An integrated comparative genomics, subtractive proteomics and immunoinformatics framework for the rational design of a Pan-Salmonella multi-epitope vaccine.

Salmonella infections pose a significant global public health concern due to the substantial expenses associated with monitoring, preventing, and treating the infection. In this study, we explored the core proteome of Salmonella to design a multi-epitope vaccine through Subtractive Proteomics and immunoinformatics approaches. A total of 2395 core proteins were curated from 30 different isolates of Salmonella (strain NZ CP014051 was taken as reference). Utilizing the subtractive proteomics approach on the Salmonella core proteome, Curlin major subunit A (CsgA) was selected as the vaccine candidate. csgA is a conserved gene that is related to biofilm formation. Immunodominant B and T cell epitopes from CsgA were predicted using numerous immunoinformatics tools. T lymphocyte epitopes had adequate population coverage and their corresponding MHC alleles showed significant binding scores after peptide-protein based molecular docking. Afterward, a multi-epitope vaccine was constructed with peptide linkers and Human Beta Defensin-2 (as an adjuvant). The vaccine could be highly antigenic, non-toxic, non-allergic, and have suitable physicochemical properties. Additionally, Molecular Dynamics Simulation and Immune Simulation demonstrated that the vaccine can bind with Toll Like Receptor 4 and elicit a robust immune response. Using in vitro, in vivo, and clinical trials, our findings could yield a Pan-Salmonella vaccine that might provide protection against various Salmonella species.

AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer's from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew's correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.

Gut microbiome composition reveals the distinctiveness between the Bengali people and the Indigenous ethnicities in Bangladesh.

Ethnicity has a significant role in shaping the composition of the gut microbiome, which has implications in human physiology. This study intends to investigate the gut microbiome of Bengali people as well as several indigenous ethnicities (Chakma, Marma, Khyang, and Tripura) residing in the Chittagong Hill Tracts areas of Bangladesh. Following fecal sample collection from each population, part of the bacterial 16 s rRNA gene was amplified and sequenced using Illumina NovaSeq platform. Our findings indicated that Bangladeshi gut microbiota have a distinct diversity profile when compared to other countries. We also found out that Bangladeshi indigenous communities had a higher Firmicutes to Bacteroidetes ratio than the Bengali population. The investigation revealed an unclassified bacterium that was differentially abundant in Bengali samples while the genus Alistipes was found to be prevalent in Chakma samples. Further research on these bacteria might help understand diseases associated with these populations. Also, the current small sample-sized pilot study hindered the comprehensive understanding of the gut microbial diversity of the Bangladeshi population and its potential health implications. However, our study will help establish a basic understanding of the gut microbiome of the Bangladeshi population.

Identification of repurposable drug targets in Mycoplasma pneumoniae using subtractive genomics, molecular docking and dynamics simulation.

Mycoplasma pneumoniae is a significant causative agent of community-acquired pneumonia, causing acute inflammation in the upper and lower respiratory tract as well as extrapulmonary syndromes. In particular, the elderly and infants are at greater risk of developing severe, life-threatening pneumonia caused by M. pneumoniae. Yet, the global increase in antimicrobial resistance against antibiotics for the treatment of M. pneumoniae infection highlights the urgent need to explore novel drug targets. To this end, bioinformatics approaches, such as subtractive genomics, can be employed to identify specific metabolic pathways and essential proteins unique to the pathogen that could be potential targets for new drugs. In this study, we implemented a subtractive genomics approach to identify 61 metabolic pathways and 42 essential proteins that are unique to M. pneumoniae. A subsequent screening in the DrugBank database revealed three druggable proteins with similarity to FDA-approved small-molecule drugs, and finally, the compound CHEBI:97093 was identified as a promising novel putative drug target. These findings can provide crucial insights for the development of highly effective drugs that selectively inhibit the pathogen-specific metabolic pathways, leading to better management and treatment of M. pneumoniae infections.

Impact of highly deleterious non-synonymous polymorphisms on GRIN2A protein's structure and function.

