Application of single-cell RNA sequencing on human testicular samples: a comprehensive review.

So far there has been no comprehensive review using systematic literature search strategies to show the application of single-cell RNA sequencing (scRNA-seq) in the human testis of the whole life cycle (from embryos to aging males). Here, we summarized the application of scRNA-seq analyses on various human testicular biological samples. A systematic search was conducted in PubMed and Gene Expression Omnibus (GEO), focusing on English researches published after 2009. Articles related to GEO data-series were also retrieved in PubMed or BioRxiv. 81 full-length studies were finally included in the review. ScRNA-seq has been widely used on different human testicular samples with various library strategies, and new cell subtypes such as State 0 spermatogonial stem cells (SSC) and stage_a/b/c Sertoli cells (SC) were identified. For the development of normal testes, scRNA-seq-based evidence showed dynamic transcriptional changes of both germ cells and somatic cells from embryos to adults. And dysregulated metabolic signaling or hedgehog signaling were revealed by scRNA-seq in aged SC or Leydig cells (LC), respectively. For infertile males, scRNA-seq studies revealed profound changes of testes, such as the increased proportion of immature SC/LC of Klinefelter syndrome, the somatic immaturity and altered germline autophagy of patients with non-obstructive azoospermia, and the repressed differentiation of SSC in trans-females receiving testosterone inhibition therapy. Besides, the re-analyzing of public scRNA-seq data made further discoveries such as the potential vulnerability of testicular SARS-CoV-2 infection, and both evolutionary conservatism and divergence among species. ScRNA-seq analyses would unveil mechanisms of testes' development and changes so as to help developing novel treatments for male infertility.

Bioinformatic assay reveal the potential mechanism of Guizhi-Shaoyao-Zhimu decoction against rheumatoid arthritis and mild-to-moderate COVID-19.

BACKGROUND AND OBJECTIVE: Patients with rheumatoid arthritis (RA) are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) than healthy population, but there is still no therapeutic strategy available for RA patients with corona virus disease 2019 (COVID-19). Guizhi-Shaoyao-Zhimu decoction (GSZD), Chinese ancient experience decoction, has a significant effect on the treatment of Rheumatism and gout. To prevent RA patients with mild-to-moderate COVID-19 from developing into severe COVID-19, this study explored the potential possibility and mechanism of GSZD in the treatment of this population. METHODS: In this study, we used bioinformatic approaches to explore common pharmacological targets and signaling pathways between RA and mild-to-moderate COVID-19, and to assess the potential mechanisms of in the treatment of patients with both diseases. Beside, molecular docking was used to explore the molecular interactions between GSZD and SARS-CoV-2 related proteins. RESULTS: Results showed that 1183 common targets were found in mild-to-moderate COVID-19 and RA, of which TNF was the most critical target. The crosstalk signaling pathways of the two diseases focused on innate immunity and T cells pathways. In addition, GSZD intervened in RA and mild-to-moderate COVID-19 mainly by regulating inflammation-related signaling pathways and oxidative stress. Twenty hub compounds in GSZD exhibited good binding potential to SARS-CoV-2 spike (S) protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), papain-like protease (PLpro) and human angiotensin-converting enzyme 2 (ACE2), thereby intervening in viral infection, replication and transcription. CONCLUSIONS: This finding provides a therapeutic option for RA patients against mild-to-moderate COVID-19, but further clinical validation is still needed.

The impact of mutation sets in receptor-binding domain of SARS-CoV-2 variants on the stability of RBD-ACE2 complex.

Aim: Bioinformatic analysis of mutation sets in receptor-binding domain (RBD) of currently and previously circulating SARS-CoV-2 variants of concern (VOCs) and interest (VOIs) to assess their ability to bind the ACE2 receptor. Methods: In silico sequence and structure-oriented approaches were used to evaluate the impact of single and multiple mutations. Results: Mutations detected in VOCs and VOIs led to the reduction of binding free energy of the RBD-ACE2 complex, forming additional chemical bonds with ACE2, and to an increase of RBD-ACE2 complex stability. Conclusion: Mutation sets characteristic of SARS-CoV-2 variants have complex effects on the ACE2 receptor-binding affinity associated with amino acid interactions at mutation sites, as well as on the acquisition of other viral adaptive advantages.

