Machine Learning Analysis of National Vaccination Schedules and Rates of Compliance Reveals Correlation with COVID19 Mortality

We questioned whether previous vaccination histories, as reflected by the national vaccination schedules and compliance rates, might correlate with mortality rates from COVID-19. Using a machine learning algorithm, we aligned the WHO data on national vaccinations schedules and compliance rates with national mortality rates, as published daily by official health authorities and posted on the WHO website. Vaccination schedule and the national rates of compliance were significantly associated with national mortality rates. The five most influential vaccines were Rubella, inactivated Polio, DTP (Diphtheria, Tetanus, Pertussis) and the Pneumococcal vaccine. These vaccinations are more likely to be associated with younger generations whereas mortality is reported mainly in older people. Our findings suggest that further studies exploring the possible mechanism(s) underlying this association with vaccination may provide important information in dealing with an ongoing pandemic. Supporting our conclusions, a recent computational study predicted an epitope similarity between the viruses causing COVID_19, measles, and rubella, the latter two covered by the triple vaccine MMR identified in our studies. This suggests that childhood vaccinations contribute to the differential clinical presentation of COVID_19 in young and older populations. Some recent publication also hypothesized that there would be a non-specific protective effect for the MMR vaccine

A Molecular Docking and Pharmacokinetic Prediction of Thiazolidine-2, 4-dione Derivatives: Toward Novel Therapeutic Targets for Type-2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a leading endocrine disorder that affects millions of people worldwide. It is characterized by hyperglycemia and high insulin resistance. The commonly prescribed oral therapeutic for insulin resistance in T2DM is Thiazolidine-2, 4-diones (TZDs). TZDs are a class of oral hypoglycemic agents that act on Peroxisome proliferator activating receptor-γ (PPAR-γ) receptors and are mainly expressed in the adipose tissues. In this work, we derive novel classes of TZDs and predict the nature of structural affinity using docking studies against the PPAR-γ.

Combined gene expression analysis in HIV Associated Dementia, Alzheimer’s disease and Parkinson’s disease- An in-silico approach

Human immunodeficiency virus (HIV) Type 1 infection predominantly affects the immune system. Nevertheless, scientific studies have proven its association with the Central Nervous system (CNS) causing several neurological complications leading to HIV Associated Dementia (HAD). HAD is characterized by a progressive, disabling decline in essential CNS functions such as cognition, motor control and behavior. These are the general characteristics of the most common Neuro degenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). The genetics of AD and PD is widely studied and clinical studies have shown cohesion in the pathology of HAD, AD and PD. Analysing the concurrent expression patterns of large number of genes amongst these related diseases will aid in establishing correlations between the genes and their functions.We have analysed the gene expression datasets of HAD, AD and PD from GEO database to determine the overlapping genes and transcription factors involved. The datasets were normalized using R-Bioconductor, and statistical analysis was performed to identify the significant genes using limma and related packages in R. Although substantial amount of common proteins among HAD and other Neuro degenerative diseases have been previously reported, our findings can help in expanding the pool of target genes and further enhancing the knowledge about the convergent pathways among HAD, AD and PD. These common markers identified will provide insights into parallel pathways of disease mechanisms and further assist in the understanding of progression of HAD pathogenesis

ATPase Domain of Heat Shock protein 70—isoform 2—(Hsp70-2) and their role in activating the adaptive immune response: An in silico approach

A lot of molecules play fundamental roles in neoplasic processes and cancer. Heat shock proteins may enhance these pathologies and favor the protumoral milieu. However, a look at the literature tells us that these molecules intervene in both to promote or attack cancer cells. In the case of breast cancer is known that Hsp70 (isoform 2) improve its establishment and progression in the patient, and is possible that the ATPase domain of Hsp70-2 favors this disease. Thus, is relevant to know if this molecular region has immunogenic activity as well as which epitopes are essential to stimulate immune cells, and whether could induce the attack of the tumor mass. In this aim, the immunogenicity of ATPase domain of Hsp70-2 was studied in silico. The results suggest that the majority of the molecule had immunogenic epitopes that boosts the immune response through activation of B cells and T cells. However, in vitro synthesis and in vivo experimental studies to evaluate the efficacy of this therapeutic candidate are required to ensure safety in people

