Showing papers by "North Eastern Hill University published in 2020"

Design of a Peptide-Based Subunit Vaccine against Novel Coronavirus SARS-CoV-2

Abstract: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide. In the absence of any antiviral or immunomodulatory therapies, the disease is spreading at an alarming rate. A possibility of a resurgence of COVID-19 in places where lockdowns have already worked is also developing. Thus, for controlling COVID-19, vaccines may be a better option than drugs. An mRNA-based anti-COVID-19 candidate vaccine has entered a phase 1 clinical trial. However, its efficacy and potency have to be evaluated and validated. Since vaccines have high failure rates, as an alternative, we are presenting a new, designed multi-peptide subunit-based epitope vaccine against COVID-19. The recombinant vaccine construct comprises an adjuvant, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes joined by linkers. The computational data suggest that the vaccine is non-toxic, non-allergenic, thermostable, with the capability to elicit a humoral and cell-mediated immune response. The stabilization of the vaccine construct is validated with molecular dynamics simulation studies. This unique vaccine is made up of 33 highly antigenic epitopes from three proteins that have a prominent role in host-receptor recognition, viral entry, and pathogenicity. We advocate this vaccine must be synthesized and tested urgently as a public health priority.

Can SARS-CoV-2 Accumulate Mutations in the S-Protein to Increase Pathogenicity?

Abstract: SARS-CoV-2 has developed a substantial number of mutations, especially in the S-protein. With the advancement of the pandemic, accumulations of further mutations at the S-protein receptor-binding domain could enhance the infectivity and pathogenicity of the virus. Prediction and evaluation of such mutations are essential for understanding the potential development of more pathogenic strains and for COVID-19 management.

Exploring the interaction of bioactive kaempferol with serum albumin, lysozyme and hemoglobin: A biophysical investigation using multi-spectroscopic, docking and molecular dynamics simulation studies.

Abstract: In recent years research based on kaempferol (KMP) has shown its potential therapeutic applications in medicinal chemistry and clinical biology. Therefore, to understand its molecular recognition mechanism, we studied its interactions with the carrier proteins, namely, human serum albumin (HSA), bovine hemoglobin (BHb) and hen egg white lysozyme (HEWL). The ligand, KMP was able to quench the intrinsic fluorescence of these three proteins efficiently through static quenching mode. The binding constant (Kb) for the interactions of KMP with these three proteins were found in the following order: HSA-KMP > BHb-KMP > HEWL-KMP. Different non-covalent forces such as hydrogen bonding and hydrophobic forces played a major role in the binding of KMP with HSA and HEWL, whereas hydrogen bonding and van der Waals forces contribute to the complexation of BHb with KMP. KMP was able to alter the micro-environment near the Trp fluorophore of the proteins. KMP altered the secondary structural component of all three proteins. The putative binding sites and the residues surrounding the KMP molecule within the respective protein matrix were determined through molecular docking and molecular dynamics (MD) simulation studies. The conformational flexibility of the ligand KMP and the three individual proteins were also evident from the MD simulation studies.

Automatic Detection of COVID-19 Infection from Chest X-ray using Deep Learning

Abstract: COVID-19 infection has created a panic across the globe in recent times. Early detection of COVID-19 infection can save many lives in the prevailing situation. This virus affects the respiratory system of a person and creates white patchy shadows in the lungs. Deep learning is one of the most effective Artificial Intelligence techniques to analyse chest X-ray images for efficient and reliable COVID-19 screening. In this paper, we have proposed a Deep Convolutional Neural Network method for fast and dependable identification of COVID-19 infection cases from the patient chest X-ray images. To validate the performance of the proposed system, chest X-ray images of more than 150 confirmed COVID-19 patients from the Kaggle data repository are used in the experimentation. The results show that the proposed system identifies the cases with an accuracy of 93%.