The increase in the infectious potential of SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Omicron, etc.) that causes COVID-19 is mainly due to virus mutations. Particularly important for the development of the disease is the interaction of the coronavirus spike protein with a receptor on the surface of human cell, as a result of which the virus penetrates the cell. Angiotensin-binding enzyme (ACE2) is such a receptor in humans, and there is a receptor-binding domain (RBD) in the coronavirus spike protein. In this study, using bioinformatic methods, an analysis of mutations in the RBD of the virus was carried out to find out their influence on the functionality and ability of the virus to interact with the ACE2 receptor with high stability, which ultimately leads to infection. A number of mutations increase the infectious potential of the virus. More recent variants of the virus have more than one mutation in the RBD, so their effects are complex. It is important that the coronavirus is constantly evolving, increasing the ability to bind to the ACE2 receptor, as well as avoiding the immune response. The Omicron variant, which has at least 15 mutations in the RBD, is the most successful in these directions.

Immunity Modulators, Repurposed Drugs and Candidate Vaccines for COVID-19: A Review

COVID-19, a pandemic has led the whole globe through unprecedented times and unpre-dictability that has adversely affected the humanity as a whole. Although the severe acute respiratory syndrome was reported in the year 2002-2004 of zoonotic origin caused by SARS-CoV-1 strain. Now recently, in December 2019, SARS-CoV-2 virus has emerged and swiftly spread to the whole world, taking a heavy toll on life. Studies are being conducted worldwide to find antiviral drugs act-ing specifically on the virus and to develop the vaccine for the disease. The present review article summarizes the currently undergoing clinical trials of Indian Ayurvedic herbs and their role in promoting immunity. It also includes studies focused on repurposing the existing drugs and finding alternative treatment methods that can be opted for potential treatment/management of COVID-19. Last but not the least, this paper provides a background on the development of preventive vaccines and the various bioinformatic tools utilized in order to help accelerate the research on coronavirus. The manuscript gives a brief outline of all the possible strategies and therapeutics underway in India and at the global level to fight against the microscopic adversary and lead to an affordable and speedy remedy for COVID-19.Copyright © 2021 Bentham Science Publishers.

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic level less than 4 months after the first official cases. Hence, the search for drugs and vaccines that could prevent or treat infections by SARS-CoV-2 began, intending to reduce a possible collapse of health systems. After 2 years, efforts to find therapies to treat COVID-19 continue. However, there is still much to be understood about the virus' pathology. Tools such as transcriptomics have been used to understand the impact of SARS-CoV-2 on different cells isolated from various tissues, leaving datasets in the databases that integrate genes and differentially expressed pathways during SARS-CoV-2 infection. After retrieving transcriptome datasets from different human cells infected with SARS-CoV-2 available in the database, we performed an integrative analysis associated with deep learning algorithms to determine differentially expressed targets mainly after infection. The targets found represented a fructose transporter (GLUT5) and a component of proteasome 26s. These targets were then molecularly modeled, followed by molecular docking that identified potential inhibitors for both structures. Once the inhibition of structures that have the expression increased by the virus can represent a strategy for reducing the viral replication by selecting infected cells, associating these bioinformatics tools, therefore, can be helpful in the screening of molecules being tested for new uses, saving financial resources, time, and making a personalized screening for each infectious disease.

Bioinformatics analysis based on high-throughput sequencing data to identify hub genes related to different clinical types of COVID-19.

This article aims to explore hub genes related to different clinical types of cases with COVID-19 and predict the therapeutic drugs related to severe cases. The expression profile of GSE166424 was divided into four data sets according to different clinical types of COVID-19 and then calculated the differential expression genes (DEGs). The specific genes of four clinical types of COVID-19 were obtained by Venn diagram and conducted enrichment analysis, protein-protein interaction (PPI) networks analysis, screening hub genes, and ROC curve analysis. The hub genes related to severe cases were verified in GSE171110, their RNA-specific expression tissues were obtained from the HPA database, and potential therapeutic drugs were predicted through the DGIdb database. There were 536, 266, 944, and 506 specific genes related to asymptomatic infections, mild, moderate, and severe cases, respectively. The hub genes of severe specific genes were AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11, and also differentially expressed in GSE171110 (P < 0.05), and their AUC values were greater than 0.955. The RNA tissue specificity of AURKB, CDC6, KIF11, UBE2C, CCNB2, CDC20, TOP2A, BUB1, and CCNB1 specifically enhanced on lymphoid tissue; CCNB2, CDC20, TOP2A, and BUB1 specifically expressed on the testis. Finally, 55 drugs related to severe COVID-19 were obtained from the DGIdb database. Summary, AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11 may be potential diagnostic biomarkers for severe COVID-19, which may affect immune and male reproductive systems. 55 drugs may be potential therapeutic drugs for severe COVID-19.

Bioinformatic analysis of the S protein of human respiratory coronavirus.

The present study aimed to apply bioinformatic methods to analyze the structure of the S protein of human respiratory coronaviruses, including severe respiratory disease syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), human coronavirus HKU1 (HCoV-HKU1), and severe respiratory disease syndrome coronavirus type 2 (SARS-CoV-2). We predicted and analyzed the physicochemical properties, hydrophilicity and hydrophobicity, transmembrane regions, signal peptides, phosphorylation and glycosylation sites, epitopes, functional domains, and motifs of the S proteins of human respiratory coronaviruses. All four S proteins contain a transmembrane region, which enables them to bind to host cell surface receptors. All four S proteins contain a signal peptide, phosphorylation sites, glycosylation sites, and epitopes. The predicted phosphorylation sites might mediate S protein activation, the glycosylation sites might affect the cellular orientation of the virus, and the predicted epitopes might have implications for the design of antiviral inhibitors. The S proteins of all four viruses have two structural domains, S1 (C-terminal and N-terminal domains) and S2 (homology region 1 and 2). Our bioinformatic analysis of the structural and functional domains of human respiratory coronavirus S proteins provides a basis for future research to develop broad-spectrum antiviral drugs, vaccines, and antibodies.

Drug Repurposing for SARS-COV-2 Using Molecular Docking

Drug repurposing is an unconventional approach that is used to investigate new therapeutic aids of existing and shelved drugs. Recent advancement in technologies and the availability of the data of genomics, proteomics, transcriptomics, etc., and with the accessibility of large and reliable database resources, there are abundantly of opportunities to discover drugs by drug repurposing in an efficient manner. The recent pandemic of SARS-COV-2, that caused the death of 6,245,750 human beings to date, has tremendously increase the exceptional usage of bioinformatics tools in interpreting the molecular characterizations of viral infections. In this paper, we have employed various bioinformatics tools such as AutoDock-Vina, PyMol etc. We have found a leading drug candidate Cepharanthine (CEP) that has shown better results and effectiveness than recently used antiviral drug candidates such as Favipiravir, IDX184, Remedesivir, Ribavirin and etc. This paper has analyzed CEP's potential therapeutic importance as a drug of choice in managing COVID-19 cases. It is anticipated that proposed study would be beneficial for researchers and medical practitioners in handling SARS-CoV-2 and its variant related diseases. © 2022 IEEE.

Revealing In Silico that Bacteria's Outer Membrane Proteins may Help our Bodies Replicate and Carry Severe Acute Respiratory Syndrome Coronavirus 2.

