Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase

Abstract

Dihydrofolate reductase (DHFR), due to its universality and the depth with which it has been studied, is a model system in the study of protein dynamics. Myriad previous works have identified networks of residues in positions near to and remote from the active site that are involved in the dynamics. For example, specific mutations on the Met20 loop in Escherichia coli DHFR (N23PP/S148A) are known to disrupt millisecond-time scale motions as well as reduce catalytic activity. However, how and if networks of dynamically coupled residues influence the evolution of DHFR is still an unanswered question. In this study, we first identify, by statistical coupling analysis and molecular dynamic simulations, a network of coevolving residues that possesses increased correlated motions. We then go on to show that allosteric communication in this network is knocked down in N23PP/S148A mutant E. coli DHFR. We also identify two sites in the human DHFR sector which may accommodate the Met20 loop double proline motif. Finally, we demonstrate a concerted evolutionary change in the human DHFR allosteric networks, which maintains dynamic communication. These findings strongly implicate protein dynamics as a driving force for evolution.