An efficient cardio vascular disease prediction using multi-scale weighted feature fusion-based convolutional neural network with residual gated recurrent unit.

The cardiovascular disease (CVD) is the dangerous disease in the world. Most of the people around the world are affected by this dangerous CVD. In under-developed countries, the prediction of CVD remains the toughest job and it takes more time and cost. Diagnosing this illness is an intricate task that has to be performed precisely to save the life span of the human. In this research, an advanced deep model-based CVD prediction and risk analysis framework is proposed to minimize the death rate of humans all around the world. The data required for the prediction of CVD is collected from online data sources. Then, the input data is preprocessed using data cleaning, data scaling, and Nan and null value removal techniques. From the preprocessed data, three sets of features are extracted. The three sets of features include deep features, Principal Component Analysis (PCA), and Support Vector Machine (SVM)-based features. A Multi-scale Weighted Feature Fusion-based Deep Structure Network (MWFF-DSN) is developed to predict CVD. This structure is composed of a Multi-scale weighted Feature fusion-based Convolutional Neural Network (CNN) with a Residual Gated Recurrent Unit (GRU). The retrieved features are given as input to MWFF-DSN, and for optimizing weights, a Modernized Plum Tree Algorithm (MPTA) is developed. From the overall analysis, the developed model has attained an accuracy of 96% and it achieves a specificity of 95.95%. The developed model takes minimum time for the CVD and it gives highly accurate detection results.

DbGTi: Thermostable trypsin inhibitor from Dioscorea bulbifera L. ground tubers: assessment of antioxidant and antibacterial properties and cytotoxicity evaluation using zebrafish model.

Oxidative stress disorders and diseases caused by drug-resistant bacteria have emerged as significant public health concerns. Plant-based medications like protease inhibitors are growing despite adverse effects therapies. Consecutively, in this study, trypsin inhibitors from Dioscorea bulbifera L. (DbGTi trypsin inhibitor) ground tubers were isolated, purified, characterized, and evaluated for their potential cytotoxicity, antibacterial, and antioxidant activities. DbGTi protein was purified by Q-Sepharose matrix, followed by trypsin inhibitory activity. The molecular weight of the DbGTi protein was found to be approximately 31 kDa by SDS-PAGE electrophoresis. The secondary structure analysis by circular dichroism (CD) spectroscopy revealed that the DbGTi protein predominantly comprises ß sheets followed by α helix. DbGTi protein showed competitive type of inhibition with Vmax = 2.1372 × 10-1 µM/min, Km = 1.1805 × 102 µM, & Ki = 8.4 × 10-9 M and was stable up to 70 °C. DbGTi protein exhibited 58 % similarity with Dioscorin protein isolated from Dioscorea alata L. as revealed by LC-MS/MS analysis. DbGTi protein showed a non-toxic effect, analyzed by MTT, Haemolytic assay and in vivo studies on zebrafish model. DbGTi protein significantly inhibited K. pneumoniae and has excellent antioxidant properties, confirmed by various antioxidant assays. The results of anti-microbial, cytotoxicity and antioxidant assays demonstrate its bioactive potential and non-toxic nature.

Differential Gene Expression Profiles Involved in the Inflammations Due to COVID-19 and Inflammatory Bowel Diseases and the Investigation of Predictive Biomarkers.

Gastrointestinal manifestations in COVID-19 were attributed to 74-86% of the hospitalised patients due to severe or prolonged pathogenesis. Though it is a respiratory disease, the impact it elicits on the gastrointestinal tract and brain are intense. Inflammatory bowel disease including Crohn's disease and ulcerative colitis are idiopathic inflammatory disorders of the gastrointestinal tract. The intrinsic mechanisms involved in gut inflammations due to a respiratory viral disease can be deciphered when the gene expression profiles of COVID-19 and IBD are compared. The current study utilises an integrated bioinformatics approach to unravel them. The publicly available gene expression profiles of colon transcriptomes infected with COVID-19, Crohn's disease and Ulcerative colitis were retrieved, integrated and analysed for the identification of differentially expressed genes. The inter-relational analysis along with gene annotation and pathway enrichment detailed the functional and metabolic pathways of the genes during normal and diseased conditions. The protein-protein interactions deduced from the STRING database and the identified hub genes predicted potential biomarker candidates for COVID-19, Crohn's disease and ulcerative colitis. The inflammatory response pathways were upregulated and enrichment of chemokine signalling, altered lipid metabolism, coagulation and complement cascades were seen in all three conditions along with impaired transport mechanisms. CXCL11, MMP10, and CFB are predicted to be overexpressed biomarkers, whilst GUCA2A, SLC13A2, CEACAM, and IGSF9 as downregulated novel biomarker candidates for colon inflammations. The three miRNAs hsa-miR-16-5p, hsa-miR-21-5p, and hsa-miR-27b-5p exhibited significant interactions with the upregulated hub genes and four long non-coding RNAs NEAT1, KCNQ1OT1, and LINC00852 capable of regulating miRNA were also predicted. This study offers significant information on the underlying molecular mechanisms of inflammatory bowel disease with identification of potential biomarkers.

