Respiratory Syncytial Virus Vaccine Design Using Structure-Based Machine-Learning Models.

ABSTRACT: When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection or reverse-genetic manipulation and may include point mutations, codon and gene deletions, and genome rearrangements. Attenuation typically involves the reduction in virus replication, due to direct effects on viral structural and replicative machinery or viral factors that antagonize host defense or cause disease. However, attenuation must balance reduced replication and immunogenic antigen expression. In the present study, we explored a new approach in order to discover attenuating mutations. Specifically, we used protein structure modeling and computational methods to identify amino acid substitutions in the RSV nonstructural protein 1 (N

SUBMITTER: McCarty TC 

PROVIDER: S-EPMC11209532 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature