Computational designing of a novel subunit vaccine for human cytomegalovirus by employing the immunoinformatics framework.

Human cytomegalovirus (HCMV) is a widespread virus that can cause serious and irreversible neurological damage in newborns and even death in children who do not have the access to much-needed medications. While some vaccines and drugs are found to be effective against HCMV, their extended use has given rise to dose-limiting toxicities and the development of drug-resistant mutants among patients. Despite half a century's worth of research, the lack of a licensed HCMV vaccine heightens the need to develop newer antiviral therapies and vaccine candidates with improved effectiveness and reduced side effects. In this study, the immunoinformatics approach was utilized to design a potential polyvalent epitope-based vaccine effective against the four virulent strains of HCMV. The vaccine was constructed using seven CD8+ cytotoxic T lymphocytes epitopes, nine CD4+ helper T lymphocyte epitopes, and twelve linear B-cell lymphocyte epitopes that were predicted to be antigenic, non-allergenic, non-toxic, fully conserved, and non-human homologous. Subsequently, molecular docking study, protein-protein interaction analysis, molecular dynamics simulation (including the root mean square fluctuation (RMSF) and root mean square deviation (RMSD)), and immune simulation study rendered promising results assuring the vaccine to be stable, safe, and effective. Finally, in silico cloning was conducted to develop an efficient mass production strategy of the vaccine. However, further in vitro and in vivo research studies on the proposed vaccine are required to confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Immunoinformatic Design of a Multivalent Peptide Vaccine Against Mucormycosis: Targeting FTR1 Protein of Major Causative Fungi.

Mucormycosis is a potentially fatal illness that arises in immunocompromised people due to diabetic ketoacidosis, neutropenia, organ transplantation, and elevated serum levels of accessible iron. The sudden spread of mucormycosis in COVID-19 patients engendered massive concern worldwide. Comorbidities including diabetes, cancer, steroid-based medications, long-term ventilation, and increased ferritin serum concentration in COVID-19 patients trigger favorable fungi growth that in turn effectuate mucormycosis. The necessity of FTR1 gene-encoded ferrous permease for host iron acquisition by fungi has been found in different studies recently. Thus, targeting the transit component could be a potential solution. Unfortunately, no appropriate antifungal vaccine has been constructed as of yet. To date, mucormycosis has been treated with antiviral therapy and surgical treatment only. Thus, in this study, the FTR1 protein has been targeted to design a convenient and novel epitope-based vaccine with the help of immunoinformatics against four different virulent fungal species. Furthermore, the vaccine was constructed using 8 CTL, 2 HTL, and 1 LBL epitopes that were found to be highly antigenic, non-allergenic, non-toxic, and fully conserved among the fungi under consideration. The vaccine has very reassuring stability due to its high pI value of 9.97, conclusive of a basic range. The vaccine was then subjected to molecular docking, molecular dynamics, and immune simulation studies to confirm the biological environment's safety, efficacy, and stability. The vaccine constructs were found to be safe in addition to being effective. Finally, we used in-silico cloning to develop an effective strategy for vaccine mass production. The designed vaccine will be a potential therapeutic not only to control mucormycosis in COVID-19 patients but also be effective in general mucormycosis events. However, further in vitro, and in vivo testing is needed to confirm the vaccine's safety and efficacy in controlling fungal infections. If successful, this vaccine could provide a low-cost and effective method of preventing the spread of mucormycosis worldwide.

Age and gender-related differences in quality of life of Bangladeshi patients with Down Syndrome: A cross-sectional study.

Currently available screening instruments for evaluation of individuals with intellectual disabilities do not capture all the complications associated with Down Syndrome (DS). Here, we examined age and gender-specific variability revolving around major challenges related to ophthalmologic and auditory health, social integration, daily life, and behavioral problems in 468 (age: 2-84 years) individuals with DS living in all eight divisions of Bangladesh. More than half of the children presented with significant difficulty in walking or other targeted movements compared with 37.9% of adolescents (p = 0.03). Nearly 70% of children exhibited communication difficulties, particularly revolving around the understanding of speech, comprehending or learning tasks or new materials, and in expressing thoughts in words or behaviors (p = 0.003-0.006). Uncontrolled urination was frequent and predominantly found among children (p = 0.04). No significant differences were present in females vs. males except for concern about physical appearance (females: 58.5% vs. males: 47.5%; p = 0.02). The severity of DS was associated with intellectual performance, communication difficulties, and self-sufficiency (i.e., uncontrolled micturition or bowel movements) but not with psychotic, ophthalmologic, auditory, or motor skills-related problems. Increased awareness of DS phenotypic profiles among professionals and caregivers can foster earlier detection and counselling and help formulate appropriate interventions to reduce long-term sequelae and enhance cognitive and behavioral developmental outcomes.

Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV).

OBJECTIVES: The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options. METHODS: In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2. RESULTS: The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine. CONCLUSION: If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria.

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Molecular genetics of surfactin and its effects on different sub-populations of Bacillus subtilis.

Surfactin is a biosurfactant produced by Bacillus subtilis. The srfA operon, Sfp gene, and two quorum sensing systems are required for its production. The master regulator spo0A also plays an indispensable role in proper surfactin synthesis. Upon production, surfactin itself acts as a signaling molecule and triggers the activation of Spo0A gene which in turn regulates cell differentiation. Interestingly, surfactin producing cells are immune to the action of surfactin but trigger other cells to differentiate into non-motile cells, matrix producing cells, cannibals, and spores. In case of competent cell differentiation, comS, which resides within the srfA operon, is co-expressed along with surfactin and plays a vital role in competent cell differentiation in response to quorum sensing signal. Surfactin inhibits the motility of certain cell subpopulations, although it helps the non-motile cells to swarm. Thus, surfactin plays significant roles in the differentiation of different subpopulations of specialized cell types of B. subtilis.

Influence on attitudes and lifestyle due to lockdown amidst COVID-19 pandemic: a perception-based analysis among Bangladeshi residents.

BACKGROUND: Countrywide lockdown or stay-at-home order has been implemented to slow down the transmission of emergent coronavirus. However, the influence on attitudes and lifestyle due to lockdown amidst the coronavirus disease 2019 (COVID-19) pandemic has been poorly understood. The present study aimed to investigate the influence on attitudes and lifestyle due to lockdown amidst the COVID-19 pandemic among Bangladeshi residents. METHODS: A cross-sectional survey carried out involving 1635 community dwellers across eight divisions in Bangladesh conducted from April 15, 2020 to May 10, 2020. A structured questionnaire incorporating socio-demographic, attitudes towards lockdown and adverse lifestyle amidst lockdown measures was employed to collect data using the Google Forms. Multiple regression analyses were executed to determine the associated factors of positive attitudes towards lockdown and adverse lifestyle. RESULTS: The mean scores of attitudes towards lockdown were 67.9 (SD = 8.4) out of 85 with an overall correct rate (positive attitudes) of 79.9%; whereas the mean scores of adverse lifestyle amidst lockdown were 16.1 (SD = 4.8) out of 34 with an overall rate of 47.4%. The factors associated with more positive attitudes towards lockdown included being female, divorced, higher educated, and students. Conversely, being male, having no formal education, and rural residence were associated factors of adverse lifestyle amidst the COVID-19 pandemic. CONCLUSIONS: The findings reflect how the COVID-19 lockdown has preciously impacted the attitudes, and lifestyle of Bangladeshi citizens, which will contribute to promoting appropriate measures during a subsequent zonal or complete lockdown.

In silico assessment of EpCAM transcriptional expression and determination of the prognostic biomarker for human lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

Epithelial cell adhesion molecule (EpCAM) is a transmembrane glycoprotein which is involved in cell signaling, proliferation, maturation, and movement, all of which are crucial for the proper development of cells and tissues. Cleavage of the EpCAM protein leads to the up-regulation of c-myc, e-fabp, and cyclins A and E which promote tumorigenesis. EpCAM can act as potential diagnostic and prognostic biomarker for different types of cancers as it is also found to be expressed in epithelia and epithelial-derived neoplasms. Hence, we aimed to analyze the EpCAM gene expression and any associated feedback in the patients of two major types of lung cancer (LC) i.e., lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), based on the publicly available online databases. In this study, server-based gene expression analysis represents the up-regulation of EpCAM in both LUAD and LUSC subtypes as compared to the corresponding normal tissues. Besides, the histological sections revealed the over-expression of EpCAM protein in cancerous tissues by depicting strong staining signals. Furthermore, mutation analysis suggested missense as the predominant type of mutation both in LUAD and LUSC in the EpCAM gene. A significant correlation (P-value < 0.05) between the higher EpCAM expression and lower patient survival was also found in this study. Finally, the co-expressed genes were identified with their ontological features and signaling pathways associated in LC development. The overall study suggests EpCAM to be a significant biomarker for human LC prognosis.

