| Amino acid networks are a series of noncovalent interactions between residues that can span from surface-exposed residues to those deep in the active site of the protein. These amino acid networks, or 'sectors', have been proposed to be intrinsic to all proteins, and to play a key role in protein allostery. Current methods of identification of networks include computationallybased and experimentally-based methods, though only the latter have the ability to probe amino acid networks under a variety of ligand-bound conditions. A recently developed NMR-based technique is known as the CHEmical Shift Covariance Analysis (CHESCA) method was used to identify and characterize the amino acid networks in isolated alpha-subunits of tryptophan synthase (alphaTS).;Tryptophan synthase (TS) has long been studied for the intersubunit communication observed between the alpha- and beta-subunits (betaTS) as well as the intramolecular channel connecting the two active sites. The conformational states of the two subunits are highly synchronized and it is possible that this extensive intersubunit communication is the result of the amino acid networks connecting alphaTS and betaTS. The use of alphaTS as the system allowed for the study of the enzyme under working conditions (i.e. while undergoing active catalytic turnover) and under resting conditions (i.e. while in the apo state), as well as two other, single ligand-bound states, revealing the ligand-dependency of the alphaTS amino acid networks. Most importantly, two clusters of residues were identified in each state and the catalytic residue, Glu49, switches clusters only in the working state. Additionally, the T183V substitution severs crucial hydrogen bonds between the dynamic beta2alpha2 and beta6alpha6 loops. This disruption appears to prevent the cluster switch of Glu49 and results in a 14-fold decrease in catalytic efficiency. These results suggest that amino acid networks play a crucial role in catalysis and association with the correct cluster is key to enzyme function. |
