Background: Antigens (or their epitopes)-carrier protein combinations are extensively utilized for vaccine development strategies. Chemical conjugation methods are cumbersome with limited conjugation sites. Computational protein modelling methods can evaluate every position of a carrier protein for conjugation via epitope grafting in a reasonable time frame as compared to wet experimental techniques. Graftibility of positions can be estimated by the presence of native atomic contacts in resulting chimeric antigen.
Methodology: Five epitopes were selected, and computational grafting at each position was performed in three templates of serum albumin. Protein modelling algorithms such as segment matching and satisfaction of spatial restraints were employed for computational grafting. Contact-based protein discriminatory function was used to evaluate the chimeric proteins having native atomic contacts.
Results: On the evaluation of approximately 1 million distinct protein modelling simulations, region around the 450th position of serum albumin was observed to be suitable for epitope grafting.
Conclusion: Computational protein modelling tools may be used to design a chimeric antigen. The approach may overcome the limitations associated with chemical conjugation and furthermore harness the potential of custom gene synthesis/recombinant protein production.
Keywords: Computational protein design; Malaria; Vaccine.
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