Abstract
Background: Rhinoviruses (RV) are associated with the development and exacerbations of asthma and chronic obstructive pulmonary disease. They've also been linked to more severe diseases like pneumonia, acute bronchiolitis, croup, and otitis media. Because of the hypervariable sequences in the same serotypes, no effective vaccine against rhinoviruses has been developed to date. With the availability of new fulllength genome sequences for all RV-A and RV-B serotyped strains, this study used bioinformatics to find a suitable RV strain with the highest similarity matrices to the other strains. Methods: The full genomic sequences of all known different RV-A and-B prototypes were downloaded from the National Centre for Biotechnology Information (NCBI) and divided into minor low-density lipoprotein receptor (LDLR) and major intercellular adhesion molecule groups (ICAM). The sequences were edited using Biological Sequence Alignment Editor, v 7.2.0 (BioEdit software) to study each capsid protein (VP1, VP2, VP3, and VP4) and analyzed using the EMBL-EBI ClustalW server and the more current Clustal Omega tool for the calculation of the identities and similarities. Results: We analyzed and predicted immunogenic motifs from capsid proteins that are conserved across distinct RV serotypes using a bioinformatics technique. The amino acid sequences of VP3 were found to be the most varied, while VP4 was the most conserved protein among all RV-A and RV-B strains. Among all strains studied, RV-74 demonstrated the highest degree of homology to other strains and could be a potential genetic source for recombinant protein production. Nine highly conserved regions with a minimum length of 9-mers were identified, which could serve as potential immune targets against rhinoviruses. Conclusion: Therefore, bioinformatics analysis conducted in the current study has paved the way for the selection of immunogenic targets. Bioinformatically, the ideal strain's capsid protein is suggested to contain the most common RVs immunogenic sites. (c) 2021 The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).