Some studies in the literature show that viruses can affect bacteria directly or indirectly, and viruses use their own specific ways to do these interactions. Furthermore, it is said that bacteria are prone to attachment mammalian cells during a viral illness using their surface proteins that bind to host extracellular matrix proteins such as fibronectin, fibrinogen, vitronectin, and elastin. A recent study identified the cooperation between bacteria and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in silico, in vitro, and in vivo. Like this study, we hypothesized that more bacteria protein might help SARS-CoV-2 transport and attach to angiotensin-converting enzyme 2 (ACE2). The bacteria's outer membrane proteins (OMPs) we chose were not random; they had to be on the outer surface of the bacteria because these proteins on the outer surface should have a high probability of interacting with both the spike protein and ACE2. We obtained by using bioinformatics tools that there may be binding between both ACE2 and spike protein of these bacteria's OMPs. Protein-protein interaction results also supported our hypothesis. Therefore, based on our predicted results, these bacteria OMPs may help SARS-CoV-2 move in our body, and both find and attach to ACE2. It is expected that these inferences obtained from the bioinformatics results may play a role in the SARS-CoV-2 virus reaching host cells. Thus, it may bring a different perspective to studies on how the virus can infect host cells.

SARS-CoV-2: Next Generation Sequencing and Analysis

Sars-cov-2 is the causative agent responsible for the global pandemic of COVID-19. Bioinformatics tools are used to sequence the viral genome, identify SARS-CoV-2 from all host genomes, and detect its variants. There is no all-in-one tool that can automatically analyse complete sequences, so different bioinformatics resources are needed to work together for detection and characterisation. This paper discusses the use of next-generation sequencing for virus definition and characterization. © 2022 SPIE. All rights reserved.

From Sequence Analysis to Application: Role of Bioinformatics to Understand Biological Systems

The field of biological sciences enumerates various important aspects of life forms, some of which remain mysterious to explain or validate. Though there has been a revolutionary advancement of tools and techniques to study different biological phenomena under laboratory conditions, there are significant limitations with implementing each concept in the laboratory. Sometimes, it is practically impossible to simulate the actual environmental conditions of living systems under in-vitro settings, or sometimes the requirements of life are discordant with various analytical techniques, or the study of complex evolutionary processes becomes technically difficult using wet-lab methods. Thus, these experimental challenges confine our boundary to explore the real world of biological systems, which may lead to the acquisition of knowledge with few lacunae. Bioinformatics as a discipline tries to fill those spaces to a major extent using in silico analysis and provides a deeper theoretical foundation and validation of existing biological principles. The importance and potential of bioinformatics have been witnessed in the pandemic times to fight against Covid-19. From developing new drugs and vaccines to crop improvement and space and environment studies, the field of bioinformatics has many prospects. This article aims to provide a bird's-eye view of different applications and cutting-edge bioinformatics approaches to understand biological systems and the emerging need to integrate this course into the education framework. © 2022, Indian Academy of Sciences.

[ORGANIZATION OF GENOMIC SURVEILLANCE FOR SARS-CoV-2 WITHIN THE MOSCOW CITY HEALTH DEPARTMENT].

An important goal of COVID-19 surveillance is to detect outbreaks using modern molecular epidemiology techniques based on methods to decode the full genome of the virus, since rapidly evolving RNA viruses, which include SARS-CoV-2, are constantly accumulating changes in their genomes. In addition to using these changes to identify the different virus lines spreading in the population, the availability of sequence information is very important. It will allow the identification of altered variants that may be more transmissible, cause more severe forms of disease, or be undetectable by existing diagnostic test systems. The global scientific community is particularly interested in changes in the spike protein (S-protein, Spike) because they are responsible for binding and penetration into the host cell, lead to false-negative results in diagnostic tests, and affect transmission rates, health outcomes, therapeutic interventions, and vaccine efficacy.Genomic surveillance uses next-generation sequencing (NGS) applications and makes data on the full genome of the virus available. These methods offer new means to detect variants that differ phenotypically or antigenically. This approach promotes earlier prediction as well as effective strategies to mitigate and contain outbreaks of SARS-CoV-2 and other new viruses long before they spread worldwide.Today, molecular typing of strains is playing an increasingly important role in this process, as it makes it possible to identify samples that share a common molecular «fingerprint¼.

