In Silico Analysis of L1/L2 Sequences of Human Papillomaviruses: Implication for Universal Vaccine Design

2017 ◽  
Vol 30 (3) ◽  
pp. 210-223 ◽  
Author(s):  
Nazila Ghorban Hosseini ◽  
Majid Tebianian ◽  
Ayoub Farhadi ◽  
Ali Hossein khani ◽  
Arian Rahimi ◽  
...  
3 Biotech ◽  
2014 ◽  
Vol 5 (4) ◽  
pp. 497-503 ◽  
Author(s):  
Amisha Jain ◽  
Pranav Tripathi ◽  
Aniket Shrotriya ◽  
Ritu Chaudhary ◽  
Ajeet Singh

2020 ◽  
Author(s):  
Mona Moballegh Naseri ◽  
Saeed Shams ◽  
Mohammad Moballegh Naseri ◽  
Bita Bakhshi

Abstract Objective: To eradicate infectious diseases, vaccination is an important strategy. CadF protein of Campylo bacter jejuni is one of the important factors in the process of the pathogenesis of the bacterium. So, the purpose of the work was to perform a bioinformatics study for identifying an epitope-based CadF vaccine, as a subunit vaccine. CadF sequences were extracted from the NCBI database. In silico analysis including all ergeni city, antigenicity, epitope conservancy assessment, molecular docking, etc.was done by different servers. Results:The results showed that CadF is an antigenic and non-allergenic protein and provides a suitable structure for vaccine design. Among epitopes, LSDSLALRL has been confirmed to stimulate both B and T cells. This 9-mers peptide is located in 135-143 segment of the CadF protein and interacted with HLA-A0101 and HLA-DRB1 0101 with energies of docking -26.18kcal/mol and -109.89kcal/mol. The peptide is not an allergen and as an antigen, it has the ability for motivating the immune system. Hence, the analyses are performed on that the epitope structure could verify the design of a vaccine against C. jejuni. The obtained theoretical results showed that CadF protein could be used for designing and evaluating a new vaccine in humans.


2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.


2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas

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