Response to insecticides and underlying mechanisms of resistance in the field populations of Aedes aegypti Linnaeus (Diptera: Culicidae) in Puducherry, India.

Background & objectives: Mosquito-borne diseases are major threats to human health worldwide. Successful control of vector mosquitoes requires periodic updates on their response to the insecticides that are in use. Different classes of neurotoxic insecticides have been used in vector control programs. Ae. aegypti and Ae. albopictus are the primary vectors of dengue and have developed resistance to organophosphates and synthetic pyrethroids that are used in vector control programs. Monitoring insecticide pressure and studying the underlying mechanisms of resistance in the field populations of Aedes aegypti are important to formulate resistant management strategies for their control programs. Methods: Aedes aegypti were collected from study sites Lawspet and Abishegapakkam and F1 progeny was subject to biochemical assays to determine the enzyme activity. Insecticide susceptibility tests were conducted to determine vector susceptibility/resistance to malathion and deltamethrin. Adult dried mosquitoes were subjected to multiplex PCR to detect point mutation in the VGSC gene. Results: Insecticide susceptibility test results revealed that Aedes aegypti is resistant to malathion and incipient resistance to deltamethrin has emerged. It was observed that ß-esterase and monoxygense activity were significantly higher in Lawspet sample than the laboratory strain, whereas it was comparatively lower in Abishegapakkam sample than laboratory strain. Multiplex PCR assays showed no kdr mutation in all Ae. aegypti strains. Interpretation & conclusion: Monitoring insecticide resistance in Ae. aegypti would help the local health authorities to implement a rationalized approach for insecticide use in vector control.

Virulence, MLST analysis, and antimicrobial resistance of Campylobacter coli isolated from broiler chickens in Tamil Nadu, India.

Background: Campylobacter species are the zoonotic bacteria and the most common cause of foodborne gastroenteritis around the world. The link between human campylobacteriosis and infected poultry consumption has been well established. Aims: In this study, we aimed to isolate Campylobacter spp. from chicken and characterize them with molecular methods. Methods: Totally, 241 chicken caecal mucosal scrapings were collected from five districts of Tamil Nadu. Bacterial isolation was done by plating on blood-free Campylobacter selective medium with supplements. Campylobacter species were identified by multiplex PCR and Campylobacter coli isolates were tested for 11 virulence genes by PCR. C. coli isolates were typed based on seven housekeeping genes multilocus sequence typing (MLST) scheme. The antimicrobial susceptibility was determined by a microdilution resazurin assay. Results: The prevalence of C. coli and C. jejuni were 14.94% (36/241), and 3.32% (8/241), respectively. The virulence genes flaA, flaB, cadF, cdtA, cdtB, cdtC, ciaB, and ceuE were present in all 36 C. coli isolates, pldA and racR genes were present in 58.33% (21/36), and 16.67% (6/36) of the isolates, respectively, and dnaJ was present in only one isolate. Two novel sequence types (ST-10872, ST-11031) were found in this study. Though different STs were identified, all the STs belonged to the same clonal complex of ST-828. All 14 C. coli isolates showed 100% resistance to nalidixic acid, and higher resistance to tetracycline (92.8%), erythromycin (71.4%), clindamycin (71.4%), and azithromycin (64.2%) was noticed. All C. coli isolates were sensitive to chloramphenicol, and higher sensitivity to ciprofloxacin (78.5%), and gentamicin (71.4%) was observed. Conclusion: The present study demonstrated that C. coli is more prevalent in broilers than C. jejuni in Tamil Nadu. The presence of C. jejuni and C. coli in chicken caecal samples from the slaughterhouse are indicative of the possibility of public health hazards.

Meta-analysis of the microbial biomarkers in the gut-lung crosstalk in COVID-19, community-acquired pneumonia and Clostridium difficile infections.