Half-metallicity in new Heusler alloys Mn2ScZ (Z = Si, Ge, Sn)

Abstract: Study of half-metallicity has been performed in a new series of Mn2ScZ (Z = Si, Ge and Sn) full Heusler alloys using density functional theory with the calculation and implementation of a Hubbard correction term (U). Volume optimization in magnetic and non-magnetic phases for both the Cu2MnAl and Hg2CuTi type structures was done to predict the stable ground state configuration. The stability was determined by calculating their formation energy as well as from elastic constants under ambient conditions. A half-metal is predicted for Mn2ScSi and Mn2ScGe with a narrow band gap in the minority spin whereas Mn2ScSn shows a metallic nature. The magnetic moments of Mn and Sc are coupled in opposite directions with different strengths indicating that the ferrimagnetic order and the total magnetic moment per formula unit for half-metals follows the Slater Pauling rule. And a strong effect was shown by the size of the Z element in the electronic and magnetic properties.

Molecular Dynamics Simulation of Protein and Protein–Ligand Complexes

Abstract: Biomacromolecules, including proteins and their complexes, adopt multiple conformations that are linked to their biological functions. Though some of the structural heterogeneity can be studied by methods like X-ray crystallography, NMR, or cryo-electron microscopy, these methods fail to explain the detailed conformational transitions and dynamics. The dynamic structural states in proteins are covered in magnitude between 10−11 and 10−6 m and time-scales from 10−12 s to 10−5 s. For a comprehensive analysis of the biomolecular dynamics, molecular dynamics (MD) simulation has evolved as the most powerful technique. With the advent of high-end computational power, MD simulations can be performed between μs to the ms time-scale that can accurately describe the dynamics of any system. Various force fields like GROMOS, AMBER, and CHARMM have been developed for MD simulations. Tools like GROMACS, AMBER, CHARMM-GUI, and NAMD are the most widely used methods for MD simulation that can provide precise information on the motions and flexibility of a protein, which contributes to the interaction dynamics of protein–ligand complexes. MD simulation has several other practical applications in diverse research areas, including molecular docking and drug design, refining protein structure predictions, and studying the unfolding pathway of a protein. Combining MD simulation with wet-lab experiments has become an indispensable complement in the investigation of several important and intricate biological processes. Various tools like principal component analysis, cross-correlation analysis, and residues interaction network analysis are additional useful approaches for analyzing MD data. In this chapter, we will discuss MD simulation for a layman understanding and explain how it can be used for protein–ligand characterization as well as for use in diverse biomolecular applications.

Targeting the heme protein hemoglobin by (-)-epigallocatechin gallate and the study of polyphenol-protein association using multi-spectroscopic and computational methods.

Abstract: In this work, the interaction of a bioactive tea polyphenol (-)-epigallocatechin gallate (EGCG) with bovine hemoglobin (BHb) along with its anti-oxidative behavior and the anti-glycation property have been explored using multi-spectroscopic and computational techniques. The binding affinity for EGCG towards BHb was observed to be moderate in nature with an order of 104 M-1, and the fluorescence quenching mechanism was characterized by an unusual static quenching mechanism. The binding constant (Kb) showed a continuous enhancement with temperature from 3.468 ± 0.380 × 104 M-1 at 288 K to 6.017 ± 0.601 × 104 M-1 at 310 K. The fluorescence emission measurements along with molecular docking studies indicated that EGCG binds near the most dominant fluorophore of BHb (β2-Trp37, at the interface of α1 and β2 chains) within the pocket formed by the α1, α2 and β2 chains. The sign and magnitude of the thermodynamic parameters, changes in enthalpy (ΔH = +17.004 ± 1.007 kJ mol-1) and in entropy (ΔS = +146.213 ± 2.390 J K-1 mol-1), indicate that hydrophobic forces play a major role in stabilizing the BHb-EGCG complex. The micro-environment around the EGCG binding site showed an increase in hydrophobicity upon ligand binding. The binding of EGCG with BHb leads to a decrease in the α-helical content, whereas that of the β-sheet increased. FTIR studies also indicated that the secondary structure of BHb changed upon binding with EGCG, along with providing further support for the presence of hydrophobic forces in the complexation process. Molecular docking studies indicated that EGCG binds within the cavity of α1, α2, and β2 chains surrounded by residues such as α1- Lys99, α1-Thr134, α1-Thr137, α1-Tyr140, α2-Lys127 and β2-Trp37. Molecular dynamics simulation studies indicated that EGCG conferred additional stability to BHb. Furthermore, moving away from the binding studies, EGCG was found to prevent the glyoxal (GO)-mediated glycation process of BHb, and it was also found to act as a potent antioxidant against the photo-oxidative damage of BHb.