Modeling Kaempferol as a Potential Pharmacological Agent for COVID-19/PF Co-Occurrence Based on Bioinformatics and System Pharmacological Tools.

Objective: People suffering from coronavirus disease 2019 (COVID-19) are prone to develop pulmonary fibrosis (PF), but there is currently no definitive treatment for COVID-19/PF co-occurrence. Kaempferol with promising antiviral and anti-fibrotic effects is expected to become a potential treatment for COVID-19 and PF comorbidities. Therefore, this study explored the targets and molecular mechanisms of kaempferol against COVID-19/PF co-occurrence by bioinformatics and network pharmacology. Methods: Various open-source databases and Venn Diagram tool were applied to confirm the targets of kaempferol against COVID-19/PF co-occurrence. Protein-protein interaction (PPI), MCODE, key transcription factors, tissue-specific enrichment, molecular docking, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to clarify the influential molecular mechanisms of kaempferol against COVID-19 and PF comorbidities. Results: 290 targets and 203 transcription factors of kaempferol against COVID-19/PF co-occurrence were captured. Epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase SRC (SRC), mitogen-activated protein kinase 3 (MAPK3), mitogen-activated protein kinase 1 (MAPK1), mitogen-activated protein kinase 8 (MAPK8), RAC-alpha serine/threonine-protein kinase (AKT1), transcription factor p65 (RELA) and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) were identified as the most critical targets, and kaempferol showed effective binding activities with the above critical eight targets. Further, anti-COVID-19/PF co-occurrence effects of kaempferol were associated with the regulation of inflammation, oxidative stress, immunity, virus infection, cell growth process and metabolism. EGFR, interleukin 17 (IL-17), tumor necrosis factor (TNF), hypoxia inducible factor 1 (HIF-1), phosphoinositide 3-kinase/AKT serine/threonine kinase (PI3K/AKT) and Toll-like receptor signaling pathways were identified as the key anti-COVID-19/PF co-occurrence pathways. Conclusion: Kaempferol is a candidate treatment for COVID-19/PF co-occurrence. The underlying mechanisms may be related to the regulation of critical targets (EGFR, SRC, MAPK3, MAPK1, MAPK8, AKT1, RELA, PIK3CA and so on) and EGFR, IL-17, TNF, HIF-1, PI3K/AKT and Toll-like receptor signaling pathways. This study contributes to guiding development of new drugs for COVID-19 and PF comorbidities.

Genotyping and In Silico Analysis of Delmarva (DMV/1639) Infectious Bronchitis Virus (IBV) Spike 1 (S1) Glycoprotein.

Genetic diversity and evolution of infectious bronchitis virus (IBV) are mainly impacted by mutations in the spike 1 (S1) gene. This study focused on whole genome sequencing of an IBV isolate (IBV/Ck/Can/2558004), which represents strains highly prevalent in Canadian commercial poultry, especially concerning features related to its S1 gene and protein sequences. Based on the phylogeny of the S1 gene, IBV/Ck/Can/2558004 belongs to the GI-17 lineage. According to S1 gene and protein pairwise alignment, IBV/Ck/Can/2558004 had 99.44-99.63% and 98.88-99.25% nucleotide (nt) and deduced amino acid (aa) identities, respectively, with five Canadian Delmarva (DMV/1639) IBVs isolated in 2019, and it also shared 96.63-97.69% and 94.78-97.20% nt and aa similarities with US DMV/1639 IBVs isolated in 2011 and 2019, respectively. Further homology analysis of aa sequences showed the existence of some aa substitutions in the hypervariable regions (HVRs) of the S1 protein of IBV/Ck/Can/2558004 compared to US DMV/1639 isolates; most of these variant aa residues have been subjected to positive selection pressure. Predictive analysis of potential N-glycosylation and phosphorylation motifs showed either loss or acquisition in the S1 glycoprotein of IBV/Ck/Can/2558004 compared to S1 of US DMV/1639 IBV. Furthermore, bioinformatic analysis showed some of the aa changes within the S1 protein of IBV/Ck/Can/2558004 have been predicted to impact the function and structure of the S1 protein, potentially leading to a lower binding affinity of the S1 protein to its relevant ligand (sialic acid). In conclusion, these findings revealed that the DMV/1639 IBV isolates are under continuous evolution among Canadian poultry.