Respiratory infections are the leading causes of mortality and the current pandemic COVID-19 is one such trauma that imposed catastrophic devastation to the health and economy of the world. Unravelling the correlations and interplay of the human microbiota in the gut-lung axis would offer incredible solutions to the underlying mystery of the disease progression. The study compared the microbiota profiles of six samples namely healthy gut, healthy lung, COVID-19 infected gut, COVID-19 infected lungs, Clostridium difficile infected gut and community-acquired pneumonia infected lungs. The metagenome data sets were processed, normalized, classified and the rarefaction curves were plotted. The microbial biomarkers for COVID-19 infections were identified as the abundance of Candida and Escherichia in lungs with Ruminococcus in the gut. Candida and Staphylococcus could play a vital role as putative prognostic biomarkers of community-acquired pneumonia whereas abundance of Faecalibacterium and Clostridium is associated with the C. difficile infections in gut. A machine learning random forest classifier applied to the data sets efficiently classified the biomarkers. The study offers an extensive and incredible understanding of the existence of gut-lung axis during dysbiosis of two anatomically different organs.

A Deep Learning Framework for Earlier Prediction of Diabetic Retinopathy from Fundus Photographs.

Diabetic patients can also be identified immediately utilizing retinopathy photos, but it is a challenging task. The blood veins visible in fundus photographs are used in several disease diagnosis approaches. We sought to replicate the findings published in implementation and verification of a deep learning approach for diabetic retinopathy identification in retinal fundus pictures. To address this issue, the suggested investigative study uses recurrent neural networks (RNN) to retrieve characteristics from deep networks. As a result, using computational approaches to identify certain disorders automatically might be a fantastic solution. We developed and tested several iterations of a deep learning framework to forecast the progression of diabetic retinopathy in diabetic individuals who have undergone teleretinal diabetic retinopathy assessment in a basic healthcare environment. A collection of one-field or three-field colour fundus pictures served as the input for both iterations. Utilizing the proposed DRNN methodology, advanced identification of the diabetic state was performed utilizing HE detected in an eye's blood vessel. This research demonstrates the difficulties in duplicating deep learning approach findings, as well as the necessity for more reproduction and replication research to verify deep learning techniques, particularly in the field of healthcare picture processing. This development investigates the utilization of several other Deep Neural Network Frameworks on photographs from the dataset after they have been treated to suitable image computation methods such as local average colour subtraction to assist in highlighting the germane characteristics from a fundoscopy, thus, also enhancing the identification and assessment procedure of diabetic retinopathy and serving as a skilled guidelines framework for practitioners all over the globe.

Mosquito Diversity in an Experimental Township in Tamil Nadu, India.

To glean more information on mosquito diversity and distribution in Auroville, a cross-sectional study was carried out by mapping the distribution of water bodies and habitats supporting immature stages on the one hand and the distribution of water bodies/habitats supporting mosquito immature stages on the other. A satellite image covering an area of 8.08 km2 was overlaid with a grid of 500 × 500 m. Fifteen modules were selected and the area of each module served as the sampling site for the entomological survey. Adult and larval stages were sampled. Diversity indices were analyzed to compare mosquito diversity. Rarefaction estimations were used to compare abundance and richness of the mosquito species between different zones. In total, 750 mosquito larvae and 84 resting adults were sampled. Eighteen species of mosquitoes belonging to 11 subgenera and 7 genera were documented. Genera included Aedes (Johann Wilhelm Meigen 1818, Diptera, Culicidae), Anopheles (Johann Wilhelm Meigen 1818, Diptera, Culicidae), Armigeres (Theobald 1901, Diptera, Culicidae), Culex (Carl Linnaeus 1758, Diptera, Culicidae), Lutzia (Theobald 1903, Diptera, Culicidae), and Mimomyia (Theobald 1903, Diptera, Culicidae). Of the 18 mosquito species identified, 8 species are new records for Auroville. The Alpha (α) biodiversity indices show that the mosquito fauna is diverse (S = 18; DMg = 2.732 [95% CI: 2.732-2.732]). The Shannon-Weiner (H' = 2.199 [95% CI: 2.133-2.276]) and Simpson indices (λ = 0.8619 [95% CI: 0.8496-0.8723]) measured species richness, evenness, and dominance. The values of these indices suggest high species richness, evenness, and dominance. Prevailing conditions can provide suitable environment for establishment of different mosquito species in this ecosystem. Given the sociodemographic characteristics of this area, research on mosquito diversity and risk of vector-borne diseases will be of great use.