Study and overview of the novel corona virus disease (COVID-19)

Abstract: In December 2019, a new disease with pneumonia-like symptoms was spreading throughout Wuhan in China which was entitled as novel coronavirus disease or COVID -19 caused by the virus SARS CoV-2. Within a span of a few days, this disease became a global threat and was termed as a pandemic by the World Health Organization (WHO) on March 11, 2020, since then the disease has affected more than 1.5 crore people worldwide and around 6.9 lakh people in India as of July 5, 2020. The origin of the COVID-19 disease has been traced back to the bats, but the intermediary contact is unknown. The disease spreads by respiratory droplets and contaminated surfaces. In most cases, the virus shows mild symptoms like fever, fatigue, dyspnea, cough, etc. which may become severe if appropriate precautions are not adhered to. For people with comorbidities (usually elderly) the disease may turn deadly and cause pneumonia, Acute Respiratory Disease Syndrome (ARDS), and multi-organ failure, thereby affecting a person's ability to breathe leading to being put on the ventilator support. The reproduction number (Rℴ) of COVID-19 is much higher than its predecessors and genetically similar diseases like SARS-CoV and MERS-CoV. This paper discusses the epidemiological characteristics of the SARS-CoV-2 virus, its phylogenetic relationship with the previous pandemic causing viruses such as SARS-CoV-1 and MERS-CoV and analyzes the various responses to this global pandemic worldwide, focusing on the actions taken by India and their outcomes.

Direct Interaction between the β-Amyloid Core and Tau Facilitates Cross-Seeding: A Novel Target for Therapeutic Intervention

Abstract: The deposition of amyloid-β (Aβ) plaques and tau-based neurofibrillary tangles is a neuropathological feature of Alzheimer’s disease (AD). While studies have shown that the Aβ and tau interaction r...

Draft Genome of the Liver Fluke Fasciola gigantica

Abstract: Fascioliasis, a neglected foodborne disease caused by liver flukes (genus Fasciola), affects more than 200 million people worldwide. Despite technological advances, little is known about the molecu...

Inter-state transmission potential and vulnerability of COVID-19 in India

Abstract: Since the first case of COVID-19 traced in India on 30th January, 2020, the total no. of confirmed cases is amplified. To assess the inter-state diversity in spreading potentiality of COVID-19, the exposure, readiness and resilience capability have been studied. On the basis of the extracted data, the outbreak scenario, growth rate, testing amenities have been analysed. The study reflects that there is an enormous disparity in growth rate and total COVID-19 cases. The major outbreak clusters associated with major cities of India. COVID-19 cases are very swiftly amplifying with exponential growth in every four to seven days in main affected states during first phase of lockdown. The result shows the vibrant disproportion in the aspects of, hospital bed ratio, coronavirus case-hospital bed ratio, provision of isolation and ventilators, test ratio, distribution of testing laboratories and accessibility of test centres all over India. The study indicates the sharp inequality in transmission potentiality and resilience capacity of different states. Every state and union territory are not well-prepared to contain the spreading of COVID-19. The strict protective measures and uniform resilience system must be implemented in every corner of India to battle against the menace of COVID-19.

Design of a multi-epitope subunit vaccine for immune-protection against Leishmania parasite.