Genome Sequences of Two Novel Coronavirus (SARS-CoV-2) Isolates from Dhaka, Bangladesh.

This study reports the genome sequences of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains detected in the nasopharyngeal swab specimens of two coronavirus disease 2019 (COVID-19) patients from Dhaka, Bangladesh.

Analysis of plant-derived phytochemicals as anti-cancer agents targeting cyclin dependent kinase-2, human topoisomerase IIa and vascular endothelial growth factor receptor-2.

Cancer is caused by a variety of pathways, involving numerous types of enzymes. Among them three enzymes i.e. Cyclin-dependent kinase-2 (CDK-2), Human topoisomerase IIα, and Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) are three of the most common enzymes that are involved in the cancer development. Although many chemical drugs are already available in the market for cancer treatment, plant sources are known to contain a wide variety of agents that are proved to possess potential anticancer activity. In this experiment, total thirty phytochemicals were analyzed against the mentioned three enzymes using different tools of bioinformatics and in silico biology like molecular docking study, drug likeness property experiment, ADME/T test, PASS prediction, and P450 site of metabolism prediction as well as DFT calculation to determine the three best ligands among them that have the capability to inhibit the mentioned enzymes. From the experiment, Epigallocatechin gallate was found to be the best ligand to inhibit CDK-2, Daidzein showed the best inhibitory activities towards the Human topoisomerase IIα, and Quercetin was predicted to be the best agent against VEGFR-2. They were also predicted to be quite safe and effective agents to treat cancer. However, more in vivo and in vitro analyses are required to finally confirm their safety and efficacy in this regard.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses.

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.

Designing novel epitope-based polyvalent vaccines against herpes simplex virus-1 and 2 exploiting the immunoinformatics approach.

Herpes Simplex Virus (HSV) is a highly infectious virus that is responsible for various types of orofacial and genital infections. Two types of HSV exist i.e. HSV-1 and HSV-2, that are infecting millions of people around the world. However, no satisfactory treatment or counter-measure has yet been discovered to fight against the HSV infections. In this study, three possible polyvalent subunit vaccines against multiple strains of HSV-1 and HSV-2, targeting the envelope glycoproteins- E, B, and D, were designed using the tools of reverse vaccinology and immunoinformatics. The highly antigenic, non-allergenic, non-toxic, non-homolog (to the human proteome), and 100% conserved epitopes across the selected strains and species (eight epitopes from each of the CTL, HTL, and BCL epitope groups), were selected for vaccine construction. These designed vaccines are expected to be effective against the selected viral types simultaneously (as a polyvalent vaccine), without producing any unwanted adverse reaction within the body. Finally, from the three vaccine constructs, one best vaccine was determined by molecular docking analysis and thereafter, the MD simulation and immune simulation studies of the best vaccine construct also yielded satisfactory results, pointing towards quite good stability of the complex. Finally, in silico cloning was performed for analyzing the effective mass production strategy of the best vaccine construct. However, wet lab-based study should be conducted on the suggested vaccines for validating their potentiality, safety, and efficacy.Communicated by Ramaswamy H. Sarma.

Women's Knowledge, Attitude, and Perceptions Toward COVID-19 in Lower-Middle-Income Countries: A Representative Cross-Sectional Study in Bangladesh.

The coronavirus disease 2019 (COVID-19) is a global health emergency of unprecedented proportions. Countries around the world have taken extraordinary steps to control the disease. The preventive measures face challenges in low and lower middle income countries (LICs and LMICs). Especially the marginalized communities, e.g., women are the hardest hit of the virus. This study took Bangladesh as a representative LMIC and aimed to determine the level of knowledge, perception, attitude, and preparedness related to COVID-19 among the adult women in the country. Using a comprehensive questionnaire, we channeled a cross-sectional study among adult women in Bangladesh. Participant's self-reported data on the knowledge, attitude, and preparedness were tabulated and analyzed using suitable statistical tools. A total of 1,869 adults from 61 districts of Bangladesh took part in this study. Ninety seven percentage of the participants claimed to have heard of COVID-19 before it arrived in Bangladesh. Regarding the general knowledge related to COVID-19's causal agent, symptoms, and treatment, the positive response rate was nearly 80%, with a mean of 10.68 ± 1.72. Younger and educated women had better knowledge levels compared to the older and lower-educated participants (p < 0.01). More efforts are required to educate women with older age and lower socioeconomic status. An overall positive attitude and perception were observed, although a significant proportion of the participants opined that the Government's efforts in controlling the outbreak were not adequate. Although the participants had a satisfactory level of knowledge and a positive attitude in adopting preventive measures against COVID-19, greater efforts are needed from the healthcare authorities and Government.