Isolation and characterization of an iridoid, Arbortristoside-C from Nyctanthes arbor-tristis Linn., a potential drug candidate for diabetes targeting α-glucosidase.

Many parts of the plant Nyctanthes arbor-tristis Linn. are widely investigated for their biological properties. Purified Arbortristosides from seeds are reported as anticancer, anti-leishmania, anti-inflammatory, anti-allergic, immunomodulatory and antiviral. The present study elaborates on the isolation, structural and functional characterization of Arbortristoside-C and its inhibition properties against alpha-glucosidase, an important target for diabetes mellitus. Arbortristoside-C is purified from seeds of N. arbor-tristis by extraction using polar fractionation and chromatographic techniques. Arbortristoside-C has been characterized using Ultra Violet (UV), Mass (MS), Infra-Red (IR) and Nuclear Magnetic Resonance (NMR). Inhibition kinetics and Isothermal Titration Calorimetry (ITC) were used for activity and binding characteristics of acarbose and Arbortristoside-C using in-house purified α-glucosidase from Bos taurus. Modeling, docking and structural comparison with acarbose bound structure revealing the similar binding characteristics of Arbortristoside-C which include interaction with catalytic acid/base Aspartic acid residue. Cytotoxicity assay revealed that 100 µg/ml is the maximum toxic-free concentration of Arbortristoside-C. The purified Arbortristoside-C showed inhibition against mammalian α-glucosidase, suggesting its potential to treat Diabetes mellitus.

Computational gene expression profiling in the exploration of biomarkers, non-coding functional RNAs and drug perturbagens for COVID-19.

The coronavirus disease, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a global health crisis that is being endured with an increased alarm of transmission each day. Though the pandemic has activated innumerable research attention to decipher an antidote, fundamental understanding of the molecular mechanisms is necessary to halt the disease progression. The study focused on comparison of the COVID-19 infected lung tissue gene expression datasets -GSE155241 and GSE150316 with the GEO2R-limma package. The significant up- and downregulated genes were annotated. Further evaluation of the enriched pathways, transcription factors, kinases, noncoding RNAs and drug perturbations revealed the significant molecular mechanisms of the host response. The results revealed a surge in mitochondrial respiration, cytokines, neurodegenerative mechanisms and deprived oxygen, iron, copper, and glucose transport. Hijack of ubiquitination by SARS-CoV-2, hox gene differentiation, histone modification, and miRNA biogenesis were the notable molecular mechanisms inferred. Long non-coding RNAs such as C058791.1, TTTY15 and TPTEP1 were predicted to be efficient in regulating the disease mechanisms. Drugs-F-1566-0341, Digoxin, Proscillaridin and Linifanib that reverse the gene expression signatures were predicted from drug perturbations analysis. The binding efficiency and interaction of proscillaridin and digoxin as obtained from the molecular docking studies confirmed their therapeutic potential. Two overlapping upregulated genes MDH1, SGCE and one downregulated gene PFKFB3 were appraised as potential biomarkers candidates. The upregulation of PGM5, ISLR and ANK2 as measured from their expressions in normal lungs affirmed their possible prognostic biomarker competence. The study explored significant insights for better diagnosis, and therapeutic options for COVID-19. Communicated by Ramaswamy H. Sarma.

Nivar cyclonic impacts on mollusk habitat destruction in Parangipettai, southeast coast of Tamil Nadu, India: A case study.

Tropical storms form in the Bay of Bengal every year during the pre-monsoon season, affecting the coastal communities and the marine ecosystem. On November 25, 2020, severe cyclone Nivar impacted the southeast coast of Tamil Nadu, causing massive damage to marine benthic species. The study found that the Nivar cyclone's high velocity wind impacted tidal currents and damaged sediment compartments. This phenomenonhas immensely affected the benthic communities of Mudasalodai, Parangipettai, Puthupettai, Samiyarpettai, and Kumarapettai. Post-Nivar cyclone observations revealed massive bivalve and gastropod mortality. The two molluscan species lost their habitats due to the tremendous cyclone effect. More than 1 lakh Mactra violacea were emigrated from Parangipettai and 5 lakh Turritella acutangula and T. attenuata were emigrated from Samiyarpettai. Thus, the Nivar cyclone severely damaged mollusk habitats along India's southeast coast. The severe cyclonic storm Nivar disrupted the southeast coast of India, with losses amounting to over $600 million.

