In-silico analysis of ectodomain G protein of Respiratory Syncytial Virus

2017 ◽  
Vol 4 (3) ◽  
pp. 110
Author(s):  
Zoya Shafat ◽  
I. Faizan ◽  
Ayesha Tazeen ◽  
Anam Farooqui ◽  
Farah Deeba ◽  
...  
2021 ◽  
Vol 27 ◽  
Author(s):  
Khalid Alshaghdali ◽  
Mohd Saeed ◽  
Mohammad Amjad Kamal ◽  
Amir Saeed

Background: The human respiratory syncytial virus (RSV) has been linked with various respiratory diseases such as common cold to lower respiratory tract illnesses like pneumonia and bronchiolitis. TLRs play a critical role in generating host immune responses against RSV. TLRs are expressed not only on leukocytes but also on many other cell types and can recognize RSV. Previous studies have established that RSV can interact with TLR4 and initiate an inflammatory cascade of cytokines. The data from a recent study indicated that TLR2/TLR6 is involved in RSV recognition and subsequent innate immune activation. However, the nature of binding and the envelope protein of RSV involved in this interaction with TLRs are not studied yet. Objective: We hypothesized that RSV G protein could bind to TLRs and mediate the inflammatory immune response against the virus infection. Therefore, we investigated whether RSV G protein could activate innate immune response through TLR signaling. Methods: Different TLR antagonists were used to assessing the effect of RSV and RSV G ectodomain exposure in human primary small airway epithelial cells (HSAECs). Various inflammatory cytokines, chemokines, and type I IFNs were measured by ELISA along with their mRNA expression by qPCR. In silico interaction of RSV G protein with TLR2/TLR6 was also analyzed. Results: ELISA and qPCR analysis have shown that TLR2/TLR6 signaling is activated in HSAECs upon RSV and RSV G protein exposure which initiates innate immune response against RSV. Moreover, RSV envelope protein G plays a crucial role in the binding and activating TLR2/TLR6 signaling. Conclusion: In summary, our study shows that TLR2/TLR6 plays an essential role in activating an innate immune response upon RSV recognition, which could help promote RSV clearance and preventing RSV-induced disease.


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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