We are facing a once in a lifetime pandemic situation due to COVID-19. The past decade have seen an advent of computational prediction and design of T cell/B cell epitope based vaccine. Famously known as reverse vaccinology approach, a wealth of information has been gathered under this approach to identify key peptides that will be used for vaccine. In reality, when a real situation like COVID-19 took place we are observing these predictions are taken less seriously . These led to my question what is the importance of these immunoinformatics tools if not used in a real life situation. Thanks in advance for sharing your thoughts.
I wish you read more papers.
Article Emerging Vaccine Informatics
There are success story with specific to vaccine development against any virus. Although many fails at clinical trials. But it doesn't means insilico analysis is just for publications only.
Dear Dr. Arora,
Thank you for your suggestion and the attached paper. It is indeed a great review.
But what i wanted to know the limited applicability of the in-silico vaccinomics approach in context of a real epidemic situation. It is undeniable that computational screening will save a lot of time to identify best candidates for vaccine. Still traditional/molecular biology or other vector based approaches are leading the way.
Again thank you for sharing your thoughs.
Hello
In normal situation there are a lot of paper published about in-silico prediction of all sorts. The outcome is not definitely a cure or vaccine. The next step which is the time-money consuming wet lab experiments is a determiner. In a pandemic situation like now that a lot of people may die in a single day, the bottleneck of this process is laboratory validation. You may conduct 100s of predictions but how many will have a chance to undergo validation in a very short time!?
As you have already said , the serotype based predictions are an emerging trend. Computational epitope selection revolves around the determination of the critical binding sites of a particular antigen to its corresponding antibody. Certain binding sites or conformations may vary as a result of ambient conditions such as the deficiency or in of some protein or organelle. During computational simulations, we try to relocate the real world environment to encourage efficient epitope selection. However, based on the genetic predisposition, medical history, etc, there is a possibly that critical contributing factors are overlooked or under estimated when thr aim is global application at the scale of covid 19. Although this approach is promising, in a situation like the covid 19 pandemic new information regarding the virus is still emerging and relying on an emerging strategy such as computational selection of epitopes (although undertaken https://chemrxiv.org/articles/T_Cell_Epitope-Based_Vaccine_Design_for_Pandemic_Novel_Coronavirus_2019-nCoV/12029523 ) may appear a bit risky.
Dear Mr. Muqsit Minhaj Pirzada
Thank you for sharing your valuable thoughts.
-Nazmul
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