Structural, functional, resistome and pathogenicity profiling of the Cooum river.

The microbial community's structure and functions determine the health, quality, and anthropogenic conditions of the river ecosystems. The presence of Bacteria such as Arcobacter spp, Escherichia spp, and Campylobacters spp, have been shown to reflect the poor water quality of rivers. Apprehension of the microbial community in polluted water bodies is significant because it affects human health and the environment. Culture-independent metagenomic and metatranscriptomic approaches employed in the current study of the Cooum river unraveled the taxonomic classification of diverse microbes, including archaea, bacteria, viruses, and phages. The presence of abundant Macellibacteroides fermentans, Arcobacter bivolvorium, Arcobacter butzleri, Methanothrix soenhngeii, and Bacteroides graminisolvens were noted. Viruses and phages like Caudovirales, Human mastadenovirus C, Siphoviridae, Escherichia phage, Erwinia phage, Synechoccus phage, and Vibrio phage were relatively predominant. Various metabolic pathways like methane, sulfur, and nitrogen metabolism adopted by the microbiome confer dangerous gases. Mechanisms such as secretory systems, signal transduction, Chemotaxis, quorum sensing, transportation of chemicals and ions were significantly enriched. The microbes expressed antimicrobial resistance mechanisms as identified from the genes encoding beta-lactamase enzymes and aminoglycoside phosphotransferase enzymes. Metal resistance mechanisms against copper, tellurium, chromium, and cadmium were plentiful. Presence of human pathogens interactions with Yersinia pestis, Campylobacter jejuni, Escherichia coli, Helicobacter pylori, and Francisella tularensis subsp. tularensis suggested the possibilities of transmission of pathogenesis to humans. The current study is the first to apprehend the detailed microbiome composition of one of the highly polluted rivers in South India. The study elaborated the microbiome's structure, functions, and metabolic potential at a specific site of the polluted river.

Metabolic and molecular modelling of zebrafish gut biome to unravel antimicrobial peptides through metagenomics.

Recently efforts have been taken for unravelling mysteries between host-microbe interactions in gut microbiome studies of model organisms through metagenomics. Co-existence and the co-evolution of the microorganisms is the significant cause of the growing antimicrobial menace. There needs a novel approach to develop potential antimicrobials with capabilities to act directly on the resistant microbes with reduced side effects. One such is to tap them from the natural resources, preferably the gut of the most closely related animal model. In this study, we employed metagenomics approaches to identify the large taxonomic genomes of the zebra fish gut. About 256 antimicrobial peptides were identified using gene ontology predictions from Macrel and Pubseed servers. Upon the property predictions, the top 10 antimicrobial peptides were screened based on their action against many resistant bacterial species, including Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, E. coli, and Bacillus cereus. Metabolic modelling and flux balance analysis (FBA) were computed to conclude the antibiotic such as tetracycline, cephalosporins, puromycin, neomycin biosynthesis pathways were adopted by the microbiome as protection strategies. Molecular modelling strategies, including molecular docking and dynamics, were performed to estimate the antimicrobial peptides' binding against the target-putative nucleic acid binding lipoprotein and confirm stable binding. One specific antimicrobial peptide with the sequence "MPPYLHEIQPHTASNCQTELVIKL" showed promising results with 53% hydrophobic residues and a net charge +2.5, significant for the development of antimicrobial peptides. The said peptide also showed promising interactions with the target protein and expressed stable binding with docking energy of -429.34 kcal/mol and the average root mean square deviation of 1 A0. The study is a novel approach focusing on tapping out potential antimicrobial peptides to be developed against most resistant bacterial species.

From genomes to molecular dynamics - A bottom up approach in extrication of SARS CoV-2 main protease inhibitors.

The recent pandemic Coronavirus disease-19 outbreak had traumatized global countries since its origin in late December 2019. Though the virus originated in China, it has spread rapidly across the world due its firmly established community transmission. To successfully tackle the spread and further infection, there needs a clear multidimensional understanding of the molecular mechanisms. Henceforth, 942 viral genome sequences were analysed to predict the core genomes crucial in virus life cycle. Additionally, 35 small interfering RNA transcripts were predicted that can target specifically the viral core proteins and reduce pathogenesis. The crystal structure of Covid-19 main protease-6LU7 was chosen as an attractive target due to the factors that there were fewer mutations and whose structure had significant identity to the annotated protein sequence of the core genome. Drug repurposing of both recruiting and non recruiting drugs was carried out through molecular docking procedures to recognize bitolterol as a good inhibitor of Covid-19 protease. The study was extended further to screen antiviral phytocompounds through quantitative structure activity relationship and molecular docking to identify davidigenin, from licorice as the best novel lead with good interactions and binding energy. The docking of the best compounds in all three categories was validated with molecular dynamics simulations which implied stable binding of the drug and lead molecule. Though the studies need clinical evaluations, the results are suggestive of curbing the pandemic.