Screening the Potential Biomarkers of COVID-19-Related Thrombosis Through Bioinformatics Analysis.

A high proportion of critically ill patients with coronavirus disease 2019 (COVID-19) experience thrombosis, and there is a strong correlation between anticoagulant therapy and the COVID-19 survival rate, indicating that common COVID-19 and thrombosis targets have potential therapeutic value for severe COVID-19.Gene expression profiling data were downloaded from Gene Expression Omnibus (GEO), and common differentially expressed genes (co-DEGs) were identified. The potential biological functions of these co-DEGs were explored by functional enrichment analysis, and protein-protein interaction (PPI) networks were constructed to elucidate the molecular mechanisms of the co-DEGs. Finally, hub genes in the co-DEG network were identified, and correlation analysis was performed.We identified 8320 upregulated genes and 7651 downregulated genes from blood samples of COVID-19 patients and 368 upregulated genes and 240 downregulated genes from blood samples of thrombosis patients. The enriched cellular component terms were mainly related to cytosolic ribosomes and ribosomal subunits. The enriched molecular function terms were mainly related to structural constituents of ribosomes and electron transfer activity. Construction of the PPI network and identification of hub genes ultimately confirmed that RPS7, IGF1R, DICER1, ERH, MCTS1, and TNPO1 were jointly upregulated hub genes, and FLNA and PXN were jointly downregulated hub genes.The identification of novel potential biomarkers provides new options for treating COVID-19-related thrombosis and reducing the rate of severe COVID-19.

SARS-CoV-2 variant strains and viral phylodynamics of ORF1a-1b genetic aspects in South America

Bioinformatics tools for online sequence analysis of variants have been used worldwide for the phylogenetic approach of SARS-Cov-2 and their variants. The purpose of this work is to contribute to the settlement of the SARS-CoV-2 genetic of the South America pandemic, presenting the ORF1a-1b evaluation. We proposed and reviewed two online bioinformatics pipelines for viral phylodynamic and phylogeographic analysis with an interactive visualization platform. The phylodynamics evaluation of South America shows a strong viral capacity to evoke immunity and an impressive multiplicity of variants in rapid expansion with mutations of potential importance, including ORF 1a-1b. They showed stately vital for infection and lethality, spreading and raising your frequency in South America from 1% to 20-30% in one year of pandemic occurrence. © 2021 IEEE.

Differences and Similarities between the Lung Transcriptomic Profiles of COVID-19, COPD, and IPF Patients: A Meta-Analysis Study of Pathophysiological Signaling Pathways.

Coronavirus disease 2019 (COVID-19) is a pandemic respiratory disease associated with high morbidity and mortality. Although many patients recover, long-term sequelae after infection have become increasingly recognized and concerning. Among other sequelae, the available data indicate that many patients who recover from COVID-19 could develop fibrotic abnormalities over time. To understand the basic pathophysiology underlying the development of long-term pulmonary fibrosis in COVID-19, as well as the higher mortality rates in patients with pre-existing lung diseases, we compared the transcriptomic fingerprints among patients with COVID-19, idiopathic pulmonary fibrosis (IPF), and chronic obstructive pulmonary disease (COPD) using interactomic analysis. Patients who died of COVID-19 shared some of the molecular biological processes triggered in patients with IPF, such as those related to immune response, airway remodeling, and wound healing, which could explain the radiological images seen in some patients after discharge. However, other aspects of this transcriptomic profile did not resemble the profile associated with irreversible fibrotic processes in IPF. Our mathematical approach instead showed that the molecular processes that were altered in COVID-19 patients more closely resembled those observed in COPD. These data indicate that patients with COPD, who have overcome COVID-19, might experience a faster decline in lung function that will undoubtedly affect global health.

