  Network theory-based approaches provide valuable insights into the variations
in global structural connectivity between differing dynamical states of
proteins. Our objective is to review network-based analyses to elucidate such
variations, especially in the context of subtle conformational changes. We
present technical details of the construction and analyses of protein structure
networks, encompassing both the non-covalent connectivity and dynamics. We
examine the selection of optimal criteria for connectivity based on the
physical concept of percolation. We highlight the advantages of using
side-chain based network metrics in contrast to backbone measurements. As an
illustrative example, we apply the described network approach to investigate
the global conformational change between the closed and partially open states
of the SARS-CoV-2 spike protein. This conformational change in the spike
protein is crucial for coronavirus entry and fusion into human cells. Our
analysis reveals global structural reorientations between the two states of the
spike protein despite small changes between the two states at the backbone
level. We also observe some differences at strategic locations in the
structures, correlating with their functions, asserting the advantages of the
side-chain network analysis. Finally we present a view of allostery as a subtle
synergistic-global change between the ligand and the receptor, the
incorporation of which would enhance the drug design strategies.