Engineering a novel subunit vaccine against SARS-CoV-2 by exploring immunoinformatics approach.

As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible countermeasures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for developing potential vaccines; however, most of them are proved to possess negative consequences. Therefore, in this study, immunoinformatics methods were exploited to design a novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog, and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vitro and in vivo studies are required on the predicted vaccine to finally validate its safety and efficacy.

Immunoinformatics-guided designing of epitope-based subunit vaccines against the SARS Coronavirus-2 (SARS-CoV-2).

SARS Coronavirus-2 (SARS-CoV-2) pandemic has become a global issue which has raised the concern of scientific community to design and discover a counter-measure against this deadly virus. So far, the pandemic has caused the death of hundreds of thousands of people upon infection and spreading. To date, no effective vaccine is available which can combat the infection caused by this virus. Therefore, this study was conducted to design possible epitope-based subunit vaccines against the SARS-CoV-2 virus using the approaches of reverse vaccinology and immunoinformatics. Upon continual computational experimentation, three possible vaccine constructs were designed and one vaccine construct was selected as the best vaccine based on molecular docking study which is supposed to effectively act against the SARS-CoV-2. Thereafter, the molecular dynamics simulation and in silico codon adaptation experiments were carried out in order to check biological stability and find effective mass production strategy of the selected vaccine. This study should contribute to uphold the present efforts of the researches to secure a definitive preventative measure against this lethal disease.

Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus.

Ebola virus is a highly pathogenic RNA virus that causes the Ebola haemorrhagic fever in human. This virus is considered as one of the dangerous viruses in the world with very high mortality rate. To date, no epitope-based subunit vaccine has yet been discovered to fight against Ebola although the outbreaks of this deadly virus took many lives in the past. In this study, approaches of reverse vaccinology were utilized in combination with different tools of immunoinformatics to design subunit vaccines against Ebola virus strain Mayinga-76. Three potential antigenic proteins of this virus i.e., matrix protein VP40, envelope glycoprotein and nucleoprotein were selected to construct the subunit vaccine. The MHC class-I, MHC class-II and B-cell epitopes were determined initially and after some robust analysis i.e., antigenicity, allergenicity, toxicity, conservancy and molecular docking study, EV-1, EV-2 and EV-3 were constructed as three potential vaccine constructs. These vaccine constructs are also expected to be effective on few other strains of Ebola virus since the highly conserved epitopes were used for vaccine construction. Thereafter, molecular docking study was conducted on these vaccines and EV-1 emerged as the best vaccine construct. Afterward, molecular dynamics simulation study revealed the good performances and stability of the intended vaccine protein. Finally, codon adaptation and in silico cloning were carried out to design a possible plasmid (pET-19b plasmid vector was used) for large scale production of the EV-1 vaccine. However, further in vitro and in vivo studies might be required on the predicted vaccines for final validation.

Curcumin analogs as the inhibitors of TLR4 pathway in inflammation and their drug like potentialities: a computer-based study.

Toll-like receptor 4 (TLR4) pathway is one of the major pathways that mediate the inflammation in human body. There are different anti-inflammatory drugs available in the market which specifically act on different signaling proteins of TLR4 pathway but they do have few side effects and other limitations for intended use in human body. In this study, Curcumin and its different analogs have been analyzed as the inhibitors of signaling proteins, i.e. Cycloxygenase-2 (COX-2), inhibitor of kappaß kinase (IKK) and TANK binding kinase-1 (TBK-1) of TLR4 pathway using different computational tools. Initially, three compounds were selected for respective target based on free binding energy among which different compounds were reported to have better binding affinity than commercially available drug (control). Upon continuous computational exploration with induced fit docking (IFD), 6-Gingerol, Yakuchinone A and Yakuchinone B were identified as the best inhibitors of COX-2, IKK, and TBK-1 respectively. Then their drug-like potentialities were analyzed in different experiments where they were also predicted to perform well. Hopefully, this study will uphold the efforts of researchers to identify anti-inflammatory drugs from natural sources.