Revisiting Prostate Cancer in India: A Genomic View

In the recent past, there has been a rise in Prostate Cancer (PCa) in Asia, particularly India.  Although systematic reviews on PCa have dealt on the genetics, genomics and the environmental influence in causal of PCa, no predictive analytics in comparing the PCa from Caucasian, American to Asian population was attempted. In this review article, we have attempted to elaborate this aspect of PCa and deliberated on challenges related to next generation sequencing methods of PCa’s manifestation when compared to the west

Modelling and Computational Sequence Analysis of a Bacteriocin Isolated from Bacillus licheniformis strain BTHT8

Bacteriocins are ribosomally synthesized antimicrobial peptides displaying different mode of action. Non pathogenic Bacillus licheniformis are usually associated with plants and produce several bacteriocins. This work looks at drug designing strategies using protein modelling and bioinformatics tools.  In this study computational modelling and docking studies were carried out using the 13 amino acid sequence of a previously characterized thermostable bacteriocin, BL8 produced by B. licheniformis strain BTHT8. These analyses enabled the understanding of the structure of BL8 protein domain, which was noted to belong to alpha + beta protein fold family. In addition, the docking study predicted that BL8 has properties of angiotensin-converting enzyme (ACE) inhibitor. 

Combined gene expression analysis in HIV Associated Dementia, Alzheimer’s disease and Parkinson’s disease- An in-silico approach

Human immunodeficiency virus (HIV) Type 1 infection predominantly affects the immune system. Nevertheless, scientific studies have proven its association with the Central Nervous system (CNS) causing several neurological complications leading to HIV Associated Dementia (HAD). HAD is characterized by a progressive, disabling decline in essential CNS functions such as cognition, motor control and behavior. These are the general characteristics of the most common Neuro degenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). The genetics of AD and PD is widely studied and clinical studies have shown cohesion in the pathology of HAD, AD and PD. Analysing the concurrent expression patterns of large number of genes amongst these related diseases will aid in establishing correlations between the genes and their functions.We have analysed the gene expression datasets of HAD, AD and PD from GEO database to determine the overlapping genes and transcription factors involved. The datasets were normalized using R-Bioconductor, and statistical analysis was performed to identify the significant genes using limma and related packages in R. Although substantial amount of common proteins among HAD and other Neuro degenerative diseases have been previously reported, our findings can help in expanding the pool of target genes and further enhancing the knowledge about the convergent pathways among HAD, AD and PD. These common markers identified will provide insights into parallel pathways of disease mechanisms and further assist in the understanding of progression of HAD pathogenesis

FrameOUT and FrameOUTDB: A web based application and repository for the identification and analysis of frameshift mutations

Frameshift, one of the three classes of recoding, leads to waste of energy, resources and activity of biosynthetic machinery. In addition, some peptides, probably cycotoxic synthesized after frameshifts, results in diseases and disorders like muscular dystrophies, lysosomal storage disorders, and cancer. Hidden Stop Codons that occur naturally in coding sequences among all organisms, are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frame-shift events. Hidden stop codons and their association with numerous diseases. These codons are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frame-shift events. There are lots of appearances of hidden stops in mitochondrial genomes and we tried to study this putative event in mitochondrial genomes of vertebrates. To reduce this gap, this work presents an algorithmic web based tool to study hidden stops in frame-shifted translation for vertebrate mitochondrial genomes through respective genetic code system. FrameOUT (FO), an algorithmic web based application, predicts mutations in a user input sequence, be it a diseased or a normal sequence by implementation of Hidden Markov Model. FODB is a collection of all available Frameshift events and their association with various diseases

Meta-Analysis Of Brain And Central Nervous System Microarray Datasets

Brain and CNS cancer are rare in comparison to other types of cancer. Currently there are no effective therapies for their treatment. In this study, meta-analysis of microarray datasets of Brain and CNS cancer was done to obtain significantly upregulated genes with increased statistical power and generalizability.  A total of 130 significantly up-regulated genes were obtained. Some of the genes found during analysis have not yet been associated with this cancer. Different biological networks were created and analyzed using the significantly up-regulated genes as input. For each network, the most significant pathways have also been identified computationally.