The group from University of Catania and coordinated by Prof Pappalardo illustrates the latest developments in a paper accepted by the prestigious journal Briefings in Bioinformatics
The phenomenon of cross-reactivity is the ability of an antibody to act against viruses that are different but very similar - at least in some parts - to each other.
Researchers at the Combine Group of the University of Catania investigated cross-reactivity in relation to the possibility of finding existing vaccines that could elicit the human immune system response to SARS-CoV-2.
Prof Pappalardo and his team describe the findings in a paper that has been recently accepted for publication in the prestigious journal Briefing of Bioinformatics: the article shows in detail the multi-step and multi-scale bioinformatic problem solving protocol that can be used to discover and test potential antigen portions that could be implemented in vaccines against SARS-CoV-2.
The integrated bioinformatics pipeline used to test these portions merges the prediction power of different software that act at different scales (molecular to organ) with a final step where an in silico platform simulates the human immune system dynamics in response to SARS-CoV-2.
“Technological advances in computer modelling and simulation are making the difference to better predict the efficacy and safety of new vaccines” - says Professor Francesco Pappalardo, associate professor at the University of Catania - “and help in providing quick interventional solutions to outbreaks as the COVID-19 pandemic.”
Findings from this research are based on previous observations of co-author Pedro Reche, associate professor in immunology at the Complutense University of Madrid: “We found combination vaccines for treating diphtheria, tetanus, and pertussis infectious diseases (DTP vaccine) to be significant sources of potential cross-reactive immunity to SARS-CoV-2[1], and this result has been confirmed by a recent study published in preprint in June[2]”.
The most interesting aspect of the research is that the proposed protocol can be potentially applied to every disease, as main author Dr Giulia Russo explains: “This paper[3] represents a great result for the STriTuVaD project, in which the computational platform has been tested to simulate the human immune system response to tuberculosis disease and treatment, and it is also a starting point for further investigations that will be carried out during the In Silico World project.”
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