GRIN2A is a gene that encodes NMDA receptors found in the central nervous system and plays a pivotal role in excitatory synaptic transmission, plasticity and excitotoxicity in the mammalian central nervous system. Changes in this gene have been associated with a spectrum of neurodevelopmental disorders such as epilepsy. Previous studies on GRIN2A suggest that non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein's structure and function. To gain a better understanding of the impact of potentially deleterious variants of GRIN2A, a range of bioinformatics tools were employed in this study. Out of 1320 nsSNPs retrieved from the NCBI database, initially 16 were predicted as deleterious by 9 tools. Further assessment of their domain association, conservation profile, homology models, interatomic interaction, and Molecular Dynamic Simulation revealed that the variant I463S is likely to be the most deleterious for the structure and function of the protein. Despite the limitations of computational algorithms, our analyses have provided insights that can be a valuable resource for further in vitro and in vivo research on GRIN2A-associated diseases.

High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference.

Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants.Communicated by Ramaswamy H. Sarma.

Pharmacoinformatics and molecular dynamics simulation approach to identify anti-diarrheal potentials of Centella asiatica (L.) Urb. against Vibrio cholerae.

Vibrio cholerae, the etiological agent of cholera, causes dehydration and severe diarrhea with the production of cholera toxin. Due to the acquired antibiotic resistance, V. cholerae has drawn attention to the establishment of novel medications to counteract the virulence and viability of the pathogen. Centella asiatica is a medicinal herb native to Bangladesh that has a wide range of medicinal and ethnobotanical applications including anti-bacterial properties. In the present investigation, a total of 25 bioactive phytochemicals of C. asiatica have been screened virtually through molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analyses, and molecular dynamics simulation. Our results revealed four lead compounds as Viridiflorol (-8.7 Kcal/mol), Luteolin (-8.1 Kcal/mol), Quercetin (-8.0 Kcal/mol) and, Geranyl acetate (-7.1 Kcal/mol) against V. cholerae Toxin co-regulated pilus virulence regulatory protein (ToxT). All the lead compounds have been found to possess favorable pharmacokinetic, pharmacodynamics, and molecular dynamics properties. Toxicity analysis revealed satisfactory results with no major side effects. Molecular dynamics simulation was performed for 100 ns that revealed noteworthy conformational stability and structural compactness for all the lead compounds, especially for Quercetin. Target class prediction unveiled enzymes in most of the cases and some experimental and investigational drugs were found as structurally similar analogs of the lead compounds. These findings could aid in the development of novel therapeutics targeting Cholera disease and we strongly recommend in vitro trials of our experimental findings.Communicated by Ramaswamy H. Sarma.

Virtual screening reveals liquiritigenin as a broad-spectrum inhibitor of SARS-CoV-2 variants of concern: an in silico study.

The SARS-CoV-2 has severely impacted the lives of people worldwide. Global concern is on the rise due to a large number of unexpected mutations in the viral genome, resulting in new variants. Nature-based bioactive phytochemicals hold great promise as inhibitors against pathogenic viruses. The current study was aimed at evaluating some bioactive antiviral phytochemicals against SARS-CoV-2 variants of concern. A total of 46 phytochemicals were screened against the pathogenic spike protein of Alpha, Beta, Delta, Gamma, and Omicron variants. In addition to molecular docking, screening for favorable pharmacokinetic and pharmacodynamic properties such as absorption, distribution, metabolism, excretion, and toxicity was undertaken. For each of the aforementioned five SARS-CoV-2 variants of concern, a 100 ns molecular dynamics simulation was run to assess the stability of the complexes between their respective spike protein receptor-binding domain and the best-selected compound. From our current investigation, the natural compound liquiritigenin turned out to be the most promising potential lead compound against almost all the variants. These findings could pave the way for the development of effective medications against SARS-CoV-2 variants. However, in vivo trials in future studies are necessary for further validation of our results.Communicated by Ramaswamy H. Sarma.

Proteome-Based Investigation Identified Potential Drug Repurposable Small Molecules Against Monkeypox Disease.

