Date of Award
Doctor of Philosophy (PhD)
Computational and Data Sciences
Gennady Verkhivker, Ph.D.
The advent of the Omicron strain of SARS-CoV-2 has elicited apprehension regarding its potential influence on the effectiveness of current vaccines and antibody treatments. The present investigation involved the implementation of mutational scanning analyses to examine the impact of Omicron mutations on the binding affinity of four categories of antibodies that target the Omicron receptor binding domain (RBD) of the Spike protein. The study demonstrates that the Omicron variant harbors 23 unique mutations across the RBD regions I, II, III, and IV. Of these mutations, seven are shared between RBD regions I and II, while three are shared among RBD regions I, II, and III. The findings suggest that the mutations exert a noteworthy influence on the antibodies' binding affinity, especially in Class II and Class III antibodies. Among the mutations, those located at positions R346, L452, and F490 appear to have a particularly notable impact. Multiple mutations were detected at positions F375, Y501, and H505 across all sub-variants of Omicron, indicating their potential significance in evading the immune system. The mutations could potentially bear significant ramifications with regards to immune evasion. The research underscores the significance of continuous observation and scrutiny of viral mutations in order to guide the creation of efficacious treatments for novel strains of SARS-CoV-2.
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M. Alshahrani, "Computational analysis of antibody binding mechanisms to the omicron RBD of SARS-CoV-2 spike protein: Identification of epitopes and hotspots for developing effective therapeutic strategies," Ph.D. dissertation, Chapman University, Orange, CA, 2023. https://doi.org/10.36837/chapman.000491