Bioinformatics and System Biology Approach to Reveal the Interaction Network and the Therapeutic Implications for Non-Small Cell Lung Cancer Patients With COVID-19.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the leading cause of coronavirus disease-2019 (COVID-19), is an emerging global health crisis. Lung cancer patients are at a higher risk of COVID-19 infection. With the increasing number of non-small-cell lung cancer (NSCLC) patients with COVID-19, there is an urgent need of efficacious drugs for the treatment of COVID-19/NSCLC. Methods: Based on a comprehensive bioinformatic and systemic biological analysis, this study investigated COVID-19/NSCLC interactional hub genes, detected common pathways and molecular biomarkers, and predicted potential agents for COVID-19 and NSCLC. Results: A total of 122 COVID-19/NSCLC interactional genes and 21 interactional hub genes were identified. The enrichment analysis indicated that COVID-19 and NSCLC shared common signaling pathways, including cell cycle, viral carcinogenesis, and p53 signaling pathway. In total, 10 important transcription factors (TFs) and 44 microRNAs (miRNAs) participated in regulations of 21 interactional hub genes. In addition, 23 potential candidates were predicted for the treatment of COVID-19 and NSCLC. Conclusion: This study increased our understanding of pathophysiology and screened potential drugs for COVID-19 and NSCLC.

Review on Approved and Inprogress COVID-19 Vaccines.

The last generation of Coronavirus named COVID-19 is responsible for the recent worldwide outbreak. Concerning the widespread and quick predominance, there is a critical requirement for designing appropriate vaccines to surmount this grave problem. Correspondingly, in this revision, COVID-19 vaccines (which are being developed until March 29th, 2021) are classified into specific and non-specific categories. Specific vaccines comprise genetic-based vaccines (mRNA, DNA), vector-based, protein/recombinant protein vaccines, inactivated viruses, live-attenuated vaccines, and novel strategies including microneedle arrays (MNAs), and nanoparticles vaccines. Moreover, specific vaccines such as BCG, MRR, and a few other vaccines are considered Non-specific. What is more, according to the significance of Bioinformatic sciences in the cutting-edge vaccine design and rapid outbreak of COVID-19, herein, Bioinformatic principles including reverse vaccinology, epitopes prediction/selection and, their further applications in the design of vaccines are discussed. Last but not least, safety, challenges, advantages, and future prospects of COVID-19 vaccines are highlighted.

Mucormycosis Vaccine Design using Bioinformatic Tools

Mucormycosis is an infection that occurs due to the presence of filamentous molds. Rhizopus delemar is a major cause of mucormycosis. The infection may be due to the inoculation of spores into wounds, inhalation of the spores, or the consumption of contaminated food. Mucormycosis cases have risen during the second wave of COVID-19 infections in India. Therefore, there is an urgent requirement for a vaccine against mucormycosis. The development of these vaccines is costly and time-consuming. Different methods have been used to decrease the expense and duration of time required for the development of a vaccine. One such method is the use of bioinformatics techniques for the development of vaccines. In this paper, the screening of epitopes through the bioinformatic tools predicts that the RO3G_11882 protein of Rhizopus delemar can be used for preparing immunological constructs. Binding and molecular simulation tests predict that the nanomeric epitope VLALHNFLL has low energy minimization values which provide stability to the peptide-MHC complex and sufficient binding with MHC class II molecules. This peptide sequence needs to further go through wet lab tests, for developing a vaccine against Mucormycosis. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.