Multiple Protein Profiler 1.0 (MPP): A Webserver for Predicting and Visualizing Physiochemical Properties of Proteins at the Proteome Level.

Determining the physicochemical properties of a protein can reveal important insights in their structure, biological functions, stability, and interactions with other molecules. Although tools for computing properties of proteins already existed, we could not find a comprehensive tool that enables the calculations of multiple properties for multiple input proteins on the proteome level at once. Facing this limitation, we developed Multiple Protein Profiler (MPP) 1.0 as an integrated tool that allows the profiling of 12 individual properties of multiple proteins in a significant manner. MPP provides a tabular and graphic visualization of properties of multiple proteins. The tool is freely accessible at https://mproteinprofiler.microbiologyandimmunology.dal.ca/ .

Immuno-informatics study identifies conserved T cell epitopes in non-structural proteins of Bluetongue virus serotypes: formulation of a computationally optimized next-generation broad-spectrum multi-epitope vaccine.

Introduction: Bluetongue (BT) poses a significant threat to the livestock industry, affecting various animal species and resulting in substantial economic losses. The existence of numerous BT virus (BTV) serotypes has hindered control efforts, highlighting the need for broad-spectrum vaccines. Methodology: In this study, we evaluated the conserved amino acid sequences within key non-structural (NS) proteins of BTV and identified numerous highly conserved murine- and bovine-specific MHC class I-restricted (MHC-I) CD8+ and MHC-II-restricted CD4+ epitopes. We then screened these conserved epitopes for antigenicity, allergenicity, toxicity, and solubility. Using these epitopes, we developed in silico-based broad-spectrum multiepitope vaccines with Toll-like receptor (TLR-4) agonists. The predicted proinflammatory cytokine response was assessed in silico using the C-IMMSIM server. Structural modeling and refinement were achieved using Robetta and GalaxyWEB servers. Finally, we assessed the stability of the docking complexes through extensive 100-nanosecond molecular dynamics simulations before considering the vaccines for codon optimization and in silico cloning. Results: We found many epitopes that meet these criteria within NS1 and NS2 proteins and developed in silico broad-spectrum vaccines. The immune simulation studies revealed that these vaccines induce high levels of IFN-γ and IL-2 in the vaccinated groups. Protein-protein docking analysis demonstrated promising epitopes with strong binding affinities to TLR-4. The docked complexes were stable, with minimal Root Mean Square Deviation and Root Mean Square Fluctuation values. Finally, the in silico-cloned plasmids have high % of GC content with > 0.8 codon adaptation index, suggesting they are suitable for expressing the protein vaccines in prokaryotic system. Discussion: These next-generation vaccine designs are promising and warrant further investigation in wet lab experiments to assess their immunogenicity, safety, and efficacy for practical application in livestock. Our findings offer a robust framework for developing a comprehensive, broad-spectrum vaccine, potentially revolutionizing BT control and prevention strategies in the livestock industry.

Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.

A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pathways that can lead to widespread inflammation, tissue damage, and organ failure. A dysregulated immune response can manifest as changes in differentiated immune cell populations and concentrations of circulating biomarkers. To propose an early diagnostic system that enables differentiation and identifies the severity of immune-dysregulated syndromes, we built an artificial intelligence tool that uses input data from single-cell RNA sequencing. In our results, single-cell transcriptomics successfully distinguished between mild and severe sepsis and COVID-19 infections. Moreover, by interpreting the decision patterns of our classification system, we identified that different immune cells upregulating or downregulating the expression of the genes CD3, CD14, CD16, FOSB, S100A12, and TCRɣδ can accurately differentiate between different degrees of infection. Our research has identified genes of significance that effectively distinguish between infections, offering promising prospects as diagnostic markers and providing potential targets for therapeutic intervention.

Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach.

BACKGROUND: Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases. METHODS: The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level. RESULTS: Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses. CONCLUSIONS: Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Complete Genome Sequencing, Annotation, and Mutational Profiling of the Novel Clade I Human Mpox Virus, Kamituga Strain.

INTRODUCTION: Human Mpox (formerly monkeypox) infection is an emerging zoonotic disease caused by the Mpox virus (MPXV). We describe the complete genome annotation, phylogeny, and mutational profile of a novel, sustained Clade I Mpox outbreak in the city of Kamituga in Eastern Democratic Republic of the Congo (DRC). METHODOLOGY: A cross-sectional, observational, cohort study was performed among patients of all ages admitted to the Kamituga Hospital with Mpox infection symptoms between late September 2023 and late January 2024. DNA was isolated from Mpox swabbed lesions and sequenced followed by phylogenetic analysis, genome annotation, and mutational profiling. RESULTS: We describe an ongoing Clade I Mpox outbreak in the city of Kamituga, South Kivu Province, Democratic Republic of Congo. Whole-genome sequencing of the viral RNA samples revealed, on average, 201.5 snps, 28 insertions, 81 deletions, 2 indels, 312.5 total variants, 158.3 amino acid changes, 81.66 intergenic variants, 72.16 synonymous mutations, 106 missense variants, 41.16 frameshift variants, and 3.33 inframe deletions across six samples. By assigning mutations at the proteome level for Kamituga MPXV sequences, we observed that seven proteins, namely, C9L (OPG047), I4L (OPG080), L6R (OPG105), A17L (OPG143), A25R (OPG151), A28L (OPG153), and B21R (OPG210) have emerged as hot spot mutations based on the consensuses inframe deletions, frameshift variants, synonymous variants, and amino acids substitutions. Based on the outcome of the annotation, we found a deletion of the D14L (OPG032) gene in all six samples. Following phylogenetic analysis and whole genome assembly, we determined that this cluster of Mpox infections is genetically distinct from previously reported Clade I outbreaks, and thus propose that the Kamituga Mpox outbreak represents a novel subgroup (subgroup VI) of Clade I MPXV. CONCLUSIONS: Here we report the complete viral genome for the ongoing Clade I Mpox Kamituga outbreak for the first time. This outbreak presents a distinct mutational profile from previously sequenced Clade I MPXV oubtreaks, suggesting that this cluster of infections is a novel subgroup (we term this subgroup VI). These findings underscore the need for ongoing vigilance and continued sequencing of novel Mpox threats in endemic regions.

PoxiPred: An Artificial-Intelligence-Based Method for the Prediction of Potential Antigens and Epitopes to Accelerate Vaccine Development Efforts against Poxviruses.

Poxviridae is a family of large, complex, enveloped, and double-stranded DNA viruses. The members of this family are ubiquitous and well known to cause contagious diseases in humans and other types of animals as well. Taxonomically, the poxviridae family is classified into two subfamilies, namely Chordopoxvirinae (affecting vertebrates) and Entomopoxvirinae (affecting insects). The members of the Chordopoxvirinae subfamily are further divided into 18 genera based on the genome architecture and evolutionary relationship. Of these 18 genera, four genera, namely Molluscipoxvirus, Orthopoxvirus, Parapoxvirus, and Yatapoxvirus, are known for infecting humans. Some of the popular members of poxviridae are variola virus, vaccine virus, Mpox (formerly known as monkeypox), cowpox, etc. There is still a pressing demand for the development of effective vaccines against poxviruses. Integrated immunoinformatics and artificial-intelligence (AI)-based methods have emerged as important approaches to design multi-epitope vaccines against contagious emerging infectious diseases. Despite significant progress in immunoinformatics and AI-based techniques, limited methods are available to predict the epitopes. In this study, we have proposed a unique method to predict the potential antigens and T-cell epitopes for multiple poxviruses. With PoxiPred, we developed an AI-based tool that was trained and tested with the antigens and epitopes of poxviruses. Our tool was able to locate 3191 antigen proteins from 25 distinct poxviruses. From these antigenic proteins, PoxiPred redundantly located up to five epitopes per protein, resulting in 16,817 potential T-cell epitopes which were mostly (i.e., 92%) predicted as being reactive to CD8+ T-cells. PoxiPred is able to, on a single run, identify antigens and T-cell epitopes for poxviruses with one single input, i.e., the proteome file of any poxvirus.

CDBProm: the Comprehensive Directory of Bacterial Promoters.

The decreasing cost of whole genome sequencing has produced high volumes of genomic information that require annotation. The experimental identification of promoter sequences, pivotal for regulating gene expression, is a laborious and cost-prohibitive task. To expedite this, we introduce the Comprehensive Directory of Bacterial Promoters (CDBProm), a directory of in-silico predicted bacterial promoter sequences. We first identified that an Extreme Gradient Boosting (XGBoost) algorithm would distinguish promoters from random downstream regions with an accuracy of 87%. To capture distinctive promoter signals, we generated a second XGBoost classifier trained on the instances misclassified in our first classifier. The predictor of CDBProm is then fed with over 55 million upstream regions from more than 6000 bacterial genomes. Upon finding potential promoter sequences in upstream regions, each promoter is mapped to the genomic data of the organism, linking the predicted promoter with its coding DNA sequence, and identifying the function of the gene regulated by the promoter. The collection of bacterial promoters available in CDBProm enables the quantitative analysis of a plethora of bacterial promoters. Our collection with over 24 million promoters is publicly available at https://aw.iimas.unam.mx/cdbprom/.

Inhibition potential of natural flavonoids against selected omicron (B.1.19) mutations in the spike receptor binding domain of SARS-CoV-2: a molecular modeling approach.

The omicron (B.1.19) variant of contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is considered a variant of concern (VOC) due to its increased transmissibility and highly infectious nature. The spike receptor-binding domain (RBD) is a hotspot of mutations and is regarded as a prominent target for screening drug candidates owing to its crucial role in viral entry and immune evasion. To date, no effective therapy or antivirals have been reported; therefore, there is an urgent need for rapid screening of antivirals. An extensive molecular modelling study has been performed with the primary goal to assess the inhibition potential of natural flavonoids as inhibitors against RBD from a manually curated library. Out of 40 natural flavonoids, five natural flavonoids, namely tomentin A (-8.7 kcal/mol), tomentin C (-8.6 kcal/mol), hyperoside (-8.4 kcal/mol), catechin gallate (-8.3 kcal/mol), and corylifol A (-8.2 kcal/mol), have been considered as the top-ranked compounds based on their binding affinity and molecular interaction profiling. The state-of-the-art molecular dynamics (MD) simulations of these top-ranked compounds in complex with RBD exhibited stable dynamics and structural compactness patterns on 200 nanoseconds. Additionally, complexes of these molecules demonstrated favorable free binding energies and affirmed the docking and simulation results. Moreover, the post-simulation validation of these interacted flavonoids using principal component analysis (PCA) revealed stable interaction patterns with RBD. The integrated results suggest that tomentin A, tomentin C, hyperoside, catechin gallate, and corylifol A might be effective against the emerging variants of SARS-CoV-2 and should be further evaluated using in-vitro and in-vivo experiments.Communicated by Ramaswamy H. Sarma.

Drug repurposing for Mpox: Discovery of small molecules as potential inhibitors against DNA-dependent RNA polymerase using molecular modeling approach.

Mpox (formerly Monkeypox), a zoonotic illness caused by the Mpox virus, belongs to the Orthopoxvirus genus in the family Poxviridae. To design and develop effective antiviral therapeutics against DNA viruses, the DNA-dependent RNA polymerase (DdRp) of poxviruses has emerged as a promising drug target. In the present study, we modeled the three-dimensional (3D) structure of DdRp using a template-based homology approach. After modeling, virtual screening was performed to probe the molecular interactions between 1755 Food and Drug Administration-approved small molecule drugs (≤500 molecular weight) and the DdRp of Mpox. Based on the binding affinity and molecular interaction patterns, five drugs, lumacaftor (-11.7 kcal/mol), conivaptan (-11.7 kcal/mol), betulinic acid (-11.6 kcal/mol), fluspirilene (-11.3 kcal/mol), and imatinib (-11.2 kcal/mol), have been ranked as the top drug compounds interacting with Mpox DdRp. Complexes of these shortlisted drugs with DdRp were further evaluated using state-of-the-art all-atoms molecular dynamics (MD) simulations on 200 nanoseconds followed by principal component analysis (PCA). MD simulations and PCA results revealed highly stable interactions of these small drugs with DdRp. After due validation in wet-lab using available in vitro and in vivo experiments, these repurposed drugs can be further utilized for the treatment of contagious Mpox virus. The outcome of this study may establish a solid foundation to screen repurposed and natural compounds as potential antiviral therapeutics against different highly pathogenic viruses.