The structure-based approaches to computing viral fitness.

Viral fitness presents a complex challenge that requires a deep understanding of evolution and selection pressures. The swift emergence of mutations in viruses makes them ideal models for studying evolutionary dynamics. Recent advancements in biophysical methods and structural biology have facilitated insights into how these mutations influence evolutionary trajectories at the structural level. Computationally guided structural techniques are particularly valuable for analyzing the mutational landscape across all possible mutations in viral proteins under selection pressure. The virus often interacts via the receptor binding domain (RBD) of its surface protein with the receptor protein of the host cell. This binding is a key step for the viral entry in host cell and infection. In response, the host immune response or vaccines generate antibodies to neutralize the virus particles. This creates a competitive scenario where the viral surface protein competes for binding between host cell receptor and antibodies. The viral mutations supposedly evolve to effectively bind to host receptors while evading the antibody recognition. The differential binding affinity of the viral surface protein, preferably via RBD, between host receptor and antibodies may aid in defining the molecular level viral fitness function. The present chapter explores these dynamics through the lens of severe acute respiratory syndrome coronavirus 2 spike protein, binding to human angiotensin-converting enzyme 2 and circulating antibodies. Interestingly, this strategy utilized the wealth of protein structural data from cryo-electron microscopy and biochemical data on mutations.