Monkeypox Virus (MPXV), the causative agent of Monkeypox (MPX) disease, is an emerging zoonotic pathogen spreading in different endemic and non-endemic nations and creating outbreaks. MPX treatment mainly includes Cidofovir and Tecovirimat but they have several side effects and solely depending on these drugs may promote the emergence of drug-resistant variants. Hence, new drugs are required to control the spread of the disease. In this study, we explored the MPXV proteome to suggest repurposable drugs. DrugBank screening revealed drugs such as Brinzolamide, Dorzolamide, Methazolamide, Zidovudine, Gemcitabine, Hydroxyurea, Fludarabine, and Tecovirimat as controls. Structural analogs of these compounds were extracted from ChEMBL Database. After Molecular docking and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET)-based screening, we identified Zidovudine (binding affinity-5.9 kcal/mol) and a Harmala alkaloid (2S,4R)-4-(9H-Pyrido[3,4-b]indol-1-yl)-1,2,4-butanetriol (binding affinity - 6.6 kcal/mol) against L2R receptor (Thymidine Kinase). Moreover, Fludarabine (binding affinity - 6.4 kcal/mol) and 5'-Dehydroadenosine (binding affinity - 6.4 kcal/mol) can strongly interact with the I4L receptor (Ribonucleotide reductase large subunit R1). Molecular Dynamics (MD) simulations suggest all of these compounds can change the C-alpha backbone, residue mobility, compactness, and solvent accessible surface area of L2R and I4L. Our results strongly suggest that these drug repurposing small molecules are worth exploring in vivo and in vitro for clinical applications.

Exploration of Streptococcus core genome to reveal druggable targets and novel therapeutics against S. pneumoniae.

Streptococcus pneumoniae (S. pneumoniae), the major etiological agent of community-acquired pneumonia (CAP) contributes significantly to the global burden of infectious diseases which is getting resistant day by day. Nearly 30% of the S. pneumoniae genomes encode hypothetical proteins (HPs), and better understandings of these HPs in virulence and pathogenicity plausibly decipher new treatments. Some of the HPs are present across many Streptococcus species, systematic assessment of these unexplored HPs will disclose prospective drug targets. In this study, through a stringent bioinformatics analysis of the core genome and proteome of S. pneumoniae PCS8235, we identified and analyzed 28 HPs that are common in many Streptococcus species and might have a potential role in the virulence or pathogenesis of the bacteria. Functional annotations of the proteins were conducted based on the physicochemical properties, subcellular localization, virulence prediction, protein-protein interactions, and identification of essential genes, to find potentially druggable proteins among 28 HPs. The majority of the HPs are involved in bacterial transcription and translation. Besides, some of them were homologs of enzymes, binding proteins, transporters, and regulators. Protein-protein interactions revealed HP PCS8235_RS05845 made the highest interactions with other HPs and also has TRP structural motif along with virulent and pathogenic properties indicating it has critical cellular functions and might go under unconventional protein secretions. The second highest interacting protein HP PCS8235_RS02595 interacts with the Regulator of chromosomal segregation (RocS) which participates in chromosome segregation and nucleoid protection in S. pneumoniae. In this interacting network, 54% of protein members have virulent properties and 40% contain pathogenic properties. Among them, most of these proteins circulate in the cytoplasmic area and have hydrophilic properties. Finally, molecular docking and dynamics simulation demonstrated that the antimalarial drug Artenimol can act as a drug repurposing candidate against HP PCS8235_RS 04650 of S. pneumoniae. Hence, the present study could aid in drugs against S. pneumoniae.

Wave-wise comparative genomic study for revealing the complete scenario and dynamic nature of COVID-19 pandemic in Bangladesh.

As the COVID-19 pandemic continues to ravage across the globe and take millions of lives and like many parts of the world, the second wave of the pandemic hit Bangladesh, this study aimed at understanding its causative agent, SARS-CoV-2 at the genomic and proteomic level and provide precious insights about the pathogenesis, evolution, strengths and weaknesses of the virus. As of Mid-June 2021, over 1500 SARS-CoV-2 genomesequences have been deposited in the GISAID database from Bangladesh which were extracted and categorized into two waves. By analyzing these genome sequences, it was discovered that the wave-2 samples had a significantly greater average rate of mutation/sample (30.79%) than the wave-1 samples (12.32%). Wave-2 samples also had a higher frequency of deletion, and transversion events. During the first wave, the GR clade was the most predominant but it was replaced by the GH clade in the latter wave. The B.1.1.25 variant showed the highest frequency in wave-1 while in case of wave-2, the B.1.351.3 variant, was the most common one. A notable presence of the delta variant, which is currently at the center of concern, was also observed. Comparison of the Spike protein found in the reference and the 3 most common lineages found in Bangladesh namely, B.1.1.7, B.1.351, B.1.617 in terms of their ability to form stable complexes with ACE2 receptor revealed that B.1.617 had the potential to be more transmissible than others. Importantly, no indigenous variants have been detected so far which implies that the successful prevention of import of foreign variants can diminish the outbreak in the country.

Novel mutations in NSP-1 and PLPro of SARS-CoV-2 NIB-1 genome mount for effective therapeutics.

BACKGROUND: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), is rapidly acquiring new mutations. Analysis of these mutations is necessary for gaining knowledge regarding different aspects of therapeutic development. Previously, we have reported a Sanger method-based genome sequence of a viral isolate named SARS-CoV-2 NIB-1, circulating in Bangladesh. The genome has four novel non-synonymous mutations in V121D, V843F, A889V, and G1691C positions. RESULTS: Using different computational tools, we have found V121D substitution has the potential to destabilize the non-structural protein-1 (NSP-1). NSP-1 inactivates the type-1 interferon-induced antiviral system. Hence, this mutant could be a basis of attenuated vaccines against SARS-CoV-2. V843F, A889V, and G1691C are all located in nonstructural protein-3 (NSP-3). G1691C can decrease the flexibility of the protein. V843F and A889V might change the binding pattern and efficacy of SARS-CoV-2 papain-like protease (PLPro) inhibitor GRL0617. V843F substitution in PLPro was the most prevalent mutation in the clinical samples. This mutation showed a reduced affinity for interferon-stimulated gene-15 protein (ISG-15) and might have an impact on innate immunity and viral spread. However, V843F+A889V double mutant exhibited the same binding affinity as wild type PLPro. A possible reason behind this phenomenon can be that V843F is a conserved residue of PLPro which damaged the protease structure, but A889V, a less conserved residue, presumably neutralized that damage. CONCLUSIONS: Mutants of NSP-1 could provide attenuated vaccines against coronavirus. Also, these mutations of PLPro might be targeted to develop better anti-SARS therapeutics. We hope our study will help to get better insides during the development of attenuated vaccine and PLPro inhibitors.

Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach.

Coronavirus disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has become an immense threat to global public health. In this study, we performed complete genome sequencing of a SARS-CoV-2 isolate. More than 67,000 genome sequences were further inspected from Global Initiative on Sharing All Influenza Data (GISAID). Using several in silico techniques, we proposed prospective therapeutics against this virus. Through meticulous analysis, several conserved and therapeutically suitable regions of SARS-CoV-2 such as RNA-dependent RNA polymerase (RdRp), Spike (S) and Membrane glycoprotein (M) coding genes were selected. Both S and M were chosen for the development of a chimeric vaccine that can generate memory B and T cells. siRNAs were also designed for S and M gene silencing. Moreover, six new drug candidates were suggested that might inhibit the activity of RdRp. Since SARS-CoV-2 and SARS-CoV-1 have 82.30% sequence identity, a Gene Expression Omnibus (GEO) dataset of Severe Acute Respiratory Syndrome (SARS) patients were analyzed. In this analysis, 13 immunoregulatory genes were found that can be used to develop type 1 interferon (IFN) based therapy. The proposed vaccine, siRNAs, drugs and IFN based analysis of this study will accelerate the development of new treatments.

Insight of druggable cannabinoids against estrogen receptor ß in breast cancer.

