Sensitivity of Functional Loop Conformations on Long-Range Electrostatics: Implications for M20 Loop Dynamics in E. coli Dihydrofolate Reductase

Solution Ionic Strength Can Modulate Functional Loop Conformations in E. coli Dihydrofolate Reductase

The observation of multiple conformations of a functional loop (termed M20) in the Escherichia coli dihydrofolate reductase (ecDHFR) enzyme triggered the proposition that large-scale motions of protein structural elements contribute to enzyme catalysis. The transition of the M20 loop from a closed conformation to an occluded conformation was thought to aid the rate-limiting release of the products. However, the influence of charged species in the solution environment on the observed M20 loop conformations, independent of charged ligands bound to the enzyme, had not been considered. Molecular dynamics simulations of ecDHFR in model CaCl2 solutions of varying molar ionic strengths IM reveal a substantial free energy barrier between occluded and closed M20 loop states at IM exceeding the E. coli threshold (∼0.24 M). This barrier may facilitate crystallization of ecDHFR in the occluded state, consistent with ecDHFR structures obtained at IM exceeding 0.3 M. At lower IM (≤0.15 M), the M20 loop can explore the occluded state, but prefers an open/partially closed conformation, again consistent with ecDHFR structures. Our findings caution against using ecDHFR structures obtained at nonphysiological ionic strengths in interpreting catalytic events or in structure-based drug design.

Influence of solution ionic strength on the stabilities of M20 loop conformations in apo E. coli dihydrofolate reductase

Interactions among ions and their specific interactions with macromolecular solutes are known to play a central role in biomolecular stability. However, similar effects in the conformational stability of protein loops that play functional roles, such as binding ligands, proteins, and DNA/RNA molecules, remain relatively unexplored. A well-characterized enzyme that has such a functional loop is Escherichia coli dihydrofolate reductase (ecDHFR), whose so-called M20 loop has been observed in three ordered conformations in crystal structures. To explore how solution ionic strengths may affect the M20 loop conformation, we proposed a reaction coordinate that could quantitatively describe the loop conformation and used it to classify the loop conformations in representative ecDHFR x-ray structures crystallized in varying ionic strengths. The Protein Data Bank survey indicates that at ionic strengths (I) below the intracellular ion concentration-derived ionic strength in E. coli (I ≤ 0.237M), the ecDHFR M20 loop tends to adopt open/closed conformations, and rarely an occluded loop state, but when I is >0.237M, the loop tends to adopt closed/occluded conformations. Distance-dependent electrostatic potentials around the most mobile M20 loop region from molecular dynamics simulations of ecDHFR in equilibrated CaCl₂ solutions of varying ionic strengths show that high ionic strengths (I = 0.75/1.5M) can preferentially stabilize the loop in closed/occluded conformations. These results nicely correlate with conformations derived from ecDHFR structures crystallized in varying ionic strengths. Altogether, our results suggest caution in linking M20 loop conformations derived from crystal structures solved at ionic strengths beyond that tolerated by E. coli to the ecDHFR function.

On the importance of statistics in molecular simulations for thermodynamics, kinetics and simulation box size

Computational simulations, akin to wetlab experimentation, are subject to statistical fluctuations. Assessing the magnitude of these fluctuations, that is, assigning uncertainties to the computed results, is of critical importance to drawing statistically reliable conclusions. Here, we use a simulation box size as an independent variable, to demonstrate how crucial it is to gather sufficient amounts of data before drawing any conclusions about the potential thermodynamic and kinetic effects. In various systems, ranging from solvation free energies to protein conformational transition rates, we showcase how the proposed simulation box size effect disappears with increased sampling. This indicates that, if at all, the simulation box size only minimally affects both the thermodynamics and kinetics of the type of biomolecular systems presented in this work.