In silico homology modelling and prediction of novel epitopic peptides from P24 protein of Haemonchus contortus

Gene ◽  
2019 ◽  
Vol 703 ◽  
pp. 102-111 ◽  
Author(s):  
G.V. Vedamurthy ◽  
Haseen Ahmad ◽  
Suneel Kumar Onteru ◽  
Vijay Kumar Saxena
Keyword(s):  
Haemonchus Contortus ◽  
In Silico ◽  
Homology Modelling ◽  
P24 Protein

scholarly journals Identification of Potential HCV Inhibitors Based on the Interaction of Epigallocatechin-3-Gallate with Viral Envelope Proteins

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1257
Author(s):  
Fareena Shahid ◽  
Noreen ◽  
Roshan Ali ◽  
Syed Lal Badshah ◽  
Syed Babar Jamal ◽  
...  
Keyword(s):  
Hepatitis C ◽  
In Silico ◽  
Experimental Validation ◽  
Homology Modelling ◽  
Viral Envelope ◽  
Screening Methods ◽  
Binding Affinities ◽  
Autodock Vina ◽  
Potential Inhibitors ◽  
Very High

Hepatitis C is affecting millions of people around the globe annually, which leads to death in very high numbers. After many years of research, hepatitis C virus (HCV) remains a serious threat to the human population and needs proper management. The in silico approach in the drug discovery process is an efficient method in identifying inhibitors for various diseases. In our study, the interaction between Epigallocatechin-3-gallate, a component of green tea, and envelope glycoprotein E2 of HCV is evaluated. Epigallocatechin-3-gallate is the most promising polyphenol approved through cell culture analysis that can inhibit the entry of HCV. Therefore, various in silico techniques have been employed to find out other potential inhibitors that can behave as EGCG. Thus, the homology modelling of E2 protein was performed. The potential lead molecules were predicted using ligand-based as well as structure-based virtual screening methods. The compounds obtained were then screened through PyRx. The drugs obtained were ranked based on their binding affinities. Furthermore, the docking of the topmost drugs was performed by AutoDock Vina, while its 2D interactions were plotted in LigPlot+. The lead compound mms02387687 (2-[[5-[(4-ethylphenoxy) methyl]-4-prop-2-enyl-1,2,4-triazol-3-yl] sulfanyl]-N-[3(trifluoromethyl) phenyl] acetamide) was ranked on top, and we believe it can serve as a drug against HCV in the future, owing to experimental validation.

In silico Repurposing of Anticancer Drug (5-Fluorouracil) as an Antibacterial Agent against Klebsiella pneumoniae

2021 ◽  
Vol 18 ◽  
Author(s):  
Amey Sharma ◽  
Apoorva Rana ◽  
Lakshya Mangtani ◽  
Aakanksha Kalra ◽  
Ravi Ranjan Kumar Niraj
Keyword(s):  
Molecular Docking ◽  
Klebsiella Pneumoniae ◽  
Thymidylate Synthase ◽  
In Silico ◽  
Homology Modelling ◽  
Klebsiella Pneumonia ◽  
Drug Resistant ◽  
Vitro Analysis ◽  
In Vitro Analysis

Background: Infections caused by drug resistant microorganisms have been increasing worldwide thereby being one of the major causes of morbidity in the 21st century. Klebsiella pneumoniae is one such bacteria causing lung inflammation, lung injury and death. Emergence of hyper-virulent and drug resistant species such as ESBL and CRKP has made this microbe a serious and urgent threat. The pace of emergence of these species is outgrowing the development of novel drug and vaccine candidates thereby focusing on drug repurposing approach. Objective: 1. Homology Modelling of Thymidylate Synthase. 2. Verification of Modelled Structure. 3. Molecular Docking. 4. Molecular Dynamic Simulation of Docked Complex. 5. In vitro analysis of 5-FU activity against Klebsiella pneumonia. Method: The 3-D structure of Thymidylate Synthase was predicted using Swiss-Model server and validated by in silico approaches. - Determination protein-protein interactions using STRING database. - Molecular docking. - MD simulations of 5-FU with predicted structure of thymidylate synthase. - In vitro antimicrobial drug sensitivity assay at different concentrations. Result: Hydrogen bond was observed in Molecular Docking - Protein-ligand complex remains stable during simulation. - 5-FU shows antimicrobial activity against Klebsiella pneumonia during In vitro study. Conclusion: Both In silico as well as in vitro analysis have indicated that 5-FU can potentially be developed as an antimicrobial agent towards Klebsiella pneumonia

scholarly journals Homology Modelling and Molecular Docking Studies of Selected Substituted Benzo[d]imidazol-1-yl)methyl)benzimidamide Scaffolds on Plasmodium falciparum Adenylosuccinate Lyase Receptor

2019 ◽  
Vol 13 ◽  
pp. 117793221986553 ◽  
Author(s):  
Gbolahan O Oduselu ◽  
Olayinka O Ajani ◽  
Yvonne U Ajamma ◽  
Benedikt Brors ◽  
Ezekiel Adebiyi
Keyword(s):  
Plasmodium Falciparum ◽  
Molecular Docking ◽  
In Silico ◽  
Homology Modelling ◽  
3D Structure ◽  
Docking Studies ◽  
Binding Energies ◽  
Benzimidazole Derivatives ◽  
Adenylosuccinate Lyase ◽  
In Silico Admet