A Child with Enlarged Extremities - A Case of Macrodystrophia Lipomatosa.

Macrodystrophia lipomatosa (ML) is a rare, non-hereditary, developmental anomaly that occurs because of the progressive proliferation of all mesenchymal elements of single or multiple digits or entire extremity, with a disproportionate increase in fibroadipose tissue. Commonly one or few digits of an extremity will be enlarged and present as macrodactyly or as enlarged limb. Lower limb involvement is more common and frequently unilateral. The diagnosis of ML is made by accurate clinical assessment and imaging modalities, such as plain X-ray, computed tomography scan, magnetic resonance imaging, and confirmed by histopathological study. In this case, we described a 10-year-old child who was brought to us with enlarged upper and lower extremities and was diagnosed as a case of ML with the help of clinico-radiological studies and presented here because of focal gigantism involving all four limbs, which is very rare.

Clinical and Radiologic Findings of Acute Necrotizing Encephalopathy in Young Adults.

Acute necrotizing encephalopathy after an acute febrile illness, although initially described exclusively in the pediatric age group, has been recently shown to have an adult onset as well. In this study, we describe 10 patients (16 years of age or older) with acute necrotizing encephalopathy. In our study, bilateral thalamic involvement with the trilaminar pattern of diffusion restriction on MR imaging was the predominant finding seen in all of the patients reviewed. Ancillary findings of cerebral white matter, brain stem, and cerebellum involvement with sparing of the basal ganglia were also noted. A poorer outcome was observed in patients with a higher degree of thalamic involvement. The cause of an underlying infection was identified in 4 patients (dengue in 3 and influenza in 1). Overall, a sizeable portion of young adults with acute necrotizing encephalopathy have shown a poorer outcome, with dengue being an important underlying trigger in an endemic region.

Structure-based drug designing towards the identification of potential anti-viral for COVID-19 by targeting endoribonuclease NSP15.

The world is facing health and economic havoc due to the Corona Virus Disease-2019 (COVID-19) pandemic. Given the number of affected people and the mortality rate, the virus is undoubtedly a serious threat to humanity. By analogy with earlier reports about Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) - viruses, the novel Coronavirus' replication mechanism is likely well understood. The structure of an endoribonuclease (NSP15) of SARS-CoV-2 was reported recently. This enzyme is expected to play a crucial role in replication. In this work, attempts were made to identify inhibitors of this enzyme. To achieve the goal, high throughput in silico screening and molecular docking procedures were performed. From an Enamine database of a billion compounds, 3978 compounds with potential antiviral activity were selected for screening and induced fit docking that funneled down to eight compounds with good docking score and docking energy. Detailed analysis of non-covalent interactions at the active site and the apparent match of the molecule with the shape of the binding pocket were assessed. All the compounds show significant interactions for tight binding. Since all the compounds are synthetic with favorable drug-like properties, these may be considered for immediate optimization and downstream applications.

Molecular modelling analysis of T219A mutant envelope protein revealed novel virulence enhancing factors in Dengue virus isolated from Kerala state, India.

Dengue virus (DENV) is an emerging health threat and its envelope glycoprotein E, is involved in the anchoring and fusion mechanisms. Anchoring followed by conformational changes of E-protein are responsible for the fusion and entry of DENV into host. The variation in the conformation of the E-protein due to mutations, results in its altered binding with antibodies (Abs) and also its receptors. This leads to failure of neutralization of DENV and enhance the infection. In our earlier studies we have identified T219A mutation in the E-protein of DENV and the present study is focused on the impact of this mutation on the conformation of E-protein and also its binding variation with Abs and Fc-γ receptor. A comparative molecular modelling studies of wild type and T219A mutant E-proteins revealed that, the mutation induced several conformational variations in the E-protein and resulted in the variable binding orientation with altered affinities. Further, the mutation was also observed to enhance the fusion mechanism by Fc-γ receptors that mediate the efficient entry of DENV into host cell through altered membrane fusion mechanism. Such conformational variations of E-protein could be the responsible factors for enhanced virulence of DENV infections.