV-2, which is occupied by human respiratory epithelial cells through communication with the human angiotension-converting enzyme II (ACE2). The ß-chitosan derivatives are synthesized and characterized by FT-IR, nuclear magnetic resonance (1H and 13C NMR), mass spectrometry, X-ray diffraction, TGA, DSC, and elemental analysis. The ß-chitosan derivatives were screened for cytotoxic activity against the HepG2 and MCF-7 (breast) cancer cell lines. Compound 1h (GI50 0.02 µM) is moderately active against the HepG2 cancer cell line, and Compound 1c is highly active (GI50 0.01 µM) against the MCF-7 cancer cell line. In addition, chitosan derivatives (1a-1j) docking against the SARS coronavirus are found by in-silico docking analysis. The findings show that compound 1c exhibits notable inhibition ability compared with other compounds, with a binding energy value of -7.9 kcal/mol. Based on the molecular docking results, the chitosan analog is proposed to be an alternative antiviral agent for SARS-CoV2.