Plasmodium falciparum adenylosuccinate lyase ( PfADSL) is an important enzyme in purine metabolism. Although several benzimidazole derivatives have been commercially developed into drugs, the template design as inhibitor against PfADSL has not been fully explored. This study aims to model the 3-dimensional (3D) structure of PfADSL, design and predict in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) of 8 substituted benzo[ d]imidazol-1-yl)methyl)benzimidamide compounds as well as predict the potential interaction modes and binding affinities of the designed ligands with the modelled PfADSL. PfADSL 3D structure was modelled using SWISS-MODEL, whereas the compounds were designed using ChemDraw Professional. ADMET predictions were done using OSIRIS Property Explorer and Swiss ADME, whereas molecular docking was done with AutoDock Tools. All designed compounds exhibited good in silico ADMET properties, hence can be considered safe for drug development. Binding energies ranged from −6.85 to −8.75 kcal/mol. Thus, they could be further synthesised and developed into active commercial antimalarial drugs.

scholarly journals Natural Product Compounds in Alpinia officinarum and Ginger are Potent SARS-CoV-2 Papain-like Protease Inhibitors

2020 ◽  
Author(s):  
Dibakar Goswami ◽  
Mukesh Kumar ◽  
Sunil K. Ghosh ◽  
Amit Das
Keyword(s):  
Virtual Screening ◽  
Natural Product ◽  
Protease Inhibitors ◽  
In Silico ◽  
Drug Target ◽  
Homology Modelling ◽  
Protease Domain ◽  
Lead Compounds ◽  
Alpinia Officinarum ◽  
Natural Product Compounds

SARS-CoV-2 or COVID-19 has caused more than 10,00,000 infections and ~55,000 deaths worldwide spanning over 203 countries, and the numbers are exponentially increasing. Due to urgent need of treating the SARS infection, many approved, pre-clinical, anti-viral, anti-malarial and anti-SARS drugs are being administered to patients. SARS-CoV-2 papain-like protease (PLpro) has a protease domain which cleaves the viral polyproteins a/b, necessary for its survival and replication, and is one of the drug target against SARS-CoV-2. 3D structures of SARS-CoV-2 PLpro were built by homology modelling. Two models having partially open and closed conformations were used in our study. Virtual screening of natural product compounds was performed. We prepared an in house library of compounds found in rhizomes, Alpinia officinarum, ginger and curcuma, and docked them into the solvent accessible S3-S4 pocket of PLpro. Eight compounds from Alpinia officinarum and ginger bind with high in silico affinity to closed PLpro conformer, and hence are potential SARS-CoV-2 PLpro inhibitors. Our study reveal new lead compounds targeting SARS-CoV-2. Further structure based modifications or extract formulations of these compounds can lead to highly potent inhibitors to treat SARS-CoV-2 infections.<br>

scholarly journals In-silico Design of Multi-epitope Vaccine against Nipah Virus using Immunoinformatics Approach

2021 ◽  
Vol 15 (1) ◽  
pp. 212-231
Author(s):  
Suraj Raju ◽  
Debasish Sahoo ◽  
Vikas Kumar Bhari
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Vaccine Development ◽  
Homology Modelling ◽  
Nipah Virus ◽  
Docking Simulation ◽  
Dynamics Simulation ◽  
Cytotoxic T Cell ◽  
Viral Spread

Nipah virus is a pleomorphic virus that causes high mortality with unpredictable outbreaks. The virus also shows high zoonotic potential with long term neurological damage after recovery further adding to the disease burden. An in-silico epitope-based vaccine offers a promising solution to supplement wider efforts to control the viral spread. This is achieved through immunoinformatics approach using a plethora of servers available. We derived cytotoxic T-cell, T-Helper, B-cell and IFN-γ targeting epitopes from surface glycoprotein G. Cytotoxic T-cell specific epitopes, HLA-B*4402, chimeric multiepitope vaccine structures were prepared using homology modelling method. The structures were validated using various methods and docking simulation was performed between epitopes and HLA-B*4402. Similarly, the vaccine construct was docked to Toll like receptor-4 and a molecular dynamics simulation was performed to assess stability of interaction. Both the docking simulations showed stable interactions with their respective receptors. Immune-simulation was carried out to validate the efficacy of vaccine candidate which showed elevated levels of antibodies such as IgM and IgG due to increase in active B cell population. Both in-vitro and in-vivo serological analysis is required for confirmation of vaccine potency. To facilitate this effort, codon optimization was undertaken to remove existing codon bias. The optimized gene sequence was cloned into the PUC19 vector to express in Escherichia coli K12 strain. Additionally, a poly histidine (6xHis) tag was added at the C-terminal end to ease the purification step. The immune-informatics approach hopes to accelerate vaccine development process to reduce the risk of attenuation while increasing the success rates of pre-clinical trials.

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