Kinetic Barrier to Enzyme Inhibition Is Manipulated by Dynamical Local Interactions in E. coli DHFR

Abstract

Dihydrofolate reductase (DHFR) is an important drug target and a highly studied model protein for understanding enzyme dynamics. DHFR's crucial role in folate synthesis renders it an ideal candidate to understand protein function and protein evolution mechanisms. In this study, to understand how a newly proposed DHFR inhibitor, 4′-deoxy methyl trimethoprim (4′-DTMP), alters evolutionary trajectories, we studied interactions that lead to its superior performance over that of trimethoprim (TMP). To elucidate the inhibition mechanism of 4′-DTMP, we first confirmed, both computationally and experimentally, that the relative binding free energy cost for the mutation of TMP and 4′-DTMP is the same, pointing the origin of the characteristic differences to be kinetic rather than thermodynamic. We then employed an interaction-based analysis by focusing first on the active site and then on the whole enzyme. We confirmed that the polar modification in 4′-DTMP induces additional local interactions with the enzyme, particularly, the M20 loop. These changes are propagated to the whole enzyme as shifts in the hydrogen bond networks. To shed light on the allosteric interactions, we support our analysis with network-based community analysis and show that segmentation of the loop domain of inhibitor-bound DHFR must be avoided by a successful inhibitor.

Allosteric Modulation of Fluorescence Revealed by Hydrogen Bond Dynamics in a Genetically Encoded Maltose Biosensor

“…Shift in hydrogen bond networks has been shown to contribute to allosteric regulation of many protein systems. 37,47,48 To our knowledge, this is the first study that sheds light on the working mechanism of a single FP biosensor using hydrogen bond dynamics and chromophore SASA as fingerprints of bright vs. dark states. Our results indicate that hydrogen bonding between the two linkers in the ON state possibly creates a more closed area at the circular permutation site, evidenced by the reduced SASA values for the chromophore, and helps preserve chromophore in the anionic state.…”

“…Hydrogen bond lists obtained by the VMD Timeline plugin were processed with a previously published python script which merges all hydrogen bonds between the atoms of two residues into a single entry. 37,38 The trajectories were clustered using the CPPTRAJ program with k -means algorithm based on C α root mean square deviation (RMSD) values. 39 Solvent accessible surface areas (SASA) were calculated with a VMD Tcl script with a probe radius of 1.4 Å using Shrake-Rupley alghoritm.…”