Abstract: Visceral Leishmaniasis (VL) is an insect-borne neglected disease caused by the protozoan parasite Leishmania donovani. In the absence of a commercial vaccine against VL, chemotherapy is currently the only option used for the treatment of VL. Vaccination has been considered as the most effective and powerful tool for complete eradication and control of infectious diseases. In this study, we aimed to design a peptide-based vaccine against L. donovani using immuno-bioinformatic tools. We identified 6 HTL, 18 CTL, and 25 B-cell epitopes from three hypothetical membrane proteins of L. donovani. All these epitopes were used to make a vaccine construct along with linkers. An adjuvant was also added at the N-terminal to enhance its immunogenicity. After that, we checked the quality of this vaccine construct and found that it is nontoxic, nonallergic, and thermally stable. A 3D structure of the vaccine construct was also generated by homology modeling to evaluate its interaction with innate immune receptors (TLR). Molecular docking was performed, which confirmed its binding with a toll-like receptor-2 (TLR-2). The stability of vaccine-TLR-2 complex and underlying interactions were evaluated using molecular dynamic simulation. Lastly, we carried out in silico cloning to check the expression of the final designed vaccine. The designed vaccine construct needs further experimental and clinical investigations to develop it as a safe and effective vaccine against VL infection.

Benzene Hydroxylation by Bioinspired Copper(II) Complexes: Coordination Geometry versus Reactivity.

Abstract: A series of bioinspired copper(II) complexes of N4-tripodal and sterically crowded diazepane-based ligands have been investigated as catalysts for functionalization of the aromatic C-H bond. The tripodal-ligand-based complexes exhibited distorted trigonal-bipyramidal (TBP) geometry (τ, 0.70) around the copper(II) center; however, diazepane-ligand-based complexes adopted square-pyramidal (SP) geometry (τ, 0.037). The Cu-NPy bonds (2.003-2.096 A) are almost identical and shorter than Cu-Namine bonds (2.01-2.148 A). Also, their Cu-O (Cu-Owater, 1.988 A; Cu-Otriflate, 2.33 A) bond distances are slightly varied. All of the complexes exhibited Cu2+ → Cu+ redox couples in acetonitrile, where the redox potentials of TBP-based complexes (-0.251 to -0.383 V) are higher than those of SP-based complexes (-0.450 to -0.527 V). The d-d bands around 582-757 nm and axial patterns of electron paramagnetic resonance spectra [g∥, 2.200-2.251; A∥, (146-166) × 10-4 cm-1] of the complexes suggest the existence of five-coordination geometry. The bonding parameters showed K∥ > K⊥ for all complexes, corresponding to out-of-plane π bonding. The complexes catalyzed direct hydroxylation of benzene using 30% H2O2 and afforded phenol exclusively. The complexes with TBP geometry exhibited the highest amount of phenol formation (37%) with selectivity (98%) superior to that of diazepane-based complexes (29%), which preferred to adopt SP-based geometry. Hydroxylation of benzene likely proceeded via a CuII-OOH key intermediate, and its formation has been established by electrospray ionization mass spectrometry, vibrational, and electronic spectra. Their formation constants have been calculated as (2.54-11.85) × 10-2 s-1 from the appearance of an O (π*σ) → Cu ligand-to-metal charge-transfer transition around 370-390 nm. The kinetic isotope effect (KIE) experiments showed values of 0.97-1.12 for all complexes, which further supports the crucial role of Cu-OOH in catalysis. The 18O-labeling studies using H218O2 showed a 92% incorporation of 18O into phenol, which confirms H2O2 as the key oxygen supplier. Overall, the coordination geometry of the complexes strongly influenced the catalytic efficiencies. The geometry of one of the CuII-OOH intermediates has been optimized by the density functional theory method, and its calculated electronic and vibrational spectra are almost similar to the experimentally observed values.

FT-SDN: A Fault-Tolerant Distributed Architecture for Software Defined Network

Abstract: The traditional Software Defined Network (SDN) architecture is based on single controller in the Control Plane. Therefore, network functioning become highly dependent on the performance of the single controller in the Control Plane, which is undesirable for any reliable application. Despite many advantages of SDN, its deployment in the practical field is restricted since reliability and fault-tolerance capabilities of the system are not satisfactory. To overcome these difficulties of SDN, (FT-SDN) architecture has been proposed. The proposed architecture consists of a simple and effective distributed Control Plane with multiple controllers. FT-SDN uses a synchronized mechanism to periodically update the controller’s state within themselves. In case of failure, FT-SDN has the ability to select another working controller based on the distance and delays among different network entities. The performance of the FT-SDN architecture was examined with respect to different specifications in the presence of faults. Experimentation was done in simulation where results were found to be satisfactory.