Breast cancer (BC) is the second most prevalent cancer worldwide. Estrogen receptor beta (ERß) is an essential protein of breast cells to suppress estrogen-induced uncontrolled proliferation. Thus, small molecules that can modulate and enhance ERß expression would be an effective agent to suppress BC development. Studies showed that cannabinoid (CB), specifically delta-9-tetrahydrocannabinol (Del9THC), can increase the expression of ERß and inhibits BC cell proliferation. In this study, less psychoactive and structurally similar analogs of Del9THC were chosen as drug candidates and ERß was targeted as a therapeutic receptor. Delta-8-tetrahydrocannabinol (Del8THC) and delta-4-isotetrahydrocannabinol (Del4isoTHC) were the drug candidates selected on the basis of literature reports, absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, medicinal chemistry profile, and physicochemical features. Molecular docking simulations were carried out to determine ligand receptor interactions and binding affinity based on free binding energy. To get a better drug, the structural modification was done on Del8THC and generated a new CB analog called Cannabinoid A. Finally, molecular interaction analysis revealed that two CBs and one of their analog interact with the active site residues of ERß. Therefore, this study revealed a new way to discover novel drug(s) for BC patients.Communicated by Ramaswamy H. Sarma.

Microsecond molecular dynamics simulations revealed the inhibitory potency of amiloride analogs against SARS-CoV-2 E viroporin.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes small envelope protein (E) that plays a major role in viral assembly, release, pathogenesis, and host inflammation. Previous studies demonstrated that pyrazine ring containing amiloride analogs inhibit this protein in different types of coronavirus including SARS-CoV-1 small envelope protein E (SARS-CoV-1 E). SARS-CoV-1 E has 93.42% sequence identity with SARS-CoV-2 E and shared a conserved domain NS3/small envelope protein (NS3_envE). Amiloride analog hexamethylene amiloride (HMA) can inhibit SARS-CoV-1 E. Therefore, we performed molecular docking and dynamics simulations to explore whether amiloride analogs are effective in inhibiting SARS-CoV-2 E. To do so, SARS-CoV-1 E and SARS-CoV-2 E proteins were taken as receptors while HMA and 3-amino-5-(azepan-1-yl)-N-(diaminomethylidene)-6-pyrimidin-5-ylpyrazine-2-carboxamide (3A5NP2C) were selected as ligands. Molecular docking simulation showed higher binding affinity scores of HMA and 3A5NP2C for SARS-CoV-2 E than SARS-CoV-1 E. Moreover, HMA and 3A5NP2C engaged more amino acids in SARS-CoV-2 E. Molecular dynamics simulation for 1 µs (1,000 ns) revealed that these ligands could alter the native structure of the proteins and their flexibility. Our study suggests that suitable amiloride analogs might yield a prospective drug against coronavirus disease 2019.

Whole genome sequencing for revealing the point mutations of SARS-CoV-2 genome in Bangladeshi isolates and their structural effects on viral proteins.

Coronavirus disease-19 (COVID-19) caused by SARS-CoV-2 has already killed more than one million people worldwide. Since novel coronavirus is a new virus, mining its genome sequence is of crucial importance for drug/vaccine(s) development. Whole genome sequencing is a helpful tool in identifying genetic changes that occur in a virus when it spreads through the population. In this study, we performed complete genome sequencing of SARS-CoV-2 to unveil the genomic variation and indel, if present. We discovered thirteen (13) mutations in Orf1ab, S and N gene where seven (7) of them turned out to be novel mutations from our sequenced isolate. Besides, we found one (1) insertion and seven (7) deletions from the indel analysis among the 323 Bangladeshi isolates. However, the indel did not show any effect on proteins. Our energy minimization analysis showed both stabilizing and destabilizing impact on viral proteins depending on the mutation. Interestingly, all the variants were located in the binding site of the proteins. Furthermore, drug binding analysis revealed marked difference in interacting residues in mutants when compared to the wild type. Our analysis also suggested that eleven (11) mutations could exert damaging effects on their corresponding protein structures.